Leonard
1948 lines
113 KiB
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1948 lines
113 KiB
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<title>Athena AI News — Ranked by Clickability</title>
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.stack { display:grid; grid-template-columns:repeat(auto-fill,minmax(320px,1fr)); gap:12px; }
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<body>
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<header>
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<h1>Athena AI News</h1>
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<div class="sub">Auto-ranked by Clickability Index · decays with age so the stack flows top → bottom · generated 2026-07-12 02:41 UTC · 237 stories</div>
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</header>
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<main>
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<h2 class="sech">🔴 Top News</h2>
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<div class="grid">
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<article class="card big" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 5.9</span>
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<span class="score">🔥 0.32</span></div>
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<h3><a href="https://9to5mac.com/2026/07/10/apple-sues-openai-trade-secret-theft/" target="_blank" rel="noopener">Apple sues OpenAI, accuses ex-employees of stealing trade secrets</a></h3>
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</article>
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<article class="card big" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 6.1</span>
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<span class="score">🔥 0.32</span></div>
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<h3><a href="https://openai.com/index/gpt-5-6/" target="_blank" rel="noopener">GPT-5.6</a></h3>
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</article>
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<article class="card big" data-src="github">
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<div class="meta"><span class="src">github</span>
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<span class="time">13:00</span>
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<span class="sig">sig 2.4</span>
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<span class="score">🔥 0.30</span></div>
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<h3><a href="https://github.com/Doriandarko/texts-to-transformer" target="_blank" rel="noopener">texts-to-transformer: Train a tiny Transformer from scratch on your iMessage history, entirely on your Mac.</a></h3>
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<p class="summary">Train a tiny language model from scratch on your iMessage history, entirely on your Mac.</p>
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</article>
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<article class="card big" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 5.4</span>
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<span class="score">🔥 0.27</span></div>
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<h3><a href="https://cdn.openai.com/pdf/04d1d1e4-bc75-476a-97cf-49055cd98d31/cdc_proof.pdf" target="_blank" rel="noopener">GPT-5.6 Sol Ultra produces proof of the Cycle Double Cover Conjecture [pdf]</a></h3>
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</article>
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<article class="card big" data-src="github">
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<div class="meta"><span class="src">github</span>
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<span class="time">13:00</span>
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<span class="sig">sig 2.1</span>
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<span class="score">🔥 0.27</span></div>
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<h3><a href="https://github.com/eli-labz/Cognitive-Core-Skills" target="_blank" rel="noopener">Cognitive-Core-Skills: A universal, industry-neutral taxonomy of cognitive core skills (perception, memory, reasoning, plan</a></h3>
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<p class="summary">Cognitive core skills are the mental operating capabilities an LLM or AI Agent needs to move from chat response to useful digital co-worker.</p>
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</article>
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<article class="card big" data-src="github">
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<div class="meta"><span class="src">github</span>
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<span class="time">13:00</span>
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<span class="sig">sig 2.3</span>
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<span class="score">🔥 0.27</span></div>
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<h3><a href="https://github.com/FuelMagistrateLead/photoshop-ai-smart-enhance" target="_blank" rel="noopener">photoshop-ai-smart-enhance: AI-powered image enhancement extension for Adobe Photoshop CC 2024+. Intelligent exposure correction</a></h3>
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<p class="summary">photoshop-ai-smart-enhance is a machine learning extension that automates image quality improvements.</p>
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</article>
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<article class="card big" data-src="github">
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<div class="meta"><span class="src">github</span>
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<span class="time">13:00</span>
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<span class="sig">sig 1.7</span>
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<span class="score">🔥 0.25</span></div>
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<h3><a href="https://github.com/buynao/aipath" target="_blank" rel="noopener">aipath: Interactive AI General Education Course — 30 Lessons, Zero Math</a></h3>
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<p class="summary">↑ The homepage hero (Lesson 15 · the next-token game): an LLM guesses one token at a time — turn the temperature and watch its top-5 candidates reshape, from focused to “wild.</p>
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</article>
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<article class="card big" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 5.2</span>
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<span class="score">🔥 0.24</span></div>
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<h3><a href="https://ai-2040.com/" target="_blank" rel="noopener">AI 2040: Plan A</a></h3>
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</article></div>
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<h2 class="sech">📰 The Stack</h2>
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<h3 class="day">📅 2026-07-11</h3>
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<div class="stack">
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<article class="card" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 5.1</span>
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<span class="score">🔥 0.24</span></div>
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<h3><a href="https://nevo-project.epfl.ch/" target="_blank" rel="noopener">AI-generated videos to maximally drive a target brain region</a></h3>
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</article>
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<article class="card" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 5.2</span>
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<span class="score">🔥 0.23</span></div>
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<h3><a href="https://openai.com/index/chatgpt-for-your-most-ambitious-work/" target="_blank" rel="noopener">ChatGPT Work</a></h3>
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</article>
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<article class="card" data-src="hackernews">
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||
<div class="meta"><span class="src">hackernews</span>
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||
<span class="time">13:01</span>
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<span class="sig">sig 5.0</span>
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<span class="score">🔥 0.23</span></div>
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<h3><a href="https://casp.ac/reports/ai-enabled-terrorism" target="_blank" rel="noopener">How the terrorist group Boko Haram uses frontier AI</a></h3>
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</article>
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<article class="card" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 5.0</span>
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<span class="score">🔥 0.22</span></div>
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<h3><a href="https://www.pangram.com/blog/ai-in-your-feed" target="_blank" rel="noopener">AI content is everywhere on social media, especially LinkedIn</a></h3>
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</article>
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<article class="card" data-src="hackernews">
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<div class="meta"><span class="src">hackernews</span>
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<span class="time">13:01</span>
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<span class="sig">sig 4.8</span>
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<span class="score">🔥 0.22</span></div>
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<h3><a href="https://www.ello.com/blog/teaching-a-child-in-1000-ms" target="_blank" rel="noopener">Building a real-time AI tutor for 5-year-olds</a></h3>
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</article>
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<article class="card" data-src="github">
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<div class="meta"><span class="src">github</span>
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<span class="time">13:00</span>
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<span class="sig">sig 1.5</span>
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<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/grandgaming9321-prog/reality-engine" target="_blank" rel="noopener">reality-engine: Top Dynamic AI World Simulation & Storytelling Tools 2026</a></h3>
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</article>
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<article class="card" data-src="github">
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<div class="meta"><span class="src">github</span>
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||
<span class="time">13:00</span>
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||
<span class="sig">sig 1.5</span>
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<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/okesipoke/manuscript-phoneme-decipher" target="_blank" rel="noopener">manuscript-phoneme-decipher: Voynich Manuscript Decoded: Elu-Sinhala Phonetic Transcription & Vocabulary Toolkit 2026</a></h3>
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</article>
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<article class="card" data-src="github">
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<div class="meta"><span class="src">github</span>
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||
<span class="time">13:00</span>
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||
<span class="sig">sig 1.5</span>
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||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/Sujal-142/ai-image-clean-eraser" target="_blank" rel="noopener">ai-image-clean-eraser: AI-Powered Text Remover 2026: Auto-Detect & Manual Precision with HD Quality</a></h3>
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</article>
|
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<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
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||
<span class="sig">sig 1.5</span>
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||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/pravin6688/churn-triad-insights" target="_blank" rel="noopener">churn-triad-insights: LLM-Powered Churn Risk Analyzer for Scalable 2026 Decision Support</a></h3>
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</article>
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<article class="card" data-src="github">
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||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.5</span>
|
||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/jaimasih05-commits/swarm-foraging-qlearn" target="_blank" rel="noopener">swarm-foraging-qlearn: Q-Learning Swarm Foraging 2026: Multi-Agent RL in Dynamic Grid Environments</a></h3>
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</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.5</span>
|
||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/aminekago-web/Paradigm-Survival-Arena" target="_blank" rel="noopener">Paradigm-Survival-Arena: Top 6 AI Paradigms Fighting for Survival in 2026</a></h3>
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</article>
|
||
<article class="card" data-src="github">
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||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.5</span>
|
||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/reunios2024/cortex-sentinel-trading-nexus" target="_blank" rel="noopener">cortex-sentinel-trading-nexus: Self-Tuning Multi-Agent AI Trading System 2026: 8-Source Signal Fusion & Kronos Model</a></h3>
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</article>
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||
<article class="card" data-src="github">
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<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.5</span>
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||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/onlyoneshakibul/magic-eraser-studio" target="_blank" rel="noopener">magic-eraser-studio: AI Object Remover 2026 – Erase Distractions & Keep HD Quality</a></h3>
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</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.4</span>
|
||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/benlamiro/ShipGenAI" target="_blank" rel="noopener">ShipGenAI: 🚀 50 production-ready Generative AI SaaS apps — brand them, ship them, keep 100% of the revenue. Str</a></h3>
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</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.5</span>
|
||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://github.com/Aliu-AiRobot/ESEILANE" target="_blank" rel="noopener">ESEILANE: High-performance Knowledge Graph engine for AI, LLMs, and GraphRAG — built for the next generation o</a></h3>
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|
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</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.5</span>
|
||
<span class="score">🔥 0.21</span></div>
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<h3><a href="https://www.tryai.dev/blog/gpt-5.6-build-off-12-models" target="_blank" rel="noopener">GPT-5.6, Grok 4.5, Claude, and Muse Spark build the same 4 apps</a></h3>
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</article>
|
||
<article class="card" data-src="github">
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||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.4</span>
|
||
<span class="score">🔥 0.20</span></div>
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||
<h3><a href="https://github.com/Reyzowter/Hello-Agents" target="_blank" rel="noopener">Hello-Agents: 🤖 Building AI Agent Systems from Scratch — A comprehensive, practical tutorial from fundamentals to </a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.0</span>
|
||
<span class="score">🔥 0.19</span></div>
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||
<h3><a href="https://www.mixfont.com/ghost-font" target="_blank" rel="noopener">A font that humans can read but AI cannot</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.2</span>
|
||
<span class="score">🔥 0.18</span></div>
|
||
<h3><a href="https://github.com/Simpl3x3/ESEILANE" target="_blank" rel="noopener">ESEILANE: High-performance Knowledge Graph engine for AI, LLMs, and GraphRAG — built for the next generation o</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.2</span>
|
||
<span class="score">🔥 0.18</span></div>
|
||
<h3><a href="https://github.com/gaasher/Agent-Loop-Skills" target="_blank" rel="noopener">Agent-Loop-Skills: Loop until it's better — drop-in agentic loops (autoresearch, scientific writing, data analysis, cod</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.2</span>
|
||
<span class="score">🔥 0.18</span></div>
|
||
<h3><a href="https://github.com/SantanderAI/autoguardrails" target="_blank" rel="noopener">autoguardrails: Alignment-research scaffold (autoresearch-style) for LLM guardrails: search over a single policy.md </a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.2</span>
|
||
<span class="score">🔥 0.18</span></div>
|
||
<h3><a href="https://github.com/wanshuiyin/Anti-Autoresearch" target="_blank" rel="noopener">Anti-Autoresearch: Don't trust an autoresearch paper at face value. Reviewer-side integrity forensics (self-consistency</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 3.7</span>
|
||
<span class="score">🔥 0.18</span></div>
|
||
<h3><a href="https://www.nytimes.com/2026/07/10/technology/apple-openai-lawsuit.html" target="_blank" rel="noopener">Apple sues OpenAI, accusing it of stealing company secrets</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.2</span>
|
||
<span class="score">🔥 0.17</span></div>
|
||
<h3><a href="https://www.anthropic.com/news/ben-bernanke" target="_blank" rel="noopener">Ben Bernanke Joins Anthropic Oversight Trust</a></h3>
|
||
|
||
</article>
|
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<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
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||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.3</span>
|
||
<span class="score">🔥 0.17</span></div>
|
||
<h3><a href="https://github.com/MADEVAL/FerryAI" target="_blank" rel="noopener">FerryAI: Native AI inference for PHP 8.3+ - run ONNX, GGUF (llama.cpp) and RubixML models directly in your PH</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.1</span>
|
||
<span class="score">🔥 0.17</span></div>
|
||
<h3><a href="https://mitpress.mit.edu/9780262053198/simpolitics/" target="_blank" rel="noopener">SimPolitics: America’s quest to solve politics with computers</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.2</span>
|
||
<span class="score">🔥 0.17</span></div>
|
||
<h3><a href="https://github.com/ronak-create/FableCut" target="_blank" rel="noopener">Show HN: FableCut – A browser video editor AI agents can drive (zero deps)</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.4</span>
|
||
<span class="score">🔥 0.16</span></div>
|
||
<h3><a href="https://news.ycombinator.com/item/48847834" target="_blank" rel="noopener">Show HN: Reverse-engineering web apps into agent tools</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 3.9</span>
|
||
<span class="score">🔥 0.16</span></div>
|
||
<h3><a href="https://entire.io/blog/how-version-control-will-evolve-for-the-agent-boom" target="_blank" rel="noopener">How version control will evolve for the agent boom</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 3.7</span>
|
||
<span class="score">🔥 0.16</span></div>
|
||
<h3><a href="https://www.microcenter.com/site/mc-news/article/amd-ryzen-ai-halo-review.aspx" target="_blank" rel="noopener">Hands-On with the AMD Ryzen AI Halo</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 3.9</span>
|
||
<span class="score">🔥 0.16</span></div>
|
||
<h3><a href="https://www.fadingmaize.com" target="_blank" rel="noopener">Show HN: Reviving my 2001 college band with AI</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 3.6</span>
|
||
<span class="score">🔥 0.14</span></div>
|
||
<h3><a href="https://blog.mozilla.ai/the-control-layer-why-the-next-era-of-ai-is-about-infrastructure-not-just-models/" target="_blank" rel="noopener">The next era of AI is about infrastructure, not just models</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08768v1" target="_blank" rel="noopener">UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08763v1" target="_blank" rel="noopener">OpenCoF: Learning to Reason Through Video Generation</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08758v1" target="_blank" rel="noopener">Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08757v1" target="_blank" rel="noopener">Score Accuracy Along the Forward Diffusion Does Not Certify Numerical Stability in Diffusion Sampling</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08756v1" target="_blank" rel="noopener">MulTTiPop: A Multitrack Transcription Dataset for Pop Music</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.3</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08754v1" target="_blank" rel="noopener">SLORR: Simple and Efficient In-Training Low-Rank Regularization</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08748v1" target="_blank" rel="noopener">Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 1.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08746v1" target="_blank" rel="noopener">Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08745v1" target="_blank" rel="noopener">AUTOPILOT VQA: Benchmarking Vision-Language Models for Incident-Centric Dashcam Understanding</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 4.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08741v1" target="_blank" rel="noopener">ARDY: Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08740v1" target="_blank" rel="noopener">Workflow as Knowledge: Semantic Persistence for LLM-Mediated Workflows</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08734v1" target="_blank" rel="noopener">The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08733v1" target="_blank" rel="noopener">Super Weights in LLMs and the Failure of Selective Training</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.3</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08731v1" target="_blank" rel="noopener">Validity of LLMs as data annotators: AMALIA on authority</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.3</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08725v1" target="_blank" rel="noopener">Pose-to-Biomechanics: Bridging 3D Human Pose Estimation and Biomechanical Attribute Prediction</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08724v1" target="_blank" rel="noopener">Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.3</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08717v1" target="_blank" rel="noopener">Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08716v1" target="_blank" rel="noopener">Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08711v1" target="_blank" rel="noopener">LTM: Large-scale Terrain Model for Wildfire-prone Landscapes</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.08703v1" target="_blank" rel="noopener">MPFlow: Learning Budgeted Max-Flow Optimization on the Lightning Network with Deep Graph Reinforcement Learning</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 9.4</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/zai-org/GLM-5.2" target="_blank" rel="noopener">GLM-5.2 (text-generation) by zai-org</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 9.3</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro" target="_blank" rel="noopener">DeepSeek-V4-Pro (text-generation) by deepseek-ai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 9.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/deepseek-ai/DeepSeek-R1" target="_blank" rel="noopener">DeepSeek-R1 (text-generation) by deepseek-ai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 9.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct" target="_blank" rel="noopener">Llama-3.1-8B-Instruct (text-generation) by meta-llama</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/black-forest-labs/FLUX.1-dev" target="_blank" rel="noopener">FLUX.1-dev (text-to-image) by black-forest-labs</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/yuxinlu1/gemma-4-12B-coder-fable5-composer2.5-v1-GGUF" target="_blank" rel="noopener">gemma-4-12B-coder-fable5-composer2.5-v1-GGUF (text-generation) by yuxinlu1</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B" target="_blank" rel="noopener">Meta-Llama-3-8B (text-generation) by meta-llama</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/meta-llama/Llama-2-7b-chat-hf" target="_blank" rel="noopener">Llama-2-7b-chat-hf (text-generation) by meta-llama</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct" target="_blank" rel="noopener">Meta-Llama-3-8B-Instruct (text-generation) by meta-llama</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/bigscience/bloom" target="_blank" rel="noopener">bloom (text-generation) by bigscience</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/openai/gpt-oss-120b" target="_blank" rel="noopener">gpt-oss-120b (text-generation) by openai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/openai/gpt-oss-20b" target="_blank" rel="noopener">gpt-oss-20b (text-generation) by openai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/microsoft/phi-2" target="_blank" rel="noopener">phi-2 (text-generation) by microsoft</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0" target="_blank" rel="noopener">stable-diffusion-xl-base-1.0 (text-to-image) by stabilityai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2" target="_blank" rel="noopener">Mistral-7B-Instruct-v0.2 (text-generation) by mistralai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/mistralai/Mistral-7B-v0.1" target="_blank" rel="noopener">Mistral-7B-v0.1 (text-generation) by mistralai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/deepseek-ai/DeepSeek-V3" target="_blank" rel="noopener">DeepSeek-V3 (text-generation) by deepseek-ai</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/CompVis/stable-diffusion-v1-4" target="_blank" rel="noopener">stable-diffusion-v1-4 (text-to-image) by CompVis</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct" target="_blank" rel="noopener">Llama-3.3-70B-Instruct (text-generation) by meta-llama</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="huggingface">
|
||
<div class="meta"><span class="src">huggingface</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 8.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://huggingface.co/google/gemma-7b" target="_blank" rel="noopener">gemma-7b (text-generation) by google</a></h3>
|
||
|
||
</article></div>
|
||
<h3 class="day">📅 2026-07-10</h3>
|
||
<div class="stack">
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 4.2</span>
|
||
<span class="score">🔥 0.22</span></div>
|
||
<h3><a href="https://github.com/DietrichGebert/ponytail" target="_blank" rel="noopener">ponytail: Makes your AI agent think like the laziest senior dev in the room. The best code is the code you nev</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.3</span>
|
||
<span class="score">🔥 0.17</span></div>
|
||
<h3><a href="https://github.com/elder-plinius/T3MP3ST" target="_blank" rel="noopener">T3MP3ST: autonomous red teaming platform; multi-agent offensive-security meta-harness</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.0</span>
|
||
<span class="score">🔥 0.16</span></div>
|
||
<h3><a href="https://github.com/omnigent-ai/omnigent" target="_blank" rel="noopener">omnigent: Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Curs</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.0</span>
|
||
<span class="score">🔥 0.15</span></div>
|
||
<h3><a href="https://github.com/synthetic-sciences/openscience" target="_blank" rel="noopener">openscience: The open-source AI workbench for scientific research</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.8</span>
|
||
<span class="score">🔥 0.14</span></div>
|
||
<h3><a href="https://github.com/isjiamu/gzh-design-skill" target="_blank" rel="noopener">gzh-design-skill: 把 Markdown 一键排成可直接粘进公众号编辑器的精致 HTML —— 6 套精选主题 + 主题生成器 + 双关卡校验。An AI-agent skill that turns Markdown </a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.8</span>
|
||
<span class="score">🔥 0.14</span></div>
|
||
<h3><a href="https://github.com/jamesob/local-llm" target="_blank" rel="noopener">local-llm: Everything I know about running LLMs locally</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.6</span>
|
||
<span class="score">🔥 0.14</span></div>
|
||
<h3><a href="https://github.com/Forward-Future/loopy" target="_blank" rel="noopener">loopy: A library of practical AI-agent loops and an installable skill for finding, adapting, and designing </a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.7</span>
|
||
<span class="score">🔥 0.14</span></div>
|
||
<h3><a href="https://github.com/HUANGCHIHHUNGLeo/claude-real-video" target="_blank" rel="noopener">claude-real-video: Let Claude (or any LLM) actually watch a video — scene-aware, deduplicated frames + transcript, from</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.5</span>
|
||
<span class="score">🔥 0.13</span></div>
|
||
<h3><a href="https://github.com/shy3130/tickflow-stock-panel" target="_blank" rel="noopener">tickflow-stock-panel: 自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.5</span>
|
||
<span class="score">🔥 0.13</span></div>
|
||
<h3><a href="https://github.com/oomol-lab/open-connector" target="_blank" rel="noopener">open-connector: Open-source auth gateway connecting 1000+ SaaS providers to AI agents through SDK, CLI, MCP, HTTP, a</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.6</span>
|
||
<span class="score">🔥 0.13</span></div>
|
||
<h3><a href="https://github.com/jmerelnyc/Talos" target="_blank" rel="noopener">Talos: GPU worker client for the Talos network. Pairs with your Talos account, serves open-model inference </a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.5</span>
|
||
<span class="score">🔥 0.13</span></div>
|
||
<h3><a href="https://github.com/simonlin1212/Vibe-Research" target="_blank" rel="noopener">Vibe-Research: Vibe-Research: Your Personal Trading Research Agent · A股/美股/港股 的个人投研 Agent：每日复盘、资讯雷达、个股数据、板块中心、我的持仓、</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.4</span>
|
||
<span class="score">🔥 0.13</span></div>
|
||
<h3><a href="https://github.com/Forsy-AI/agent-apprenticeship" target="_blank" rel="noopener">agent-apprenticeship: The living ecosystem where AI agents complete tasks through workflow loops, improve through iterativ</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.4</span>
|
||
<span class="score">🔥 0.12</span></div>
|
||
<h3><a href="https://github.com/uzairansaruzi/hermex" target="_blank" rel="noopener">hermex: Native iPhone app for your Hermes agent</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.4</span>
|
||
<span class="score">🔥 0.12</span></div>
|
||
<h3><a href="https://github.com/Kulaxyz/self-learning-skills" target="_blank" rel="noopener">self-learning-skills: A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won g</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.5</span>
|
||
<span class="score">🔥 0.12</span></div>
|
||
<h3><a href="https://github.com/nexu-io/motion-anything" target="_blank" rel="noopener">motion-anything: ✨ The agentic motion layer — an open-source, chat-native motion engine. Describe the feeling; your A</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.3</span>
|
||
<span class="score">🔥 0.12</span></div>
|
||
<h3><a href="https://github.com/ai4s-research/open-science" target="_blank" rel="noopener">open-science: Open Science Desktop — local-first, model-agnostic AI research workbench for macOS, Windows & Linux.</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.12</span></div>
|
||
<h3><a href="https://github.com/lycorp-jp/sim-use" target="_blank" rel="noopener">sim-use: Give your AI agent eyes and hands on iOS Simulator and Android emulator/devices.</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.3</span>
|
||
<span class="score">🔥 0.12</span></div>
|
||
<h3><a href="https://github.com/Pluviobyte/rnskill" target="_blank" rel="noopener">rnskill: 雪踏乌云的 AI Agent Skills 集合</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.3</span>
|
||
<span class="score">🔥 0.12</span></div>
|
||
<h3><a href="https://github.com/SmileLikeYe/agent-chief" target="_blank" rel="noopener">agent-chief: Attention is your scarcest resource. Chief is the local-first layer that guards it — turning every a</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.3</span>
|
||
<span class="score">🔥 0.10</span></div>
|
||
<h3><a href="https://www.alecscollon.com/blog/llm-burnout/" target="_blank" rel="noopener">I think I have LLM burnout</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.09</span></div>
|
||
<h3><a href="https://microsoft.github.io/flint-chart/#/" target="_blank" rel="noopener">Show HN: Microsoft releases Flint, a visualization language for AI agents</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.1</span>
|
||
<span class="score">🔥 0.08</span></div>
|
||
<h3><a href="https://cognition.com/blog/swe-1-7" target="_blank" rel="noopener">SWE-1.7 Reach Near GPT 5.5 and Opus Intelligence</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.0</span>
|
||
<span class="score">🔥 0.08</span></div>
|
||
<h3><a href="https://combine-lab.github.io/blog/2026/07/07/fable-is-not-a-useful-model.html" target="_blank" rel="noopener">The classifiers Anthropic puts in front of Fable are too zealous</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.7</span>
|
||
<span class="score">🔥 0.08</span></div>
|
||
<h3><a href="https://arstechnica.com/ai/2026/07/we-cannot-choose-to-become-idiots-the-ai-cheating-scandal-roiling-brown-university/" target="_blank" rel="noopener">Suspecting AI cheating, Ivy League prof ordered in-person final; scores fell 50%</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.7</span>
|
||
<span class="score">🔥 0.08</span></div>
|
||
<h3><a href="https://www.tryai.dev/blog/grok-4.5-vs-gpt-5.5-vs-claude-build-off" target="_blank" rel="noopener">We made Grok 4.5, GPT-5.5, and Claude build the same apps</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.5</span>
|
||
<span class="score">🔥 0.07</span></div>
|
||
<h3><a href="https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase" target="_blank" rel="noopener">Benchmarking coding agents on Databricks' multi-million line codebase</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.4</span>
|
||
<span class="score">🔥 0.07</span></div>
|
||
<h3><a href="https://www.worksinprogress.news/p/ai-is-bottlenecked-by-the-grid" target="_blank" rel="noopener">What's slowing down the AI buildout</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.4</span>
|
||
<span class="score">🔥 0.07</span></div>
|
||
<h3><a href="https://thetruthasiseeitnow.com/ai-slop-starts-with-the-codebase-itself/" target="_blank" rel="noopener">AI changes the economics of software rewrites</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.6</span>
|
||
<span class="score">🔥 0.06</span></div>
|
||
<h3><a href="https://news.ycombinator.com/item/48834961" target="_blank" rel="noopener">Ask HN: Another "Hacker News" with less AI and more human-focused hacking news?</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 6.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1urxvxh/i_built_imgnet_a_face_verification_model_that/" target="_blank" rel="noopener">I built IMGNet – a face verification model that identifies people using sign patterns, not cosine similarity [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 6.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1upvkp5/phd_thesis_on_differentiable_ray_tracing_for/" target="_blank" rel="noopener">Ph.D. thesis on Differentiable Ray Tracing for Radio Propagation Modeling [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 6.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1un63hv/proposal_use_semantic_compression_as_input/" target="_blank" rel="noopener">Proposal: Use semantic compression as input diffusion to read sessions larger than the context window [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1urvxgb/talosxii_handwritten_autograd_small_rlmlp_stack/" target="_blank" rel="noopener">Talos-XII: hand-written autograd + small RL/MLP stack in Rust, applied to gacha probability modeling (no tch-rs/ndarray/PyTorch) — looking for benchmark help on ARM/AVX-512/GPU [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1up0azr/cpu_tts_benchmark_with_utmos_mos_scoring_kokoro/" target="_blank" rel="noopener">CPU TTS benchmark with UTMOS MOS scoring: Kokoro, Supertonic, Inflect-Nano, and Kyutai's new Pocket TTS [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
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||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1unw5un/competence_gate_gating_tooluse_on_a_small_models/" target="_blank" rel="noopener">Competence Gate: gating tool-use on a small model's internal confidence signal instead of its verbalised one — Qwen3.5-4B, open weights [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
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||
<div class="meta"><span class="src">reddit</span>
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||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1usa46w/hyperparameter_tuning_approach_question_r/" target="_blank" rel="noopener">Hyperparameter tuning approach question [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1uq68li/what_if_a_model_could_only_learn_what_trusted/" target="_blank" rel="noopener">What if a model could only learn what trusted LoRA adapters can express? [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1ur1fnz/agentic_safety_triggers_arent_textual_safety/" target="_blank" rel="noopener">Agentic safety triggers aren't textual safety triggers — MCP attacks that beat SOTA guardrails more than half the time (code + dataset) [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
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||
<div class="meta"><span class="src">reddit</span>
|
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<span class="time">13:00</span>
|
||
<span class="sig">sig 5.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1uoejrl/best_models_for_generating_redteam_attacks_also/" target="_blank" rel="noopener">Best models for generating red-team attacks? Also looking for public datasets [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1uon503/does_anyone_have_a_name_for_that_subtle_sameness/" target="_blank" rel="noopener">Does anyone have a name for that subtle "Sameness" creeping into model outputs lately? [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1upzxk2/torchjd_training_with_multiple_losses_in_pytorch_p/" target="_blank" rel="noopener">TorchJD: Training with multiple losses in PyTorch [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1uoz5jo/trace_opensource_hierarchical_memory_for_llm/" target="_blank" rel="noopener">TRACE: open-source hierarchical memory for LLM agents, 82.5% on MemoryAgentBench’s EventQA using gpt-oss-20B [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1uo92vz/i_built_an_open_fromscratch_mt_pipeline_parallel/" target="_blank" rel="noopener">I built an open, from-scratch MT pipeline + parallel corpus for Tunisian Darija (Arabizi) early baseline, and I'm growing it into a curated community corpus [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1umqfd2/h64lm_a_249mparameter_mixtureofexperts/" target="_blank" rel="noopener">H64LM: A 249M-parameter Mixture-of-Experts Transformer built from scratch in PyTorch [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1ulrdw9/improving_machinetranslated_novels_via_style/" target="_blank" rel="noopener">Improving machine-translated novels via style transfer — looking for advice on the faithfulness/fluency tradeoff [P]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1uqtamz/dinov2_way_worse_than_siglip_in_knn_is_this/" target="_blank" rel="noopener">DINOv2 way worse than SigLIP in k-NN. Is this expected? [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1upofuw/mira_multiplayer_interactive_world_models_trained/" target="_blank" rel="noopener">MIRA: Multiplayer Interactive World Models trained on Rocket League [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1upjftu/icml_position_track_want_better_ml_reviews_stop/" target="_blank" rel="noopener">ICML Position Track: Want Better ML Reviews? Stop Asking Nicely and Start Incentivizing with a Credit System [D]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1uov7or/machine_learning_industry_job_requirements_used/" target="_blank" rel="noopener">Machine learning industry job requirements used to be myopic, but now it feels impossible. Anyone else seeing this? [D]</a></h3>
|
||
|
||
</article></div>
|
||
<h3 class="day">📅 2026-07-09</h3>
|
||
<div class="stack">
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.3</span>
|
||
<span class="score">🔥 0.07</span></div>
|
||
<h3><a href="https://github.com/XiaomiMiMo/MiMo-Code" target="_blank" rel="noopener">MiMo-Code: MiMo Code: Where Models and Agents Co-Evolve</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.4</span>
|
||
<span class="score">🔥 0.05</span></div>
|
||
<h3><a href="https://github.com/chuspeeism/dashiAI-ppt-skill" target="_blank" rel="noopener">dashiAI-ppt-skill: An AI-agent skill that generates browser-editable presentations from multiple visual themes, exporta</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.05</span></div>
|
||
<h3><a href="https://github.com/lingbol088-spec/reverse-flow-skill" target="_blank" rel="noopener">reverse-flow-skill: 面向 AI Agent / Codex 的本地 CTF 逆向工程流程技能。加载后通过“真心为你”进入逆向模式，默认在本地沙盒、CTF、crackme、wargame 或训练靶场环境中工作，按“分析 →</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.5</span>
|
||
<span class="score">🔥 0.04</span></div>
|
||
<h3><a href="https://noma.security/blog/gitlost-how-we-tricked-githubs-ai-agent-into-leaking-private-repos/" target="_blank" rel="noopener">GitLost: We Tricked GitHub's AI Agent into Leaking Private Repos</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.03</span></div>
|
||
<h3><a href="https://odra.dev/slopfix/" target="_blank" rel="noopener">We charge $10k a week to delete AI-generated code</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.0</span>
|
||
<span class="score">🔥 0.03</span></div>
|
||
<h3><a href="https://twitter.com/OpenAI/status/2074704958419792299" target="_blank" rel="noopener">GPT-5.6 Sol, along with Terra and Luna, will launch publicly this Thursday</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.4</span>
|
||
<span class="score">🔥 0.03</span></div>
|
||
<h3><a href="https://replicated.live/blog/away" target="_blank" rel="noopener">Automating AI Away</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 4.1</span>
|
||
<span class="score">🔥 0.03</span></div>
|
||
<h3><a href="https://firesphere.dev/articles/yes-actually-i-do-fucking-mind" target="_blank" rel="noopener">Re: I'm Begging You to Leave Your AI Note-Taker at Home</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 3.6</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://blog.zksecurity.xyz/posts/circl-bugs/" target="_blank" rel="noopener">AI Meets Cryptography 1: What AI Found in Cloudflare's Circl</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 3.7</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://github.com/kklimuk/docx-cli" target="_blank" rel="noopener">Show HN: Docx-CLI: agents read/edit Word docs using 1/2 the time and tokens</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">05:24</span>
|
||
<span class="sig">sig 4.5</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://www.fastcompany.com/91520702/y-combinator-garry-tan-agentic-ai-social-media" target="_blank" rel="noopener">YC CEO says he ships 37K LoC AI code per day. A developer looked under the hood</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">05:24</span>
|
||
<span class="sig">sig 3.3</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://www.reuters.com/world/beijing-is-looking-curbing-overseas-access-chinas-top-ai-models-sources-say-2026-07-07/" target="_blank" rel="noopener">Beijing is looking at curbing overseas access to China's top AI models</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">05:24</span>
|
||
<span class="sig">sig 2.1</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://thebeach.dev/posts/lisp-agent/" target="_blank" rel="noopener">An agent in 100 lines of Lisp</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 4.3</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07708v1" target="_blank" rel="noopener">Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.3</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07707v1" target="_blank" rel="noopener">Co-LMLM: Continuous-Query Limited Memory Language Models</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07706v1" target="_blank" rel="noopener">The Key to Going Linear: Analysis-Driven Transformer Linearization</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07702v1" target="_blank" rel="noopener">From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07696v1" target="_blank" rel="noopener">Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07695v1" target="_blank" rel="noopener">Institutional Red-Teaming: Deployment Rules, Not Just Models, Causally Shape Multi-Agent AI Safety</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07693v1" target="_blank" rel="noopener">Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07690v1" target="_blank" rel="noopener">Agon: Competitive Cross-Model RL with Implicit Rival Grading of Reasoning</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07683v1" target="_blank" rel="noopener">ECGLight: Compute-Light Framework For Paper ECG Digitization and Myocardial Infarction Screening</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07682v1" target="_blank" rel="noopener">Neural Operator-enabled Topology-informed Evolutionary Strategy for PDE-Constrained Optimization</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07680v1" target="_blank" rel="noopener">Any-Dimensional Learning by Sampling</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07678v1" target="_blank" rel="noopener">How Data Shapes RoPE Frequency Usage: From Positional Scale Matching to Length Generalization</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 3.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07676v1" target="_blank" rel="noopener">SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07674v1" target="_blank" rel="noopener">Max Out GRPO Signal: Adaptive Trace Prefix Control for Hard Reasoning Problems</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07673v1" target="_blank" rel="noopener">MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07671v1" target="_blank" rel="noopener">PeTeR: Post-Training Robustification of Probabilistic Circuits</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07670v1" target="_blank" rel="noopener">Does Bielik Know What It Doesn't Know? Activation Dispersion Separates Entity Familiarity from Factual Reliability Across Model Scale</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 6.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07669v1" target="_blank" rel="noopener">DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07665v1" target="_blank" rel="noopener">Guidance Breaks the Fitted Operator: A Terminal-Fitted Repair for Classifier-Free Guidance</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="arxiv">
|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.07663v1" target="_blank" rel="noopener">Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 6.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1ul3ohk/making_optimization_work_when_labels_are_scarce_r/" target="_blank" rel="noopener">Making Optimization Work When Labels Are Scarce [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 5.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1unt64q/if_deepmind_or_anthropic_is_doing_your_exact/" target="_blank" rel="noopener">If DeepMind or Anthropic is doing your exact research topic, do you still continue? [D]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 4.8</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1up3kby/edge_ai_asl_recognition_on_raspberry_pi_5_looking/" target="_blank" rel="noopener">Edge AI ASL Recognition on Raspberry Pi 5 – Looking for Feedback on My System Design [P]</a></h3>
|
||
|
||
</article></div>
|
||
<h3 class="day">📅 2026-07-08</h3>
|
||
<div class="stack">
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 3.0</span>
|
||
<span class="score">🔥 0.03</span></div>
|
||
<h3><a href="https://github.com/cobusgreyling/loop-engineering" target="_blank" rel="noopener">loop-engineering: Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems </a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://github.com/SuperJJ007/CSSwitch" target="_blank" rel="noopener">CSSwitch: 帮你的 Claude Science 一键接入你自己的 API：DeepSeek / 通义千问 / 智谱 GLM / Kimi / MiniMax / 小米 MiMo / 硅基流动 / OpenRou</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">13:00</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://github.com/ComputeRoyale/Compute-Royale" target="_blank" rel="noopener">Compute-Royale: Bet on AI agents racing real GPUs. They rent compute, do hash-verified work, earn and you stake Sola</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 5.6</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://martinalderson.com/posts/the-upcoming-ai-margin-collapse-part-1-glm-5-2/" target="_blank" rel="noopener">GLM 5.2 and the coming AI margin collapse</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 5.4</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://www.anthropic.com/research/global-workspace" target="_blank" rel="noopener">A global workspace in language models</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 5.3</span>
|
||
<span class="score">🔥 0.02</span></div>
|
||
<h3><a href="https://www.lttlabs.com/articles/2026/07/06/amd-ryzen-ai-halo" target="_blank" rel="noopener">AMD Ryzen AI Halo – $4k AI Dev Kit</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.9</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://ternlight-demo.vercel.app/" target="_blank" rel="noopener">Ternlight – 7 MB embedding model that runs in browser (WASM)</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.9</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://spectrum.ieee.org/small-language-models-ai-pharmaceuticals" target="_blank" rel="noopener">Small AI Models Gain Traction In places with unreliable networks</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.7</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/iOfficeAI/OfficeCLI" target="_blank" rel="noopener">OfficeCLI: Office suite for AI agents to read and edit Microsoft Office files</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:02</span>
|
||
<span class="sig">sig 5.1</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://raheeljunaid.com/blog/anthropics-method-to-losing-goodwill-in-a-few-easy-steps/" target="_blank" rel="noopener">Anthropic's Method to Losing Goodwill in a Few Easy Steps</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.4</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://www.wsj.com/tech/ai/ai-workers-tech-ceos-job-losses-afc71e15" target="_blank" rel="noopener">Big Tech Has Suddenly Flipped on the AI Jobs Wipeout Scenario</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.3</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://www.kapa.ai/blog/how-we-prune-rag-context" target="_blank" rel="noopener">Pruning RAG context down to what the answer actually needs</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.2</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://www.apollo.com/wealth/insights-news/insights/daily-spark/ai-the-roi-runway-could-be-long-outside-the-tech-sector" target="_blank" rel="noopener">AI: The ROI Runway Could Be Long Outside the Tech Sector</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.1</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://oztalking.com/en/issues/hidden-4gb-ai-model" target="_blank" rel="noopener">Google Chrome Installed a 4GB AI Model on Your PC</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:02</span>
|
||
<span class="sig">sig 4.2</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://rruxandra.github.io/regression-to-the-mean.html" target="_blank" rel="noopener">Regression to the Mean: on LLMs and the quiet death of the new</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.9</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/JimLiu/baoyu-design" target="_blank" rel="noopener">baoyu-design: Run Claude Design locally as an Agent Skill — Cursor, Claude Code & more. Produce polished UI mockup</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">13:02</span>
|
||
<span class="sig">sig 4.0</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://www.breef.com/breefingroom/articles/the-ai-marketing-backlash-why-ai-first-brands-are-starting-to-fall-flat" target="_blank" rel="noopener">The AI Marketing Backlash: Why 'AI-First' Brands Are Starting to Fall Flat</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.5</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/agent0ai/dox" target="_blank" rel="noopener">dox: Self-documenting AGENTS.md</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.5</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/superloglabs/superlog" target="_blank" rel="noopener">superlog: Open-source observability tool that uses AI agents to self-heal your software</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.4</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/amElnagdy/guard-skills" target="_blank" rel="noopener">guard-skills: Guard skills for coding agents, quality gates that catch AI-generated failure modes in code, tests, </a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.7</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/orange2ai/renwei-writing" target="_blank" rel="noopener">renwei-writing: 人味儿写作 · An AI agent skill: edit people's words without erasing the person behind them</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 4.0</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/modiqo/skillspec" target="_blank" rel="noopener">skillspec: SkillSpec makes agent skills followable, testable, and provable with Doctor risk reports, guided imp</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.5</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/alchaincyf/fanbox" target="_blank" rel="noopener">fanbox: vibe coding 的驾驶舱：左边文件，右边/下边终端，中间看清每一次改动。 / The cockpit for vibe coding: browse files on the left, co</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.6</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/majidmanzarpour/threejs-game-skills" target="_blank" rel="noopener">threejs-game-skills: Agent skills for building playable, polished Three.js browser games with gameplay, AAA-style graphic</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="github">
|
||
<div class="meta"><span class="src">github</span>
|
||
<span class="time">05:51</span>
|
||
<span class="sig">sig 3.5</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://github.com/modiqo/cliare" target="_blank" rel="noopener">cliare: CLI agent-readiness measurement, command-shape inference, and CI scorecards</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="hackernews">
|
||
<div class="meta"><span class="src">hackernews</span>
|
||
<span class="time">05:53</span>
|
||
<span class="sig">sig 4.6</span>
|
||
<span class="score">🔥 0.01</span></div>
|
||
<h3><a href="https://tomtunguz.com/ai-spend-breakeven-2029/" target="_blank" rel="noopener">When AI Costs More Than the Engineer</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">05:52</span>
|
||
<span class="sig">sig 5.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/LocalLLaMA/comments/1uq0h4o/i_tested_freshly_merged_dflash_in_llamacpp_on/" target="_blank" rel="noopener">I tested freshly merged DFlash in llama.cpp on Qwen 3.6 27B Local AI win. 4.44x faster at 36K context. Here are my findings RTX 6000 PRO.</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 6.0</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://www.reddit.com/r/LocalLLaMA/comments/1uqmbv7/literature_review_llm_inference_at_the_edge/" target="_blank" rel="noopener">Literature Review: LLM Inference at the Edge: Mobile, NPU, and GPU Performance Efficiency Trade-offs Under Sustained Load | Bnechmarking LLMs on Phones [R]</a></h3>
|
||
|
||
</article>
|
||
<article class="card" data-src="reddit">
|
||
<div class="meta"><span class="src">reddit</span>
|
||
<span class="time">13:01</span>
|
||
<span class="sig">sig 5.2</span>
|
||
<span class="score">🔥 0.00</span></div>
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<h3><a href="https://www.reddit.com/r/MachineLearning/comments/1ukgwk1/a_systemlevel_approach_to_prompt_injection/" target="_blank" rel="noopener">A system-level approach to prompt injection: separating instruction and data channels in LLM agents [P]</a></h3>
|
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<div class="meta"><span class="src">reddit</span>
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<span class="time">13:01</span>
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<span class="sig">sig 5.0</span>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://www.reddit.com/r/LocalLLaMA/comments/1uqpers/deepseek_v4_flash_with_dspark_via_sglang/" target="_blank" rel="noopener">DeepSeek V4 Flash with DSpark via SGLang</a></h3>
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<span class="time">15:39</span>
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<span class="sig">sig 3.2</span>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://techcrunch.com/2026/07/07/savis-app-aims-to-protect-consumers-from-realistic-ai-scams-like-kidnappers-demanding-ransom/" target="_blank" rel="noopener">Savi’s app aims to protect consumers from realistic AI scams like kidnappers demanding ransom</a></h3>
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<div class="meta"><span class="src">arxiv</span>
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<span class="time">15:44</span>
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<span class="sig">sig 6.1</span>
|
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://arxiv.org/abs/2607.06565v1" target="_blank" rel="noopener">ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation</a></h3>
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<div class="meta"><span class="src">arxiv</span>
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<span class="time">15:44</span>
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<span class="sig">sig 3.4</span>
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<span class="score">🔥 0.00</span></div>
|
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<h3><a href="https://arxiv.org/abs/2607.06546v1" target="_blank" rel="noopener">Graph Convolutional Attention: A Spectral Perspective on Graph Denoising and Diffusion</a></h3>
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<div class="meta"><span class="src">arxiv</span>
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<span class="time">15:44</span>
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<span class="sig">sig 3.1</span>
|
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<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06544v1" target="_blank" rel="noopener">Rethinking Indic AI from a Lens of Cultural Heritage Preservation</a></h3>
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<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
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<span class="sig">sig 1.8</span>
|
||
<span class="score">🔥 0.00</span></div>
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<h3><a href="https://arxiv.org/abs/2607.06542v1" target="_blank" rel="noopener">On the feasibility of dependency parsing of non-human sequences without a gold standard. Is evaluation possible in other species?</a></h3>
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<div class="meta"><span class="src">arxiv</span>
|
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<span class="time">15:44</span>
|
||
<span class="sig">sig 2.5</span>
|
||
<span class="score">🔥 0.00</span></div>
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<h3><a href="https://arxiv.org/abs/2607.06540v1" target="_blank" rel="noopener">Hierarchical Acoustic-Semantic Modeling: Modality Separation and Semantic Coherence for Full-Duplex SLMs</a></h3>
|
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|
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<div class="meta"><span class="src">arxiv</span>
|
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<span class="time">15:44</span>
|
||
<span class="sig">sig 4.8</span>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://arxiv.org/abs/2607.06532v1" target="_blank" rel="noopener">GraphBU: MILP Instance Generation with Graph-Native Block Units</a></h3>
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<div class="meta"><span class="src">arxiv</span>
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<span class="time">15:44</span>
|
||
<span class="sig">sig 5.4</span>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://arxiv.org/abs/2607.06531v1" target="_blank" rel="noopener">The Large Cancer Assistant (LCA): A Model-Agnostic Orchestration Framework for Scalable Clinical Decision Support in Oncology</a></h3>
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<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06529v1" target="_blank" rel="noopener">Life Style Levels: Neighborhood Delineation using Geospatial Data</a></h3>
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<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 5.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06527v1" target="_blank" rel="noopener">RSF-GLLM: Bridging the Semantic Gap in Multi-Hop Knowledge Graph QA via Recurrent Soft-Flow and Decoupled LLM Generation</a></h3>
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|
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<span class="time">15:44</span>
|
||
<span class="sig">sig 3.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06523v1" target="_blank" rel="noopener">DepthWeave-KV: Token-Adaptive Cross-Layer Residual Factorization for Long-Context KV Cache Compression</a></h3>
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||
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|
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<span class="time">15:44</span>
|
||
<span class="sig">sig 4.7</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06522v1" target="_blank" rel="noopener">Bridging Physical Reasoning and Task Generalization via Visual Action Outcome Reasoning Alignment</a></h3>
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|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 3.6</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06519v1" target="_blank" rel="noopener">FreqDepthKV: Frequency-Guided Depth Sharing for Robust KV Cache Compression in Long-Context LLM Inference</a></h3>
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||
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|
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<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06514v1" target="_blank" rel="noopener">FootsiesGym: A Fighting Game Benchmark for Two-Player Zero-Sum Imperfect-Information Games</a></h3>
|
||
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<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 2.9</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06507v1" target="_blank" rel="noopener">DynaKRAG: A Unified Framework for Learnable Evidence Control in Multi-Hop Retrieval-Augmented Generation</a></h3>
|
||
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|
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||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 4.4</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06505v1" target="_blank" rel="noopener">Industry Classification of GitHub Repositories Using the North American Industry Classification System</a></h3>
|
||
|
||
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|
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<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 3.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06504v1" target="_blank" rel="noopener">RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models</a></h3>
|
||
|
||
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|
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|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 3.4</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06503v1" target="_blank" rel="noopener">Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade</a></h3>
|
||
|
||
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|
||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 5.1</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06497v1" target="_blank" rel="noopener">EntroPath: Maximum Entropy Path Ensemble Embedding for Manifold Learning</a></h3>
|
||
|
||
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|
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||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 2.2</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06495v1" target="_blank" rel="noopener">Pitwall: Faithful Natural-Language Race-Strategy Briefings from a Calibrated Real-Time Monte Carlo Engine</a></h3>
|
||
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|
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||
<div class="meta"><span class="src">arxiv</span>
|
||
<span class="time">15:44</span>
|
||
<span class="sig">sig 3.5</span>
|
||
<span class="score">🔥 0.00</span></div>
|
||
<h3><a href="https://arxiv.org/abs/2607.06489v1" target="_blank" rel="noopener">Multi-Agent Deep Reinforcement Learning for Multi Objective Battery Management in Dairy Farms</a></h3>
|
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|
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|
||
<span class="sig">sig 4.5</span>
|
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<span class="score">🔥 0.00</span></div>
|
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|
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<span class="sig">sig 4.3</span>
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<span class="score">🔥 0.00</span></div>
|
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<h3><a href="https://the-decoder.com/google-deepmind-adds-background-execution-and-mcp-support-to-gemini-api-managed-agents/" target="_blank" rel="noopener">Google Deepmind adds background execution and MCP support to Gemini API managed agents</a></h3>
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<span class="sig">sig 4.3</span>
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<h3><a href="https://the-decoder.com/chinese-ai-startup-minimax-plans-to-open-source-a-2-7-trillion-parameter-model-later-this-year/" target="_blank" rel="noopener">Chinese AI startup MiniMax plans to open-source a 2.7 trillion parameter model later this year</a></h3>
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<span class="sig">sig 4.3</span>
|
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<span class="score">🔥 0.00</span></div>
|
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<h3><a href="https://techcrunch.com/2026/07/08/former-openai-exec-kevin-weil-is-now-on-the-board-of-stoke-space/" target="_blank" rel="noopener">Former OpenAI exec Kevin Weil is now on the board of Stoke Space</a></h3>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://the-decoder.com/muse-image-is-technically-impressive-but-metas-use-of-instagram-photos-raises-questions/" target="_blank" rel="noopener">Muse Image is technically impressive, but Meta's use of Instagram photos raises questions</a></h3>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://techcrunch.com/2026/07/08/hot-french-startup-zml-releases-free-product-to-speed-inference-across-lots-of-ai-chips/" target="_blank" rel="noopener">Hot French startup ZML releases free product to speed inference across lots of AI chips</a></h3>
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<h3><a href="https://the-decoder.com/openais-gpt-5-6-launches-thursday-after-a-delay-forced-by-the-u-s-government/" target="_blank" rel="noopener">OpenAI's GPT-5.6 launches Thursday after a delay forced by the U.S. government</a></h3>
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<h3><a href="https://techcrunch.com/2026/07/08/sambanova-draws-1b-at-11b-valuation-in-series-f-first-close/" target="_blank" rel="noopener">AI chip maker SambaNova raises $1B at $11B valuation, 5 months after last mega round</a></h3>
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|
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|
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://techcrunch.com/2026/07/07/meta-rolls-out-muse-a-new-ai-image-generator/" target="_blank" rel="noopener">Meta just launched a new AI generator, Muse Image, and users are already pushing back over use of their photos</a></h3>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://techcrunch.com/2026/07/07/microsoft-joins-ai-cost-cutting-trend-by-relying-more-on-its-own-models/" target="_blank" rel="noopener">Microsoft joins AI cost-cutting trend by relying more on its own models</a></h3>
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<h3><a href="https://techcrunch.com/2026/07/07/why-the-rise-of-open-source-ai-isnt-hurting-anthropic-yet/" target="_blank" rel="noopener">Why the rise of open source AI isn’t hurting Anthropic … yet</a></h3>
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<span class="score">🔥 0.00</span></div>
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<span class="score">🔥 0.00</span></div>
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<span class="sig">sig 3.3</span>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://techcrunch.com/2026/07/07/the-coding-agent-wars-are-spilling-into-the-rest-of-the-office-claude-cowork/" target="_blank" rel="noopener">Claude Cowork expands to mobile and web</a></h3>
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<span class="time">15:46</span>
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<span class="sig">sig 3.3</span>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://www.artificialintelligence-news.com/news/insilico-medicine-advances-ai-drug-for-ipf-to-phase-iii-trials/" target="_blank" rel="noopener">Insilico Medicine advances AI drug for IPF to Phase III trials</a></h3>
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<span class="time">15:46</span>
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<span class="sig">sig 3.2</span>
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<span class="score">🔥 0.00</span></div>
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<h3><a href="https://the-decoder.com/claudes-hidden-inner-monologue-is-now-readable-thanks-to-anthropics-new-jacobian-lens/" target="_blank" rel="noopener">Claude's hidden inner monologue is now readable thanks to Anthropic's new Jacobian Lens</a></h3>
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