Auto-psych: a new system where AI agents do the whole science loop themselves -- come up with theori... - 惯性聚合

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Stanford AI Lab (@StanfordAILab) on X Stanford AI Lab (@StanfordAILab) on X Stanford AI Lab (@StanfordAILab) on X Stanford AI Lab (@StanfordAILab) on X Are you at ICML 2026 in Seoul? 🇰🇷 Check out the full list of papers from Stanford AI Lab — spannin... LLMs are better at predicting what other models will say than what’s actually true. When they’re wro... Congratulations to the team on the #ICML2026 workshop Oral! @jchudnov (co-lead), @JoshuaK92829 (co... Deduplication is standard practice but never perfect --this work measures what the residue costs in ... What if the way we collect human feedback in robotics is quietly losing information? If one traject... We love scaling inference compute, but it’s costly! Independently sampling parallel attempts might b... @milanganai @katielulula Read the post here! https://t.co/02bfnFx1Rm New SAIL Blog post: R&B-EnCoRe: What Should a Robot Actually Think About Before It Acts? @milan... By @kushin_m, @danielwurgaft, @LinasNasvytis, @michaelyli_, @noahdgoodman, and @mcxfrank! Congrats to @OpenJarvisAI! The future of LM inference runs beyond the datacenter: local by default, ... Most open agentic datasets target one benchmark. In compute-controlled comparisons, OpenThoughts-Age... By the wonderful team @jubayer_hamid, @ifdita_hasan, @michaelyli_, @oshaikh13, @yoonholeee, @DorsaS... At test time, we wrap LLMs in scaffolds that scale compute every which way -- longer chains, paralle... By an incredible team - @jubayer_hamid, @ifdita_hasan, @michaelyli_, @oshaikh13, @yoonholeee, @Dorsa... At test time, we wrap LLMs in scaffolds that scale compute every which way -- longer chains, paralle... @peterbhase @ChrisGPotts The post: https://t.co/Bn7ASHZ9Ap New SAIL Blog post: CoT Monitoring: Where Does a Hot Safety Problem Come From? @peterbhase and @C... Modern multimodal models aren't a single decode loop anymore; they're composite. M* is one runtime t... https://t.co/7hsAQFD68G Learn about how to orchestrate agents without a central orchestrator… in @VentureBeat’s recent artic... @jyangballin @vincentsunnchen https://t.co/P8vGVpGyc5 Hear from @jyangballin on ProgramBench and the lineage of AI coding benchmarks! In conversation with... Check out our latest blog post highlighting SAIL papers appearing at #CVPR2026. Congrats to everyone... Read the full piece at https://t.co/uloN888wwZ Are you at ICLR 2026 in Rio? Check out the full list of papers from Stanford AI Lab - covering LLM r... Check out our latest SAIL blog post on VAGEN, a reinforcement learning framework that trains VLM age... Can AI actively explore and build mental maps of space, or just answer when handed observations? C... Collaboration between Stanford SAIL and ETH shows RL with rich feedback significantly outperforms sc... Everyone can now discover new SOTA in science with a few hundred bucks! Test-Time Training + open m... Our latest research, TTT-E2E, marks a new era for LLM memory. Now, models can continue training du... SAIL is still accepting applications for the SAIL Postdoctoral Fellowships! This is an opportunity t... Millions of children face speech disorders—but few get timely care. Our new benchmark, SLP-Helm, tes... We do a lot of cutting edge research at the Stanford AI Lab, but really our main job is educating st... Check out our latest blog post about MiniVLA, a smaller open-source vision-language-action model! ht... Congratulations to @GuibasLeonidas and colleagues for winning the SIGGRAPH 2023 Test of Time award f...

Auto-psych: a new system where AI agents do the whole science loop themselves -- come up with theori...

Stanford AI · 2026-06-27 · via Stanford AI Lab(@StanfordAILab)

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