Berkeley AI Research @berkeley_ai
We're graduate students, postdocs, faculty and scientists at the cutting edge of artificial intelligence research. bair.berkeley.edu Berkeley, CA Joined July 2017-
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I enjoyed this conversation with Hugo talking about the challenges of LLM-powered data processing. The next decade will witness a paradigm shift in many social sciences, helping people unlock value from unstructured documents at scale. I am very lucky to be able to be a part of…
I enjoyed this conversation with Hugo talking about the challenges of LLM-powered data processing. The next decade will witness a paradigm shift in many social sciences, helping people unlock value from unstructured documents at scale. I am very lucky to be able to be a part of…
“Data will solve robotics and automation: True or false?”: A debate. Held @ieee_ras_icra #ICRA2025 and featuring BAIR faculty @Ken_Goldberg and BAIR alumnus @animesh_garg. science.org/doi/10.1126/sc…
New @SciRobotics editorial by BAIR Faculty @Ken_Goldberg: Good old-fashioned engineering can close the 100,000-year “data gap” in robotics science.org/doi/10.1126/sc…
Humanoid robots are coming, but don't hold your breath waiting for them: news.berkeley.edu/2025/08/27/are…
Nice video of Laura Lewis et al.s paper on social curiosity in chimps and children, from our lab. Paper is here.royalsocietypublishing.org/doi/full/10.10… nbcbayarea.com/video/news/nat…
🚨 New postdoc position in our lab @Berkeley_EECS! 🚨 (please retweet + share with relevant candidates) We seek applicants with experience in language modeling who are excited about high-impact applications in the health and social sciences! More info in thread 1/3
Language following is a tough problem for VLAs: while these models can follow complex language, in practice getting datasets that enable language following is hard. We developed a method to counterfactually and automatically label data to improve language following! 🧵👇
Inherent biases and imbalances in robot data can make training steerable VLA policies challenging. We introduce CAST, a method to augment datasets with counterfactuals to induce better language following cast-vla.github.io ← paper, code, data, and more available here! 🧵
HIL-SERL appears at Science Robotics today!It learns complex robotic skills with reinforcement learning directly in the real world in just 1-2 hours Website: hil-serl.github.io science.org/doi/10.1126/sc…
Can we break the memory wall for LLM inference via KV cache rematerialization? 🚨 Introducing XQuant, which leverages underutilized compute units to eliminate the memory bottleneck for LLM inference! • 10–12.5x memory savings vs. FP16 • Near-zero accuracy loss • Beats…
One-liner summaries are central to emergency care, but generating them is cognitively demanding/time-pressured. We evaluated LLMs for automated one-liner generation & compared them head-to-head w/ physician summaries. New work w/ @MelMolinaMD, led by @nbgolchini @nikita_mehandru!
One-liner summaries are central to emergency care, but generating them is cognitively demanding/time-pressured. We evaluated LLMs for automated one-liner generation & compared them head-to-head w/ physician summaries. New work w/ @MelMolinaMD, led by @nbgolchini @nikita_mehandru! https://t.co/bJPXohO4sp
Want to achieve extreme performance in motion tracking—and go beyond it? Our preprint tech report is now online, with open-source code available!
Traditional ML fairness audits don't work in the LLM era, eg medical LLMs may have eq treatment rec rates across groups (seemingly good!) but differ in empathetic vs dismissive phrasing (bad!). Also what do "groups" even mean now? New NEJM AI piece w @Emily_Alsentzer out today
So honored to receive the KDD Outstanding Dissertation Award for my dissertation "Computational Methods for Human Networks and High-Stakes Decisions"!! Huge thanks to my advisors @jure @jugander + committee members @erichorvitz @jurafsky! @StanfordAILab @Berkeley_EECS @UCJointCPH
A feature of BAIR faculty @istoica05 with quotes and mentions from fellow BAIR faculty @profjoeyg, @matei_zaharia, @jenniferchayes, Michael I Jordan; BAIR alumni and researchers @alighodsi, @ml_angelopoulos, @infwinston , Yang Zhou, @pcmoritz, @robertnishihara; and startups…
A feature of BAIR faculty @istoica05 with quotes and mentions from fellow BAIR faculty @profjoeyg, @matei_zaharia, @jenniferchayes, Michael I Jordan; BAIR alumni and researchers @alighodsi, @ml_angelopoulos, @infwinston , Yang Zhou, @pcmoritz, @robertnishihara; and startups…
Why This Billionaire Berkeley Professor Won’t Leave The Classroom via @Forbes forbes.com/sites/martinad…
1/N 🚀 Launching LEANN — the tiniest vector index on Earth! Fast, accurate, and 100% private RAG on your MacBook. 0% internet. 97% smaller. Semantic search on everything. Your personal Jarvis, ready to dive into your emails, chats, and more. 🔗 Code: github.com/yichuan-w/LEANN 📄…
As promised, we are starting to dive deep, beginning with @SkildAI Brain's general-purpose perceptive locomotion capability. Mesmerizing to see a full-size humanoid go over any obstacles effortlessly. All through a single end-to-end model: from pixels to action.
As promised, we are starting to dive deep, beginning with @SkildAI Brain's general-purpose perceptive locomotion capability. Mesmerizing to see a full-size humanoid go over any obstacles effortlessly. All through a single end-to-end model: from pixels to action.
📢NEW POSITION PAPER: Use Sparse Autoencoders to Discover Unknown Concepts, Not to Act on Known Concepts Despite recent results, SAEs aren't dead! They can still be useful to mech interp, and also much more broadly: across FAccT, computational social science, and ML4H. 🧵
Excited to talk about how scientific insights into deep networks can translate into practical applications. Thanks to the @Cohere_Labs ML Understanding group for the invite!
Excited to talk about how scientific insights into deep networks can translate into practical applications. Thanks to the @Cohere_Labs ML Understanding group for the invite!

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Eugene Vinitsky (@RLC... @EugeneVinitsky
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Jordan Stevenson 🇨... @iharc_jordan
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Bethany Perez @bethanyperez83
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Benjamin Israelson @israelsonbj
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Bruno Marafiga @Vinacomunista
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Oscar Navas @naviumco
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Shane @shanelarisey
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Soumith Chintala @soumithchintala
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Sergey Levine @svlevine
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NeurIPS Conference @NeurIPSConf
139K Followers 36 Following Vancouver, Dec 10-15, 24. https://t.co/ga8aOw6yUO Tweets to this account are not monitored. Please send feedback to [email protected].
Kyunghyun Cho @kchonyc
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Oriol Vinyals @OriolVinyalsML
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Animesh Garg @animesh_garg
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Dan Roy @roydanroy
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Thomas G. Dietterich @tdietterich
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Christopher Manning @chrmanning
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Jon Barron @jon_barron
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Angjoo Kanazawa @akanazawa
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Philipp Moritz @pcmoritz
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ACL 2025 @aclmeeting
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Institute for Foundat... @MLFoundations
1K Followers 2K Following NSF AI Institute with researchers from @UTAustin, @UW, @WichitaState, @MSFTResearch, @UCBerkeley, @UCLA, @sfiscience, @Stanford, @Caltech, @ASU
Skild AI @SkildAI
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Meena Jagadeesan @mjagadeesan25
760 Followers 188 Following Incoming Assistant Prof @Penn CS | Incoming Postdoc @StanfordAILab | Previously @Berkeley_ai @Harvard
Yuxi on the Wired @layer07_yuxi
3K Followers 71 Following [email protected]:~$ whoami tech enby (agi/asi pronouns) (math ⊗ physic ⊗ comput).ist
Alexander Wei @alexwei_
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Raj Movva @rajivmovva
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University of Califor... @UofCalifornia
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Eunice Yiu @eunice_yiu_
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Roei Herzig @roeiherzig
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Andrew Wagenmaker @ajwagenmaker
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Ezinne Nwankwo @ezinne_nwa
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Neerja Thakkar @neerjathakkar
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Amit Kohli @the_legitamit
123 Followers 39 Following PhD student at @Berkeley_EECS supervised by Laura Waller (@optrickster). Computational aberration correction. Statistical imaging. Undergrad at @stanford_ee.
Oier Mees @oier_mees
2K Followers 296 Following Robot Foundation Models. Postdoc at @berkeley_ai w/ Sergey Levine. PhD @UniFreiburg. Prev. intern @NVIDIAAI.
Carlo Sferrazza @carlo_sferrazza
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