Berkeley AI Research (@berkeley_ai) - Twitter Profili

Berkeley AI Research retweetledi

Zhe Ye@0xlf_·27 Nis

1/ 🧵Introducing: VeriSpecGen 🚀 Formal verification is a principled way to guarantee code correctness, but writing high-quality specifications remains expensive and expertise-intensive. What if LLMs could reliably synthesize intent-aligned formal specs directly from natural language? Introducing VeriSpecGen, a framework that improves both inference and training time formal specification synthesis performance in Lean! 🛠️✨ 📈 SOTA Results: VeriSepcGen achieves 86.6% on the VERINA SpecGen task using Claude Opus 4.5. The framework improves over baselines by up to 31.8pt across different model families and scales, proving robust regardless of base model characteristics. 📄 Paper: arxiv.org/pdf/2604.10392 🔗 Website: spec.verina.io

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Berkeley AI Research retweetledi

Roei Herzig@roeiherzig·1d

We recently held BAIR’s annual robotics workshop at @berkeley_ai, and among many fantastic talks, @trevordarrell and I gave a short one on my research journey over the past three years. Excited to share what we’ve learned about using structural priors and inductive biases to build more capable Physical AI models. This is just the beginning. 🤖✨ youtube.com/watch?v=YdvUQu…

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Ken Goldberg@Ken_Goldberg·4d

"The Humanoid Condition", a timely 24 min video, just came out from @Bloomberg. (My students and I appear around minute 7:00 and 23:00 to express some concerns about the timeline...) youtube.com/watch?v=UQZooa…

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Bloomberg@business

On this episode of Bloomberg Primer, we explore the gap between the futuristic hype and reality of humanoid robots, and how quickly it will shrink bloomberg.com/news/articles/…

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Joey Gonzalez@profjoeyg·5d

Should nations be negotiating with AI instead of people? Probably? What would happen? We setup AI and humans in a battle for world domination playing the game Risk with all the negotiation and side channel discussion that make games of Risk end in tears. I was pleasantly surprised by the results and what they might mean for the future of humanity. More seriously, I am really excited to understand how AI performs in competitive settings and how we can find welfare-maximizing correlated equilibrium by introducing AI diplomats ... future work.

Abby O'Neill@abby_k_oneill

Would you trust an AI agent to negotiate on your country's behalf at the G20? Real coordination is long-horizon, asymmetric, and non-binding; current multi-agent evaluations miss this. We build Cooperate to Compete (C2C): a testbed for LM agents coordinating with rivals. 🤝🔪🎭

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Berkeley AI Research retweetledi

Abby O'Neill@abby_k_oneill·5d

Would you trust an AI agent to negotiate on your country's behalf at the G20? Real coordination is long-horizon, asymmetric, and non-binding; current multi-agent evaluations miss this. We build Cooperate to Compete (C2C): a testbed for LM agents coordinating with rivals. 🤝🔪🎭

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Berkeley AI Research@berkeley_ai·5d

Congratulations to BAIR faculty @jlistgarten and @yun_s_song who have been elected to the International Society for Computational Biology (@iscb) 2026 class of Fellows! iscb.org/about-iscb/soc…

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Berkeley AI Research@berkeley_ai·5d

Congratulations to BAIR faculty @doristsao who has been elected to the American Academy of Arts and Sciences! amacad.org/news/new-membe…

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Kevin Zakka@kevin_zakka·5d

Heterogeneous simulation (different mesh per world) is now fully supported in mjlab. If you were hesitant about using mjlab for manipulation, now is a great time to switch over 🙂 mujocolab.github.io/mjlab/main/sou…

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Kevin Zakka@kevin_zakka·5d

I trained a grasping policy on objects of various shapes and sizes using the new mjlab feature and this really cool pivot grasp strategy emerges for large flat objects that are larger than the gripper aperture. So cool and beautiful to see!

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Berkeley AI Research retweetledi

Ion Stoica@istoica05·5d

We wanted to make long-horizon video generation accessible beyond massive compute clusters. With Quant VideoGen, you can now deploy HYWorldPlay locally on an RTX 5090. By exploiting spatiotemporal redundancy, we’ve slashed memory usage by 7× with almost no overhead. Congratulations to the team!

Haocheng Xi@HaochengXiUCB

🎥 Video generation is hitting the memory wall. As videos get longer, the KV cache quietly explodes — and long-horizon consistency starts to break. We built Quant VideoGen: a training-free KV cache compression method for auto-regressive video diffusion. Instead of storing every KV in high precision, QVG exploits video’s spatiotemporal redundancy with semantic-aware smoothing + progressive residual quantization. 🚀 Up to 7× KV memory reduction ⚡ <4% overhead ✅ Strong long-video quality 🕹️ Deploy HYWorldPlay on your own RTX 5090 locally KV compression is becoming a core scaling primitive — not just for LLMs, but for video generation too. Paper: arxiv.org/abs/2602.02958 Code: github.com/svg-project/Qu… (1/5)

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Haocheng Xi@HaochengXiUCB·5d

🎥 Video generation is hitting the memory wall. As videos get longer, the KV cache quietly explodes — and long-horizon consistency starts to break. We built Quant VideoGen: a training-free KV cache compression method for auto-regressive video diffusion. Instead of storing every KV in high precision, QVG exploits video’s spatiotemporal redundancy with semantic-aware smoothing + progressive residual quantization. 🚀 Up to 7× KV memory reduction ⚡ <4% overhead ✅ Strong long-video quality 🕹️ Deploy HYWorldPlay on your own RTX 5090 locally KV compression is becoming a core scaling primitive — not just for LLMs, but for video generation too. Paper: arxiv.org/abs/2602.02958 Code: github.com/svg-project/Qu… (1/5)

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Berkeley AI Research retweetledi

Negar Arabzadeh@NegarEmpr·6d

1/ "Can QPP Choose the Right Query Variant?" has been accepted at #SIGIR2026!🇦🇺 You can easily over-generate multiple query variants at low cost, but running RAG for all of them is expensive! Can we pick the winner query before paying the generation cost? arxiv.org/abs/2604.22661

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Kevin Zakka@kevin_zakka·26 Nis

Gave my PhD dissertation talk on Friday! It's been an incredible journey made possible by the best advisor who believed in me and gave me the freedom and support to explore. Thank you @pabbeel! And thank you to everyone who came to support and share this milestone with me 🙏

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Berkeley AI Research retweetledi

Marwa Abdulhai@marwaabdulhai·26 Nis

I am in Rio for #ICLR 2026! I am excited to be presenting 3 posters at the following workshops: ⚖️ Hierarchical Agenda Reasoning for Strategic Multi-Turn Dialogue Agents 📍 04/26, 11:15 AM–12 PM or 4:10–5 PM | DATA-FM, Room 203 A+B 📍 04/27, 11:35 AM–12:20 PM & 2:30–3:10 PM | SPOT Workshop ✏️ How LLMs Distort Our Written Language 📍 04/26, 3–3:50 PM | AIWILD Workshop, Room 204 A/B 🤖 Evaluating and Reducing Deceptive Dialogue from Language Models with Multi-Turn RL 📍 04/27, 10–11 AM | Trustworthy AI Workshop, Room 204 A+B If you're interested in dialogue agents, multi-turn RL, AI deception, and/or preserving human agency in AI-interactions, I'd love to chat. Feel free to reach out!

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Sergey Levine@svlevine·27 Nis

Tomorrow in the Workshop on World Models at ICLR in Rio (10:30 am) I’ll talk about a… different take on what might make for a good world model. Come find out, 10:30 in Room 202A at ICLR sites.google.com/view/iclr-2026…

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Sewon Min@sewon__min·26 Nis

I will give two talks at ICLR workshops!! 🇧🇷 Sunday 9:40-10:10: "LLMs for Distributed Data Use" @ Workshop on Data Problems in Foundation Models (Room 203 A/B) Monday 15:30–16:05 : "Are Mixture-of-Experts Modular? Why It Matters and How to Fix It" @ ICBINB Workshop (Room 201 C) Both happened to be related to MoEs, but tackle two completely different questions → some say hi!

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Sergey Levine@svlevine·25 Nis

I'll give a talk about lifelong learning tmrw (Sun), 9:30 am (Brazil time) in the lifelong agents workshop, about how we can get robot foundation models to improve with RL: lifelongagent.github.io Then at 11:30 am, I'll talk about how generative models can drive self-improvement here: recursive-workshop.github.io

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Seohong Park@seohong_park·24 Nis

What if we represent a state as a "list" of similarities to all other states? In our recent ICLR paper, we studied this "dual" representation. Come visit our poster at #4608 10:30a-1p on Fri (morning, 2nd day)! Paper: arxiv.org/abs/2510.06714 Blog post: seohong.me/blog/dual-repr…

Seohong Park@seohong_park

Introducing *dual representations*! tl;dr: We represent a state by the "set of similarities" to all other states. This dual perspective has lots of nice properties and practical benefits in RL. Blog post: seohong.me/blog/dual-repr… Paper: arxiv.org/abs/2510.06714 ↓

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Berkeley AI Research retweetledi

Lakshya A Agrawal@LakshyAAAgrawal·23 Nis

Thrilled to present GEPA as an Oral Talk and Poster at ICLR 2026 this Friday in Rio! 🇧🇷 Apr 24 Oral Session 3A (Agents), 10:30 AM BRT, Amphitheater Poster Session 4, 3:15 PM, Pavilion 3 x.com/LakshyAAAgrawa… Let's recap what's happened since we released GEPA last year 🧵

Lakshya A Agrawal@LakshyAAAgrawal

How does prompt optimization compare to RL algos like GRPO? GRPO needs 1000s of rollouts, but humans can learn from a few trials—by reflecting on what worked & what didn't. Meet GEPA: a reflective prompt optimizer that can outperform GRPO by up to 20% with 35x fewer rollouts!🧵

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Yajat Yadav@YajatYadav314·23 Nis

Excited to be in Rio this week to present RETAIN (w/ @zhiyuan_zhou_ , @ajwagenmaker, @KarlPertsch, and @svlevine) at #ICLR2026! 🇧🇷 Saturday 10:30 AM – 1:00 PM at P3-#1208. Project Page: retain.yajatyadav.com x.com/zhiyuan_zhou_/….

Paul Zhou@zhiyuan_zhou_

Do you ever find finetuning VLA overfits to the target task, to the point where generalist ability is lost and even minor deviations beyond the SFT data break the policy? We found an extremely simple solution: directly merge the base and finetuned policy in weight space 🤯 👇🧵

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