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Do Larger Language Models Imply Better Reasoning? A Pretraining Scaling Law for Reasoning On a synthetic multihop reasoning environment designed to closely replicate the structure and distribution of real-world large-scale knowledge graphs, the authors observe that

📜🚨 Check out our latest work on "Self-Resource Allocation in Multi-Agent LLM Systems" where we explore how LLMs can be used to optimize task allocation in multi-agent systems 🤖 🧵(1/3)

New work led by Sophia Xiao Pu and Michael Saxon: ThoughtTerminator, to avoid LLMs from overthinking. And a new benchmark DUMB500, a benchmark of extremely simple questions.

[1] MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in Videos Come meet Xuehai He William Wang and me tomorrow morning (4/24) at 9:30-11:30am. x.com/XuehaiH/status…

Congratulations Xinyi on your new job at Princeton and SUNY Buffalo! Very proud of your achievements. She’s the 7th and newly minted professor from our lab. Talk to her at #iclr2025.

If you're at ICLR you may want to grab the opportunity to talk with my incredible co-authors Kexun Zhang and Yuxi XIE on everything Search + Agent related at our SWE-Search poster, on Thursday at 3:00pm, Hall 3 + Hall 2B #156. 😁 iclr.cc/virtual/2025/p…

Happening Now: Xinyi Wang on distributional memorization vs distributional generalization for tracing LLM capabilities back to training data at #ICLR2025 Xinyi Wang poster 244.

Excited to share our paper at #ICML2025! We've developed MELON🍉, a robust defense method against indirect prompt injection attacks on LLM agents that achieves near 0 ASR! Hope you enjoy🍉! Grateful to my incredible collaborators! William Wang Wenbo Guo Jindong Wang Xianjun Yang

Amazing Alfonso! We are lucky to have you as a part of the team!

DeepPath hits 1,000 citations! 🎉 Back in 2017, we introduced DeepPath, one of the earliest reinforcement learning frameworks for multi-hop reasoning over discrete knowledge graph structures. The idea was simple but ambitious: use an RL agent to learn relational paths in

Lab celebration lunch after Xinyi Wang's defense!

Approximately 44% of U.S. unicorn startups (valued at $1 billion or more) were founded by immigrants. As of 2024, 46% of Fortune 500 companies were founded by immigrants or their children, collectively generating over $8.6 trillion in revenue and employing millions. Immigrants

Thrilled Gödel Agent got noticed by Sakana AI & excited for their expansion! Accepted at ACL 2025, our 1st fully self-referential agent can read & modify its entire logic (even that logic). Done via recursion. Paper: arxiv.org/abs/2410.04444

International students, and Chinese students in particular, are essential to the AI research ecosystem in the US. You can't say you support AI research in this country and then threaten to revoke Chinese students' visas.

Revoking visas to Chinese PhD students is economically shortsighted and inhumane. Most Chinese PhD students stay in the U.S. after graduation (first image, stats from 2022). They're staying and building technology in the U.S., not taking it to China. Immigrant students create

New paper 🚨📜🚀 Introducing “Agents of Change: Self-Evolving LLM Agents for Strategic Planning”! In this work, we show how LLM-powered agents can rewrite their own prompts & code to climb the learning curve in the board game Settlers of Catan 🎲 🧵👇

ChipAgents is hiring multiple positions: chipagents.ai/careers We’re a fast-moving, venture-backed startup building AI agents that revolutionize chip design and verification—and we’re growing our on-site team in beautiful Santa Barbara. Come help us push the boundaries of

Trying out the new, free Starlink Internet access on a United regional flight. It’s shockingly fast. 🤯

ChipAgents' Head of Engineering Mehir Arora explains the differences between LLMs and AI Agents to the EDA community. A must watch! 🚀

Congratulations to all! Super excited to graduate 7 PhD students this year: they are joining UW, Princeton, Google x 2, xAI, Amazon, and Meta. They are the future of AI!