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Tree-structured debates between LLM agents elicit critical, comparative reasoning. Tree-of-Debate transforms scientific papers into personas that debate their novelties to identify unique and similar ideas. Paper: arxiv.org/abs/2502.14767 w/ Ishika Agarwal Tal August Data Mining Group@UIUC!

🚀 Introducing 𝗦𝗲𝗮𝗿𝗰𝗵-𝗥𝟭 – the first 𝗿𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗗𝗲𝗲𝗽𝘀𝗲𝗲𝗸-𝗥𝟭 (𝘇𝗲𝗿𝗼) for training reasoning and search-augmented LLM agents with reinforcement learning! This is a step towards training an 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗢𝗽𝗲𝗻𝗔𝗜 “𝗗𝗲𝗲𝗽

Panopticon, but instead of prison cells, it's a stack of Overleaf tabs. You can’t watch them all at once, but at any moment, you *could* be watching any of them. And they know it.

#ICLR2025 was a blast! Grateful for the opportunity to present our work on formally certifying LLMs. For more details of our work, please check out our project page: certifyllm.com

🚀Our ICML 2025 paper introduces "Premise-Augmented Reasoning Chains" - a structured approach to induce explicit dependencies in reasoning chains. By revealing the dependencies within chains, we significantly improve how LLM reasoning can be verified. 🧵[1/n]

Would models know more about Indian food in Hindi and Turkey’s history in Turkish? Does the language of a question affect an LLM’s answer? ✨Yes!✨ Ishika Agarwal and I are excited to announce our newest preprint in which we explore “Language Specific Knowledge (LSK)”.

Behind every successful woman there’s a man. His name is Claude.