The recent Claude 3.7 model from Anthropic lets you control the budget for thinking—how might this work? Check out L1, our fully open recipe for training reasoning models with controllable thinking budgets!

Cool to see our L1 (arxiv.org/abs/2503.04697) methodology used here! And a nice insight about using the controllable reasoning budget to enable more efficient use of inference hardware

AlphaVerus has been accepted at #ICML2025! alphaverus.github.io arxiv.org/abs/2412.06176 We've seen in math that good verification (e.g., Lean) unlocks surprising capabilities–why not for code too? AlphaVerus puts LLMs & Rust’s Verus verifier into a self-improving loop–lots

Confused about recent LLM RL results where models improve without any ground-truth signal? We were too. Until we looked at the reported numbers of the Pre-RL models and realized they were serverely underreported across papers. We compiled discrepancies in a blog below🧵👇

I will be at #ICML2025 this week. Reach out if you want to chat about llm reasoning, computer-use agents, code gen or actually anything! (DMs are open) I will also be presenting AlphaVerus (self-improving verified code gen) this Thursday! alphaverus.github.io

Can LLMs self-improve on code generation? Check out our work AlphaVerus where model generates provably correct code and self-improves without any weight updates! At #ICML2025 today: 📆: 11:00 AM - 1:30 PM 📷: Poster #East-2912 alphaverus.github.io w/ Bryan, Sean Welleck

Excited about CMU's new Institute for Computer-Aided Reasoning in Mathematics (ICARM), a new NSF Mathematical Sciences Research Institute. I'm honored to serve as an Assistant Director focusing on machine learning and mathematics.