Lisa Alazraki

lisaalaz.bsky.social

22 May 2025 15:43

Thrilled to share our new preprint on Reinforcement Learning for Reverse Engineering (RLRE) 🚀 We demonstrate that human preferences can be reverse engineered effectively by pipelining LLMs to optimise upstream preambles via reinforcement learning 🧵⬇️

Tom Hosking

tomhosking.bsky.social

27 March 2025 16:19

I'm really proud to have led the model merging work that went into @cohere.com Command A and R7B, all made possible by an amazing group of collaborators. Check out the report for loads of details on how we trained a GPT-4o level model that fits on 2xH100!

Lisa Alazraki

lisaalaz.bsky.social

13 February 2025 16:18

Do LLMs need rationales for learning from mistakes? 🤔 When LLMs learn from previous incorrect answers, they typically observe corrective feedback in the form of rationales explaining each mistake. In our new preprint, we find these rationales do not help, in fact they hurt performance! 🧵

Adina Williams

adinawilliams.bsky.social

11 December 2024 16:21

Our paper PRISM alignment won a best paper award at #neurips2024! All credits to @hannahrosekirk.bsky.social A.Whitefield, P.Röttger, A.M.Bean, K.Margatina, R.Mosquera-Gomez, J.Ciro, @maxbartolo.bsky.social H.He, B.Vidgen, S.Hale Catch Hannah tomorrow at neurips.cc/virtual/2024/poster/97804

Tim Rocktäschel

handle.invalid

05 December 2024 09:44

Excited to reveal Genie 2, our most capable foundation world model that, given a single prompt image, can generate an endless variety of action-controllable, playable 3D worlds. Fantastic cross-team effort by the Open-Endedness Team and many other teams at Google DeepMind! 🧞