10.1k citations · 22.1k across the 78 of their papers we have counts for
4 papers · 1 filter
Can foundation models actively gather information in interactive environments to test hypotheses?
Danny P. Sawyer, Nan Rosemary Ke, Hubert Soyer +9
Foundation models excel at single-turn reasoning but struggle with multi-turn exploration in dynamic environments, a requirement for many real-world challenges. We evaluated these…
Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning
Yuxi Xie, Anirudh Goyal, Wenyue Zheng +4
We introduce an approach aimed at enhancing the reasoning capabilities of Large Language Models (LLMs) through an iterative preference learning process inspired by the successful s…
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
David Raposo, Sam Ritter, Blake Richards +3
Transformer-based language models spread FLOPs uniformly across input sequences. In this work we demonstrate that transformers can instead learn to dynamically allocate FLOPs (or c…
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei +1132
In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over…