2 citations · 6 across the 11 of their papers we have counts for
3 papers · 1 filter
From Prompts to Posteriors: Can LLM Agents Perform Bayesian Inference in Context?
Linus Filbry, Luckeciano C. Melo, Yarin Gal
Large language models (LLMs) are increasingly applied across the scientific discovery pipeline, from synthesizing literature to generating hypotheses to informing experimental desi…
Iterative Deployment Improves Planning Skills in LLMs
Augusto B. Corrêa, Yoav Gelberg, Luckeciano C. Melo +3
We show that iterative deployment of large language models (LLMs), each fine-tuned on data carefully curated by users from the previous models' deployment, can significantly change…
Memo: Training Memory-Efficient Embodied Agents with Reinforcement Learning
Gunshi Gupta, Karmesh Yadav, Zsolt Kira +2
To enable embodied agents to operate effectively over extended timeframes, it is crucial to develop models that form and access memories to stay contextualized in their environment…