3 papers
cs.AI2025
Strategist: Self-improvement of LLM Decision Making via Bi-Level Tree Search
Jonathan Light, Min Cai, Weiqin Chen +5
Traditional reinforcement learning and planning typically requires vast amounts of data and training to develop effective policies. In contrast, large language models (LLMs) exhibi…
cs.SE2025
Scattered Forest Search: Smarter Code Space Exploration with LLMs
Jonathan Light, Yue Wu, Yiyou Sun +6
We frame code generation as a black-box optimization problem within the code space and demonstrate how optimization-inspired techniques can enhance inference scaling. Based on this…
cs.AI2024
PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making
Jonathan Light, Sixue Xing, Yuanzhe Liu +7
Effective extraction of the world knowledge in LLMs for complex decision-making tasks remains a challenge. We propose a framework PIANIST for decomposing the world model into seven…