most citedEnhancing Large Vision Language Models with Self-Training on Image Comprehension

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

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…

cs.SE2024

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

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.LG2024

Dataset Distillation for Offline Reinforcement Learning

Jonathan Light, Yuanzhe Liu, Ziniu Hu

Offline reinforcement learning often requires a quality dataset that we can train a policy on. However, in many situations, it is not possible to get such a dataset, nor is it easy…

cs.CL2024

Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller

Min Cai, Yuchen Zhang, Shichang Zhang +5

We propose SelfControl, an inference-time model control method utilizing gradients to control the behavior of large language models (LLMs) without explicit human annotations. Given…

cs.CV2024★ 1 cited

Enhancing Large Vision Language Models with Self-Training on Image Comprehension

Yihe Deng, Pan Lu, Fan Yin +6

Large vision language models (LVLMs) integrate large language models (LLMs) with pre-trained vision encoders, thereby activating the perception capability of the model to understan…

cs.AI2023

AvalonBench: Evaluating LLMs Playing the Game of Avalon

Jonathan Light, Min Cai, Sheng Shen +1

In this paper, we explore the potential of Large Language Models (LLMs) Agents in playing the strategic social deduction game, Resistance Avalon. Players in Avalon are challenged n…