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cs.AI2024
Enhancing Decision-Making for LLM Agents via Step-Level Q-Value Models
Yuanzhao Zhai, Tingkai Yang, Kele Xu +4
Agents significantly enhance the capabilities of standalone Large Language Models (LLMs) by perceiving environments, making decisions, and executing actions. However, LLM agents st…
cs.LG2024
Online Self-Preferring Language Models
Yuanzhao Zhai, Zhuo Zhang, Kele Xu +6
Aligning with human preference datasets has been critical to the success of large language models (LLMs). Reinforcement learning from human feedback (RLHF) employs a costly reward…
cs.LG2024
Optimistic Model Rollouts for Pessimistic Offline Policy Optimization
Yuanzhao Zhai, Yiying Li, Zijian Gao +5
Model-based offline reinforcement learning (RL) has made remarkable progress, offering a promising avenue for improving generalization with synthetic model rollouts. Existing works…