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cs.LG2025
Natural Language Reinforcement Learning
Xidong Feng, Bo Liu, Yan Song +7
Artificial intelligence progresses towards the "Era of Experience," where agents are expected to learn from continuous, grounded interaction. We argue that traditional Reinforcemen…
cs.LG2024
Entropy-Regularized Token-Level Policy Optimization for Language Agent Reinforcement
Muning Wen, Junwei Liao, Cheng Deng +3
Large Language Models (LLMs) have shown promise as intelligent agents in interactive decision-making tasks. Traditional approaches often depend on meticulously designed prompts, hi…
cs.LG2024
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
Siyuan Guo, Cheng Deng, Ying Wen +3
In this work, we investigate the potential of large language models (LLMs) based agents to automate data science tasks, with the goal of comprehending task requirements, then build…