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cs.AI2025
MCTS-EP: Empowering Embodied Planning with Online Preference Optimization
Hang Xu, Zang Yu, Yehui Tang +3
This paper introduces MCTS-EP, an online learning framework that combines large language models (LLM) with Monte Carlo Tree Search (MCTS) for training embodied agents. MCTS-EP inte…
cs.AI2025
ComputerRL: Scaling End-to-End Online Reinforcement Learning for Computer Use Agents
Hanyu Lai, Xiao Liu, Yanxiao Zhao +7
We introduce ComputerRL, a framework for autonomous desktop intelligence that enables agents to operate complex digital workspaces skillfully. ComputerRL features the API-GUI parad…
cs.AI2025
FEVO: Financial Knowledge Expansion and Reasoning Evolution for Large Language Models
Bo Pang, Yalu Ouyang, Hangfei Xu +6
Advancements in reasoning for large language models (LLMs) have lead to significant performance improvements for LLMs in various fields such as mathematics and programming. However…