3 papers
cs.CL2026
Memex(RL): Scaling Long-Horizon LLM Agents via Indexed Experience Memory
Zhenting Wang, Huancheng Chen, Jiayun Wang +1
Large language model (LLM) agents are fundamentally bottlenecked by finite context windows on long-horizon tasks. As trajectories grow, retaining tool outputs and intermediate reas…
cs.LG2025
EPO: Entropy-regularized Policy Optimization for LLM Agents Reinforcement Learning
Wujiang Xu, Wentian Zhao, Zhenting Wang +6
Training LLM agents in multi-turn environments with sparse rewards, where completing a single task requires 30+ turns of interaction within an episode, presents a fundamental chall…
cs.LG2025
DUMP: Automated Distribution-Level Curriculum Learning for RL-based LLM Post-training
Zhenting Wang, Guofeng Cui, Yu-Jhe Li +2
Recent advances in reinforcement learning (RL)-based post-training have led to notable improvements in large language models (LLMs), particularly in enhancing their reasoning capab…