Author

Weiyuan Li

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#artificial intelligence Preprint Sep 2026

Beyond Skill Evolution: Self-Evolving Context Management Policies for Long-Horizon Agent Harnesses

Harness evolution improves LLM agents by learning from execution trajectories, but existing experience- and skill-based methods are less effective on long-horizon tasks. As interactions grow, useful evidence can be buried by redundant or outdated context, making context management itself a key bottleneck. We introduce...

Wei-Yuan Li, Jing-Heng Xu, Ai-Li Chen et al. · 0 citations

#artificial intelligence Preprint Sep 2026

EvoRS: On-Policy Self-Evolution of Reward Systems for Open-Ended Reinforcement Learning

Open-ended reinforcement learning often relies on rubric-based rewards for tasks without directly verifiable answers. Yet the policy and reward system form a dynamic feedback loop: as the policy optimizes the current reward, an initially useful reward system may become unreliable due to reward hacking or reduced respon...

Weiyuan Li, Aili Chen, Xin-Tao Wang et al. · 0 citations

Preprint Aug 2026

Verify Smarter, Evolve Further: Efficient Harness Evolution through Behavior-Aware Verification

HarnessLens is introduced, a budget-aware framework for automated harness evolution that jointly explores the task space and user-configurable components, derives candidate modifications from execution trajectories, and selectively verifies each candidate on behavior-relevant tasks using an attributable-evidence gate.

Jingheng Xu, Yi-Kai Zhang, Aiden Chen et al. · 2 citations