Author

Jian-Min Wu

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Preprint Sep 2026

VidHarness: Evolving Agent Harnesses for Cost-Efficient Long Video Understanding

Vision-language models (VLMs) can answer questions about hour-long videos, but processing every frame is prohibitively expensive, even though the evidence for a question usually spans only a few seconds. Video agents, i.e., harness programs wrapped around a frozen VLM, address this by observing the video selectively, y...

Susan Liang, Jian-Min Wu, Da-Xiang Dong · 0 citations

#artificial intelligence Preprint Oct 2026

RLDISCOVER: LLM-driven co-evolution of reinforcement learning algorithms

LLM-guided program evolution has enabled discoveries in mathematics and computational optimization, raising the prospect of reinforcement learning (RL) algorithms that self-evolve to improve how agents learn. However, realizing this prospect faces two obstacles. Joint search over coupled algorithmic components is diffi...

Hao-Ran Li, Z. Ge, Xiao-Ming Yuan et al. · 0 citations

Preprint Aug 2026

Janus: An Algorithm-Evaluator Co-Evolution Framework for LLM-Driven Discovery under Expensive Evaluation Budgets

Janus is introduced, a framework that uses LLMs to co-evolve target programs and executable proxy evaluators to address label scarcity and extend evaluator-guided LLM discovery from tasks with cheap, scalable feedback to scientific domains where trustworthy evaluation is scarce and expensive.

Xi-Meng Liu, Qianlong Wang, Ying-Ming Mao et al. · 2 citations