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Yining Zheng

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#machine learning Preprint Sep 2026

MARCO: Multi-Round Agentic Reinforcement for Conditional Molecular Optimization

Molecular optimization is inherently iterative: a candidate is proposed, evaluated against several objectives, and revised while preserving a relationship to the source molecule. Most instruction-following models instead emit one edited molecule, forcing validity, property improvement, and similarity control into a sin...

Shi-Cheng Fang, Yu-Xin Wang, Zhuo Yang et al. · 0 citations
#machine learning Preprint Sep 2026

ORPG: Reconciling Multiple Reward Objectives through Objective-wise Policy Gradients

Objective-wise Reconciled Policy Gradient (ORPG), which constructs a separate clipped policy objective for each reward and reconciles the resulting gradients into one policy update, achieves the highest average full-budget accuracy and three-budget hypervolume among the compared methods.

Shi-Cheng Fang, Yi-Wen Zhao, Wen-Bo Tian et al. · 0 citations
Preprint Aug 2026

SWE-bench Science: Can Coding Agents Resolve Engineering Tasks in Science?

A paired ablation that removes explicit scientific guidance while preserving the repository and executable engineering context shows that scientific knowledge is not uniformly beneficial: well-grounded information can constrain repair and improve average performance and token efficiency, whereas poorly aligned guidance...

Zhi-Peng Xu, Jia-Hao Lu, Yi-Ning Zheng et al. · 4 citations
#natural language process... Preprint Aug 2026

What Makes Agent Memory Useful for Reliable Unanswerable Question Handling?

It is found that memory can improve UAQ performance in some settings, but such gains are selective rather than universal and remain fragile under dataset shift, suggesting that reliable UAQ memory depends less on storing larger amounts of experience and more on preserving transferable behavioral guidance.

Chuanyuan Tan, Junpu Yu, Yuxia Wang et al. · 0 citations

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