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Yuxuan Zhou

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#machine learning Preprint Oct 2026

When Non-Adversarial Noise Hurts Learning: Benchmarking Skill Self-Evolution in Agents

Large language model agents increasingly improve by distilling experience into reusable skills, but errors in that experience can persist in learned rules and affect later tasks. Existing evaluations largely examine clean learning or perturbations encountered after skills are frozen, leaving robustness during self-evol...

Tao Yu, Zhong-Tian Luo, Yu-Chen Long et al. · 0 citations
#artificial intelligence Preprint Sep 2026

OPIS: An Input-Grounded Benchmark for Multi-Object Memory in Video World Models

OPIS is introduced, an input-grounded benchmark that strictly anchors the assessment to a fixed set of object instances from the initial observation for evaluating multi-object memory in video world models and demonstrates that preserving the particular object instances in the input is considerably harder than generati...

Hao Wang, Tao Yu, Liu-Zhou Zhang et al. · 0 citations
Preprint Aug 2026

A Multimodal Automatic Redteaming Evaluation based on Atomic Jailbreak Strategy Decoupling and Combination

This work proposes a multimodal automated red team jailbreak method named Hierarchical Atomic Combination Attack (HACA), based on a six-dimensional strategy space, where a cross-modal joint planner is used to select and combine the different atomic jailbreak strategy for subsequent jailbreak command generation.

Shiji Zhao, Yuxuan Zhou, Chen Xiong et al. · 0 citations

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