الباحثون

Xiaojun Jia

المنشورات 4

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PyCache Trap: The Inspection-Execution Gap in Agent Skill Scanners

Jie Liao, Simeng Qin, Wenqi Ren وآخرون · 2026

Agent skills combine instructions with executable resources, giving third-party packages access to an agent's runtime. Existing skill scanners inspect documentation and visible source, but Python may execute a bundled bytecode cache with different behavior. We study this gap between inspection and execution through PyC …

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ASCENT: First-Order Optimal Fine-Tuning with Recalibration for Safety--Utility Co-Enhancement

Weiwei Qi, Chongyu Wang, Tianhang Zheng وآخرون · 2026

Supervised fine-tuning can substantially improve the downstream utility of large language models (LLMs) but may compromise their safety. Existing safety-preserving methods constrain downstream updates using safety-related parameters or subspaces, but mainly focus on safety preservation rather than joint safety and util …

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Linear Fitness Subspace in Protein Language Models Enables Sample-Efficient Directed Evolution

Siyuan Ma, Canran Xiao, Zikai Xiao وآخرون · 2026

Model-guided directed evolution seeks to identify high-fitness protein variants under limited oracle budgets. Protein language models (PLMs) provide rich representations for this task, but task-agnostic zero-shot scores can be misaligned with a target assay, while supervised search in high-dimensional embedding spaces …

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Visual-Invariance-Augmented Feature Optimal Alignment for Transferable Adversarial Attacks against Closed-Source MLLMs

Xiaojun Jia, Simeng Qin, Yiming Li وآخرون · 2026

Multimodal large language models (MLLMs) remain vulnerable to transferable adversarial examples, especially in black-box settings where only open-source surrogate models are accessible. Existing targeted transfer attacks mainly align adversarial and target samples using global image-level features, such as encoder [CLS …

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