Author

Zhen-Hong Zhou

h-index 6 View on Semantic Scholar

We have 4 of 24 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Preprint Sep 2026

Feature-Aware Token Attack for Compression-Triggered Stealthy Failures in Large Vision-Language Models

This work proposes Feature-Aware Token Attack (FATA), which couples attention suppression with cosine-based feature preservation on a fixed set of salient clean-image tokens and has the lowest measured detection rate among four attacks across three evaluated detectors at a 5% false-positive rate.

Shilinlu Yan, Bo-Wen Chen, Yuechen Zhang et al. · 0 citations

#machine learning Preprint Sep 2026

RESCUE: Repairing Language Model Errors to Sparse Circuits via Reinforcement Learning

This work introduces RESCUE (Reasoning-Error Sparse-Circuit Uncovering and Editing), a framework that localizes error-associated circuits and surgically repairs them for performance enhancement, and introduces a pruning technique and precisely fine-tunes error circuits to correct task failures, thereby translating erro...

Chuan-Pu-Zou-Sheng-Li-Guo-Jing-Zhong-Gu-Yue-Shu-Ca Liu, Miao Yu, Yi-Kai Cai et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Still There, No Longer Seen: Exposing Compression-Induced Risk in Large Vision-Language Models

Visual token compression reduces the inference cost of Large Vision-Language Models (LVLMs). However, aggregate robustness measures do not reveal whether a particular adversarial failure is induced by compression or inherited from the underlying model. We define a compression-specific failure (CSF) as an adversarial in...

Qian-Kun Li, Yuechen Zhang, Bo-Wen Chen et al. · 1 citation

#artificial intelligence Preprint Sep 2026

In-Place Instruction Following in Diffusion Language Models

GRAFT, an IPP-oriented post-training framework combining constraint-aware SFT and preference optimization is proposed, an IPP-oriented post-training framework combining constraint-aware SFT and preference optimization that raises the average IIF score and preserves general generation ability.

Zheng Nie, Zhe-Rui Li, Jia-Ming Zhang et al. · 0 citations