collaborators

5 papers

cs.AI2026

Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment

Haoyuan Wang, Xiaohao Liu, Jiajie Su +2

Multimodal large language models (MLLMs) need efficient mechanisms to update knowledge without degrading existing capabilities. While intrinsic multimodal knowledge editing achieve…

cs.CV2026

Rethinking Noise-Robust Training for Frozen Vision Foundation Models: A Cross-Dataset Benchmark with a Case Study of Small-Loss Failure

Zitong Li, Haoyu Wang

Frozen Vision Foundation Models (VFMs) with lightweight classification heads are increasingly used in medical imaging because they offer efficient and reproducible deployment. Yet…

cs.CV2026

HalluCXR: Benchmarking and Mitigating Hallucinations in Medical Vision-Language Models for Chest Radiograph Interpretation

Haoyu Wang, Zitong Li

Vision-language models (VLMs) are increasingly used for medical image interpretation, yet they frequently hallucinate, generating clinically plausible but factually incorrect findi…

cs.LG2026

GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets

Zhangyang Yao, Haiyan Zhao, Haoyu Wang +3

Mixed-precision quantization improves the budget--accuracy trade-off for large language models (LLMs) by allocating more bits to sensitive modules. However, automating this allocat…

cs.LG2026

MeGU: Machine-Guided Unlearning with Target Feature Disentanglement

Haoyu Wang, Zhuo Huang, Xiaolong Wang +3

The growing concern over training data privacy has elevated the "Right to be Forgotten" into a critical requirement, thereby raising the demand for effective Machine Unlearning. Ho…