6 papers
Pruning as a Cooperative Game: Surrogate-Assisted Layer Contribution Estimation for Large Language Models
Xuan Ding, Pengyu Tong, Ranjie Duan +3
While large language models (LLMs) demonstrate impressive performance across various tasks, their deployment in real-world scenarios is still constrained by high computational dema…
ONRW: Optimizing inversion noise for high-quality and robust watermark
Xuan Ding, Xiu Yan, Chuanlong Xie +1
Watermarking methods have always been effective means of protecting intellectual property, yet they face significant challenges. Although existing deep learning-based watermarking…
AgentsEval: Clinically Faithful Evaluation of Medical Imaging Reports via Multi-Agent Reasoning
Suzhong Fu, Jingqi Dong, Xuan Ding +4
Evaluating the clinical correctness and reasoning fidelity of automatically generated medical imaging reports remains a critical yet unresolved challenge. Existing evaluation metho…
VesSAM: Efficient Multi-Prompting for Segmenting Complex Vessel
Suzhong Fu, Rui Sun, Xuan Ding +8
Accurate vessel segmentation is critical for clinical applications such as disease diagnosis and surgical planning, yet remains challenging due to thin, branching structures and lo…
Sliding-Window Merging for Compacting Patch-Redundant Layers in LLMs
Xuan Ding, Rui Sun, Yunjian Zhang +7
Depth-wise pruning accelerates LLM inference in resource-constrained scenarios but suffers from performance degradation due to direct removal of entire Transformer layers. This pap…
DipSVD: Dual-importance Protected SVD for Efficient LLM Compression
Xuan Ding, Rui Sun, Yunjian Zhang +6
The ever-increasing computational demands and deployment costs of large language models (LLMs) have spurred numerous compressing methods. Compared to quantization and unstructured…