7 papers
Noise-Aware and Dynamically Adaptive Federated Defense Framework for SAR Image Target Recognition
Yuchao Hou, Zixuan Zhang, Jie Wang +9
As a critical application of computational intelligence in remote sensing, deep learning-based synthetic aperture radar (SAR) image target recognition facilitates intelligent perce…
TouchFormer: A Robust Transformer-based Framework for Multimodal Material Perception
Kailin Lyu, Long Xiao, Jianing Zeng +6
Traditional vision-based material perception methods often experience substantial performance degradation under visually impaired conditions, thereby motivating the shift toward no…
MMT-ARD: Multimodal Multi-Teacher Adversarial Distillation for Robust Vision-Language Models
Yuqi Li, Junhao Dong, Chuanguang Yang +5
Vision-Language Models (VLMs) are increasingly deployed in safety-critical applications, making their adversarial robustness a crucial concern. While adversarial knowledge distilla…
C3-OWD: A Curriculum Cross-modal Contrastive Learning Framework for Open-World Detection
Siheng Wang, Zhengdao Li, Yanshu Li +12
Object detection has advanced significantly in the closed-set setting, but real-world deployment remains limited by two challenges: poor generalization to unseen categories and ins…
CoopQ: Cooperative Game Inspired Layerwise Mixed Precision Quantization for LLMs
Junchen Zhao, Ali Derakhshan, Jayden Kana Hyman +3
Large Language Models (LLMs) promise impressive capabilities, yet their multi-billion-parameter scale makes on-device or low-resource deployment prohibitive. Mixed-precision quanti…
Mitigating Group-Level Fairness Disparities in Federated Visual Language Models
Chaomeng Chen, Zitong Yu, Junhao Dong +4
Visual language models (VLMs) have shown remarkable capabilities in multimodal tasks but face challenges in maintaining fairness across demographic groups, particularly when deploy…