4 papers
Beyond Vulnerabilities: A Survey of Adversarial Attacks as Both Threats and Defenses in Computer Vision Systems
Zhongliang Guo, Yifei Qian, Yanli Li +6
Adversarial attacks against computer vision systems have emerged as a critical research area that challenges the fundamental assumptions about neural network robustness and securit…
DUP: Detection-guided Unlearning for Backdoor Purification in Language Models
Man Hu, Yahui Ding, Yatao Yang +3
As backdoor attacks become more stealthy and robust, they reveal critical weaknesses in current defense strategies: detection methods often rely on coarse-grained feature statistic…
Exploring Cognitive and Aesthetic Causality for Multimodal Aspect-Based Sentiment Analysis
Luwei Xiao, Rui Mao, Shuai Zhao +4
Multimodal aspect-based sentiment classification (MASC) is an emerging task due to an increase in user-generated multimodal content on social platforms, aimed at predicting sentime…
Defending Against Weight-Poisoning Backdoor Attacks for Parameter-Efficient Fine-Tuning
Shuai Zhao, Leilei Gan, Luu Anh Tuan +4
Recently, various parameter-efficient fine-tuning (PEFT) strategies for application to language models have been proposed and successfully implemented. However, this raises the que…