2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
PromptPath: Prompt-Adaptive Computational Pathways for In-Context Learning
Hangrui Zhang, Feifei Shao, Yawei Luo +6
In-context learning (ICL) has attracted increasing attention for enabling models to perform new tasks using only a few ``input--output'' prompt examples. However, existing approach…
Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models
Xiao Liu, Jiaxiang Liu, Boci Peng +6
Vision Language Models adapt well to downstream tasks but are highly vulnerable to adversarial perturbations that disrupt cross-modal semantic alignment. Existing defenses are larg…
MindAdapter: Few-Shot Parameter-Efficient Residual Calibration of Cross-Subject Brain-to-Visual Decoding Models
Jiaxiang Liu, Jiawei Du, Xupeng Chen +4
Cross-subject brain-to-visual decoding remains a core challenge in brain-computer interfaces due to severe inter-individual variability that induces systematic subject-specific fun…
Med-R2: An Adversarial Benchmark for Evidence-Grounded Reasoning in Medical VLMs
Wen Ma, Fucheng Niu, Zhiting Fan +3
Vision-language models have demonstrated impressive capabilities in general medical visual question answering, yet due to limited interpretability, it remains unclear whether their…