39 citations · 48 across the 17 of their papers we have counts for
5 papers · 1 filter
CKGFuzzer: LLM-Based Fuzz Driver Generation Enhanced By Code Knowledge Graph
Hanxiang Xu, Wei Ma, Ting Zhou +5
In recent years, the programming capabilities of large language models (LLMs) have garnered significant attention. Fuzz testing, a highly effective technique, plays a key role in e…
TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models
Xin Wang, Kai Chen, Jiaming Zhang +2
Large pre-trained Vision-Language Models (VLMs) such as CLIP have demonstrated excellent zero-shot generalizability across various downstream tasks. However, recent studies have sh…
ReToMe-VA: Recursive Token Merging for Video Diffusion-based Unrestricted Adversarial Attack
Ziyi Gao, Kai Chen, Zhipeng Wei +5
Recent diffusion-based unrestricted attacks generate imperceptible adversarial examples with high transferability compared to previous unrestricted attacks and restricted attacks.…
I Don't Know You, But I Can Catch You: Real-Time Defense against Diverse Adversarial Patches for Object Detectors
Zijin Lin, Yue Zhao, Kai Chen +1
Deep neural networks (DNNs) have revolutionized the field of computer vision like object detection with their unparalleled performance. However, existing research has shown that DN…
Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks
Chonghua Wang, Haodong Duan, Songyang Zhang +2
Recently, the large language model (LLM) community has shown increasing interest in enhancing LLMs' capability to handle extremely long documents. As various long-text techniques a…