56 citations · 95 across the 47 of their papers we have counts for
8 papers · 1 filter
VRPTEST: Evaluating Visual Referring Prompting in Large Multimodal Models
Zongjie Li, Chaozheng Wang, Chaowei Liu +4
With recent advancements in Large Multimodal Models (LMMs) across various domains, a novel prompting method called visual referring prompting has emerged, showing significant poten…
InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language Models
Xunguang Wang, Zhenlan Ji, Pingchuan Ma +2
Large vision-language models (LVLMs) have demonstrated their incredible capability in image understanding and response generation. However, this rich visual interaction also makes…
Refining Decompiled C Code with Large Language Models
Wai Kin Wong, Huaijin Wang, Zongjie Li +5
A C decompiler converts an executable into source code. The recovered C source code, once re-compiled, is expected to produce an executable with the same functionality as the origi…
Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach
Zhenlan Ji, Pingchuan Ma, Zongjie Li +1
While code generation has been widely used in various software development scenarios, the quality of the generated code is not guaranteed. This has been a particular concern in the…
Split and Merge: Aligning Position Biases in LLM-based Evaluators
Zongjie Li, Chaozheng Wang, Pingchuan Ma +4
Large language models (LLMs) have shown promise as automated evaluators for assessing the quality of answers generated by AI systems. However, these LLM-based evaluators exhibit po…
REEF: A Framework for Collecting Real-World Vulnerabilities and Fixes
Chaozheng Wang, Zongjie Li, Yun Peng +5
Software plays a crucial role in our daily lives, and therefore the quality and security of software systems have become increasingly important. However, vulnerabilities in softwar…