5 papers
POSTCONDBENCH: Benchmarking Correctness and Completeness in Formal Postcondition Inference
Gehao Zhang, Juan Zhai
Formal postconditions precisely characterize program behavior and support debugging, testing, and verification, but writing them requires substantial expertise and effort. This has…
EDITOR: Effective and Interpretable Prompt Inversion for Text-to-Image Diffusion Models
Mingzhe Li, Kejing Xia, Gehao Zhang +5
Text-to-image generation models~(e.g., Stable Diffusion) have achieved significant advancements, enabling the creation of high-quality and realistic images based on textual descrip…
Breaking the Myth: Can Small Models Infer Postconditions Too?
Gehao Zhang, Zhenting Wang, Juan Zhai
Formal specifications are essential for ensuring software correctness, yet manually writing them is tedious and error-prone. Large Language Models (LLMs) have shown promise in gene…
Disappearing Ink: Obfuscation Breaks N-gram Code Watermarks in Theory and Practice
Gehao Zhang, Eugene Bagdasarian, Juan Zhai +1
Distinguishing AI-generated code from human-written code is becoming crucial for tasks such as authorship attribution, content tracking, and misuse detection. Based on this, N-gram…
FlexFL: Flexible and Effective Fault Localization with Open-Source Large Language Models
Chuyang Xu, Zhongxin Liu, Xiaoxue Ren +3
Due to the impressive code comprehension ability of Large Language Models (LLMs), a few studies have proposed to leverage LLMs to locate bugs, i.e., LLM-based FL, and demonstrated…