Meng Xu

SNIPTEST reveals that targeted fuzzing of code slices can significantly enhance the validation of static analysis warnings, achieving over 54% success in identifying true vulnerabilities.

Decoupling generation from selection leads to substantial gains in factual accuracy and relevance in summarization, even under strict budget constraints.

Spotting AI-generated harms requires more than just image analysis: this system links images to their source even when paired with harmful text, enabling accountability.