4 papers
DSEffi-Bench: Demystifying Large Language Models' Capability in Efficient Data Science Code Generation
Zhihao Gong, Junzhe Yu, Dong Huang +3
Current data science (DS) code generation benchmarks equate correctness with quality, overlooking execution time differences that span orders of magnitude between correct solutions…
FuzzAgent: Multi-Agent System for Evolutionary Library Fuzzing
Yunlong Lyu, Peng Chen, Fengyi Wu +3
Library fuzzing is essential for hardening the software supply chain, but adopting it at scale remains expensive. Practitioners still spend substantial effort on environment setup,…
Breaking the Loop: Detecting and Mitigating Denial-of-Service Vulnerabilities in Large Language Models
Junzhe Yu, Yi Liu, Huijia Sun +2
Large Language Models (LLMs) have significantly advanced text understanding and generation, becoming integral to applications across education, software development, healthcare, en…
Efficient Detection of Toxic Prompts in Large Language Models
Yi Liu, Junzhe Yu, Huijia Sun +4
Large language models (LLMs) like ChatGPT and Gemini have significantly advanced natural language processing, enabling various applications such as chatbots and automated content g…