4 papers
Robustness and Trade-offs for Code LLMs on Protected Code
Jin Wen, Yuejun Guo, Yujie Ma +2
Code large language models (LLMs) are increasingly used on software artifacts that may be intentionally obfuscated for intellectual-property protection, reverse-engineering resista…
Not All Errors Are Equal: Consequence-Aware Reasoning Compute Allocation
Jingbo Wen, Liang He, Haoyu Wang +4
Test-time compute has emerged as an effective paradigm for improving large language model capability at inference time. Existing allocation strategies primarily prioritize tasks ac…
Towards Demystifying and Repairing LLM-in-the-Loop Vulnerabilities
Yujie Ma, Jialin Rong, Chenxi Yang +5
Large Language Models (LLMs) have been actively integrated into modern software systems as critical components, introducing a new type of software vulnerability, LLM-in-the-Loop (L…
Evaluation and Improvement of Fault Detection for Large Language Models
Qiang Hu, Jin Wen, Maxime Cordy +4
Large language models (LLMs) have recently achieved significant success across various application domains, garnering substantial attention from different communities. Unfortunatel…