Papers by Samuel Osebe
AutoSUIT Bench - Automated Security UnIt Test Benchmark for LLM Coding (2026.findings-acl)
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Samuel Osebe, Fan Yang, Junyi Li, Yue Gu, Yongxin Wang, Satyapriya Krishna, Kai-Wei Chang, Aram Galstyan, Rahul Gupta, Weitong Ruan
| Challenge: | Large Language Models (LLMs) are evolving rapidly on code generation tasks. |
| Approach: | They propose to automate the vulnerability code benchmark creation with iterative auto validation. |
| Outcome: | The proposed benchmark covers 232 CWE categories across C/C++, Java, and Python languages. |