3 papers
cs.SE2026
Is Your Benchmark Still Useful? Dynamic Benchmarking for Code Language Models
Batu Guan, Xiao Wu, Yuanyuan Yuan +1
In this paper, we tackle a critical challenge in model evaluation: how to keep code benchmarks useful when models might have already seen them during training. We introduce a novel…
cs.SE2026
Understanding Agent-Based Patching of Compiler Missed Optimizations
Batu Guan, Zirui Wang, Shaohua Li
Compiler missed optimizations refer to cases in which compilers failed to optimize certain code. It takes many compiler developers' efforts to implement or patch such missed optimi…
cs.CL2024
CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code
Batu Guan, Yao Wan, Zhangqian Bi +4
Large Language Models (LLMs) have achieved remarkable progress in code generation. It now becomes crucial to identify whether the code is AI-generated and to determine the specific…