3 citations · 7 across the 13 of their papers we have counts for
4 papers · 1 filter
Steer, Don't Solve: Training Small Critic Models for Large Code Agents
Shubham Gandhi, Yiqing Xie, Atharva Naik +2
Coding tasks are typically complicated and require multiple capabilities, ranging from high-level planning to low-level implementation. While coding agents are optimized for the jo…
Hybrid-Gym: Training Coding Agents to Generalize Across Tasks
Yiqing Xie, Emmy Liu, Gaokai Zhang +7
When assessing the quality of coding agents, predominant benchmarks focus on solving single issues on GitHub, such as SWE-Bench. In contrast, in real use, these agents solve more v…
CodeRAG-Bench: Can Retrieval Augment Code Generation?
Zora Zhiruo Wang, Akari Asai, Xinyan Velocity Yu +4
While language models (LMs) have proven remarkably adept at generating code, many programs are challenging for LMs to generate using their parametric knowledge alone. Providing ext…
CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks
Yiqing Xie, Alex Xie, Divyanshu Sheth +3
To adequately test modern code generation systems, evaluation benchmarks must execute and test the code generated by the system. However, these execution and testing requirements h…