1 citations · 1 across the 11 of their papers we have counts for
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SpecPath: Testing Coding Agents Across Contract-Equivalent Specification Histories
Yangfan Wu, Haozhe Wang, Huanyu Yang +2
Modern coding agents increasingly appear capable of following complex software requirements, yet their success leaves a critical ambiguity: do they resolve the active specification…
StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs
Jialin Yang, Dongfu Jiang, Lipeng He +17
As Large Language Models (LLMs) become integral to software development workflows, their ability to generate structured outputs has become critically important. We introduce Struct…
Understanding by Reconstruction: Reversing the Software Development Process for LLM Pretraining
Zhiyuan Zeng, Yichi Zhang, Yong Shan +11
While Large Language Models (LLMs) have achieved remarkable success in code generation, they often struggle with the deep, long-horizon reasoning required for complex software engi…
SWE-QA-Pro: A Representative Benchmark and Scalable Training Recipe for Repository-Level Code Understanding
Songcheng Cai, Zhiheng Lyu, Yuansheng Ni +13
Agentic repository-level code understanding is essential for automating complex software engineering tasks, yet the field lacks reliable benchmarks. Existing evaluations often over…
ACECODER: Acing Coder RL via Automated Test-Case Synthesis
Huaye Zeng, Dongfu Jiang, Haozhe Wang +3
Most progress in recent coder models has been driven by supervised fine-tuning (SFT), while the potential of reinforcement learning (RL) remains largely unexplored, primarily due t…