collaborators

18 papers

cs.CL2026

SWE-Bench ProMax: Benchmarking Agents on Large-Scale Multilingual Code Refactoring

Yuling Shi, Jinghan Xu, Kelin Fu +12

As AI coding agents take on increasingly complex, long-horizon software engineering tasks, existing benchmarks are rapidly saturating and their evaluation quality has come under se…

cs.SE2026

Inside the Skill Market: From Software Engineering Activities to Reusable Agent Skills

Jialun Cao, Xinru Yan, Songqiang Chen +3

Software engineering (abbrev. SE) has continuously evolved through increasingly powerful forms of reuse, from source code and libraries to components and services. Recent advances…

cs.SE2026

Code Benchmarks Should Prioritize Rigor, Reliability, and Reproducibility

Jialun Cao, Yuk-Kit Chan, Zixuan Ling +12

Code-related benchmarks play a critical role in evaluating large language models (LLMs), yet their quality fundamentally shapes how the community interprets model capabilities. In…

cs.SE2026

iCoRe: An Iterative Correlation-Aware Retriever for Bug Reproduction Test Generation

Junyi Wang, Jialun Cao, Zhongxin Liu

Automatically generating bug reproduction tests (BRT) from issue descriptions is crucial for software maintenance. LLM-based approaches have shown great potential for this task. Th…

cs.LG2026

Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training

Yuanyi Wang, Yifan Yang, Su Lu +9

Continual post-training aims to extend large language models (LLMs) with new knowledge, skills, and behaviors, yet it remains unclear when sequential updates enable capability tran…

cs.SE2026

Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation

Qiming Zhu, Jialun Cao, Xuanang Chen +6

Current research on large language models (LLMs) with retrieval-augmented code generation (RACG) has largely focused on single-language settings, leaving their cross-lingual effect…