activity
20222026
most citedPandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization

29 citations · 49 across the 18 of their papers we have counts for

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Showing cs.SEShow all

7 papers · 1 filter

cs.SE2026

AttnCompress: Dynamic Attention-Guided Trajectory Compression for Software Engineering Agents

Zhengran Zeng, Yixin Li, Rui Xie +2

The transition from human-centric assistance to Autonomous Software Engineering (ASE) agents has enabled the resolution of complex real-world SE tasks. However, the trial-and-error…

cs.SE2025

Benchmarking and Studying the LLM-based Agent System in End-to-End Software Development

Zhengran Zeng, Yixin Li, Rui Xie +2

The development of LLM-based autonomous agents for end-to-end software development represents a significant paradigm shift in software engineering. However, the scientific evaluati…

cs.SE2025

SWR-Bench: Assessing LLM Performance in Real-World Code Review Comment Generation

Zhengran Zeng, Ruikai Shi, Keke Han +7

Automated Code Review (ACR) is crucial for software quality, yet existing benchmarks often fail to reflect real-world complexities, hindering the evaluation of modern Large Languag…

cs.SE2025★ 1 cited

Seed&Steer: Guiding Large Language Models with Compilable Prefix and Branch Signals for Unit Test Generation

Shuaiyu Zhou, Zhengran Zeng, Xiaoling Zhou +3

Unit tests play a vital role in the software development lifecycle. Recent advances in Large Language Model (LLM)-based approaches have significantly improved automated test genera…

cs.SE2024

CoderUJB: An Executable and Unified Java Benchmark for Practical Programming Scenarios

Zhengran Zeng, Yidong Wang, Rui Xie +2

In the evolving landscape of large language models (LLMs) tailored for software engineering, the need for benchmarks that accurately reflect real-world development scenarios is par…

cs.SE2024★ 2 cited

CodeShell Technical Report

Rui Xie, Zhengran Zeng, Zhuohao Yu +3

Code large language models mark a pivotal breakthrough in artificial intelligence. They are specifically crafted to understand and generate programming languages, significantly boo…

cs.SE2022★ 16 cited

Low-Resources Project-Specific Code Summarization

Rui Xie, Tianxiang Hu, Wei Ye +1

Code summarization generates brief natural language descriptions of source code pieces, which can assist developers in understanding code and reduce documentation workload. Recent…