arXivDaily arXiv每日学术速递 周一至周五更新

AI 大模型

代码大模型 / AI 编程

代码生成、软件工程智能体、程序修复、测试生成和开发者工具。

共收录 12245 信号源:cs.SE, cs.CL, cs.AI, cs.LG, cs.PL

1. 仓库级理解 3963 篇

2502.05344 2025-02-11 cs.SE cs.AI 81%

RAG-Verus: Repository-Level Program Verification with LLMs using Retrieval Augmented Generation

Sicheng Zhong, Jiading Zhu, Yifang Tian, Xujie Si

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.AI

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2501.07857 2025-01-15 cs.SE cs.AI 81%

Hierarchical Repository-Level Code Summarization for Business Applications Using Local LLMs

Nilesh Dhulshette, Sapan Shah, Vinay Kulkarni

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.AI

Comments To appear at LLM4Code@ICSE 2025

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2411.08054 2024-11-14 cs.DL cs.AI cs.LG 81%

GREI Data Repository AI Taxonomy

John Chodacki, Mark Hanhel, Stefano Iacus, Ryan Scherle, Eric Olson, Nici Pfeiffer, Kristi Holmes, Mohammad Hosseini

专题命中 仓库级理解 :repository(title,abstract);分类 cs.AI、cs.LG

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2410.11291 2024-10-17 cs.CL cs.AI 81%

Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset Repository

S. Tamang, D. J. Bora

专题命中 仓库级理解 :repository(title,abstract);分类 cs.CL、cs.AI

Comments 6 pages, 1 table, 1 figure

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2303.13173 2024-09-12 cs.SE cs.AI 81%

Design Patterns for AI-based Systems: A Multivocal Literature Review and Pattern Repository

Lukas Heiland, Marius Hauser, Justus Bogner

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.AI

Comments Accepted for publication at the International Conference on AI Engineering (CAIN) 2023

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2409.06226 2024-09-11 cs.IR cs.CL cs.LG 81%

NLP-Powered Repository and Search Engine for Academic Papers: A Case Study on Cyber Risk Literature with CyLit

Linfeng Zhang, Changyue Hu, Zhiyu Quan

专题命中 仓库级理解 :repository(title,abstract);分类 cs.CL、cs.LG

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2403.06095 2024-08-15 cs.SE cs.AI 81%

RepoHyper: Search-Expand-Refine on Semantic Graphs for Repository-Level Code Completion

Huy N. Phan, Hoang N. Phan, Tien N. Nguyen, Nghi D. Q. Bui

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.AI

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2201.07381 2024-03-12 cs.AI cs.SE 81%

Unveiling Project-Specific Bias in Neural Code Models

Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Junzhe Jiang, Yang Liu

专题命中 仓库级理解 :code model(title,abstract);分类 cs.SE、cs.AI

Comments Accepted by LREC-COLING 2024

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2402.14323 2024-02-26 cs.SE cs.AI 81%

REPOFUSE: Repository-Level Code Completion with Fused Dual Context

Ming Liang, Xiaoheng Xie, Gehao Zhang, Xunjin Zheng, Peng Di, wei jiang, Hongwei Chen, Chengpeng Wang, Gang Fan

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.AI

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2402.07323 2024-02-13 cs.SE cs.LG 81%

Lessons Learned from Mining the Hugging Face Repository

Joel Castaño, Silverio Martínez-Fernández, Xavier Franch

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.LG

Comments Accepted at the 2024 ACM/IEEE 1st International Workshop on Methodological Issues with Empirical Studies in Software Engineering (WSESE)

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2208.09495 2023-11-07 cs.SE cs.AI 81%

Topical: Learning Repository Embeddings from Source Code using Attention

Agathe Lherondelle, Varun Babbar, Yash Satsangi, Fran Silavong, Shaltiel Eloul, Sean Moran

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.AI

Comments Pre-print, under review

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2301.09715 2023-01-26 cs.CL cs.IR cs.LG 81%

PrimeQA: The Prime Repository for State-of-the-Art Multilingual Question Answering Research and Development

Avirup Sil, Jaydeep Sen, Bhavani Iyer, Martin Franz, Kshitij Fadnis, Mihaela Bornea, Sara Rosenthal, Scott McCarley, Rong Zhang, Vishwajeet Kumar, Yulong Li, Md Arafat Sultan, Riyaz Bhat, Radu Florian, Salim Roukos

专题命中 仓库级理解 :repository(title,abstract);分类 cs.CL、cs.LG

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2107.05112 2021-07-13 cs.SE cs.AI 81%

Repo2Vec: A Comprehensive Embedding Approach for Determining Repository Similarity

Md Omar Faruk Rokon, Pei Yan, Risul Islam, Michalis Faloutsos

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.AI

Comments 10 pages, 8 figures, 5 tables. In press: ICSME'21

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2104.12001 2021-04-27 cs.SE cs.LG 81%

Predicting the Number of Reported Bugs in a Software Repository

Hadi Jahanshahi, Mucahit Cevik, Ayşe Başar

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.LG

Journal ref Canadian AI 2020: Advances in Artificial Intelligence pp 309-320

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2003.13619 2020-03-31 cs.LG cs.SE 81%

Repository for Reusing Artifacts of Artificial Neural Networks

Javad Ghofrani, Ehsan Kozegar, Mohammad Divband Soorati, Arezoo Bozorgmehr, Hongfei Chen, Maximilian Naake

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE、cs.LG

Comments tool paper https://github.com/ghofrani85/RAN2 7 pages

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2108.04800 2022-01-19 cs.LG cs.CV 80%

Meta-repository of screening mammography classifiers

Benjamin Stadnick, Jan Witowski, Vishwaesh Rajiv, Jakub Chłędowski, Farah E. Shamout, Kyunghyun Cho, Krzysztof J. Geras

专题命中 仓库级理解 :repository(title,abstract);分类 cs.LG

Comments 17 pages, 2 figures. Meta-repository available at https://www.github.com/nyukat/mammography_metarepository ; v3 adds results on the CSAW-CC dataset

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2608.14128 2026-08-17 cs.SE 新提交 79%

DepWareTrans: Dependency-Aware Incremental Repository Migration across Co-executable Languages

DepWareTrans:跨可共执行语言的依赖感知增量仓库迁移

Sivajeet Chand, Alexander Pretschner, Steve Haupt, Derui Zhu, Sushant Kumar Pandey

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 提出依赖感知增量迁移框架,构建依赖图分组文件进行批量翻译,在 STAR 仓库等上实现 100% 编译和测试成功率,提升仓库级代码翻译的可扩展性与可靠性。

Comments Accepted for publication in the Industry Showcase Track of the 41st IEEE/ACM International Conference on Automated Software Engineering, which will take place in Munich, Germany during October 12-16, 2026

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2608.03558 2026-08-05 cs.SE 新提交 79%

EffiHolmes: Differential Profiling-Guided Repository Level Time Inefficiency Fix Localization

EffiHolmes:基于差分分析的仓库级时间低效修复定位

Haowen Yang, Yun Peng, Zishuo Ding

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 EffiHolmes是基于LLM的仓库级时间低效修复定位框架,通过差分分析等技术提升定位精度,在RepoEffi-Bench上优于多种基线方法,且跨模型规模稳健。

Comments Accepted at the 41st IEEE/ACM International Conference on Automated Software Engineering (ASE 2026). 13 pages, 3 figures, and 4 tables

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2607.28775 2026-08-03 cs.SE 新提交 79%

Repository-Aware Metamorphic Relation Generation for Augmented Reality Applications using Large Language Models

基于大型语言模型的增强现实应用的仓库感知变形关系生成

Dibyendu Brinto Bose, Jiawei Qin, Chris Brown

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 本文提出一种结合仓库级上下文与推理编排的流水线,利用大型语言模型生成优化的变形关系,在142个移动AR仓库数据集上验证了该方法可构建可靠的领域相关测试预言,能有效检测代码变异。

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2607.25996 2026-07-29 cs.SE 新提交 79%

RepoReasoner: Evaluating Repository-Level Code Reasoning Ability of Long-Context Language Models

RepoReasoner:评估长上下文语言模型的仓库级代码推理能力

Yanlin Wang, Suiquan Wang, Yanli Wang, Bowen Zhang, Daya Guo, Jiachi Chen, Zibin Zheng

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 研究针对现有代码推理基准测试局限,引入RepoReasoner评估仓库级代码推理,通过多阶段管道构建基准,评估输出预测和调用链预测能力,发现当前LLMs在仓库级推理存在局限,为未来相关研究提供方向。

Comments Published in FSE'2026

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2607.13439 2026-07-16 cs.CR cs.SE 新提交 79%

DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection

DREA:用于仓库级漏洞检测的解耦推理与探索代理

Mingyang Sun, Guozhu Meng

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 研究针对大语言模型用于仓库级漏洞检测时的不足,提出DREA框架,通过规划与探索代理解耦,实现目标导向上下文获取。构建RepoPairBench评估,提升配对正确性,降低成本,还发现安全推理质量是当前大语言模型的瓶颈。

Comments Accepted for presentation at Internetware 2026. 12 pages, 4 figures, and 5 tables

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2605.16701 2026-07-15 cs.SE 版本更新 79%

What's Inside a GitHub Repository? An Empirical Study on the Contents of 10K Projects

GitHub仓库中有什么?对10000个项目内容的实证研究

Andre Hora, João Eduardo Montandon, Diego Elias Costa

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 本文通过分析10000个GitHub仓库的文件和目录,揭示了过去十年仓库内容的变化,包括README.md标准化、GitHub Actions兴起、配置格式演变及生成式AI相关内容的增长。

Comments Paper accepted to ICSME 2026

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2607.01764 2026-07-03 cs.AI 新提交 79%

Mastermind: Strategy-grounded Learning for Repository-Scale Vulnerability Reproduction

Mastermind: 基于策略学习的仓库级漏洞复现

Mingzhe Du, Luu Anh Tuan, Tianyi Wu, Renyang Liu, Zhijiang Guo, Dong Huang, See-Kiong Ng

机构 * National University of Singapore(新加坡国立大学) Nanyang Technological University(南洋理工大学) The Hong Kong University of Science and Technology (Guangzhou)(香港科技大学(广州))

专题命中 仓库级理解 :repository(title,abstract);分类 cs.AI

AI总结 提出Mastermind双循环框架,通过策略学习(SFT+GRPO)提升LLM代理在仓库级漏洞复现中的表现,在260个训练任务和200个测试任务上达到84.5%通过率,并成功迁移至不同执行器。

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2607.01213 2026-07-02 cs.SE 新提交 79%

RepoRescue: An Empirical Study of LLM Agents on Whole-Repository Compatibility Rescue

RepoRescue: LLM智能体在全仓库兼容性修复上的实证研究

Zhihao Lin, Mingyi Zhou, Zhensu Sun, Yizhuo Yang, Renyu Yang, David Lo, Li Li

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 研究LLM智能体能否自动修复因环境演化而失效的旧仓库,提出RepoRescue基准,包含315个仓库,评估多种智能体系统,发现跨文件协调是主要难点,且系统间互补性显著。

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2607.00911 2026-07-02 cs.SE 新提交 79%

From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintained

从注册表到仓库:AI代理技能如何编写、适配和维护

Haoyu Gao, Jai Lal Lulla, Hong Yi Lin, Sebastian Baltes, Christoph Treude, Mansooreh Zahedi

专题命中 仓库级理解 :repository(title);coding agent(abstract);分类 cs.SE

AI总结 本研究首次对AI代理技能作为工程制品进行实证分析,通过挖掘公共注册表和GitHub仓库中的技能,发现技能重用多为一次性复制,定制化主要适配本地环境,而行为契约几乎不变。

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2606.31206 2026-07-01 cs.SE 新提交 79%

FeatX: Editing Software by Editing Features for Repository-Level Code Evolution

FeatX: 通过编辑特征来编辑软件以实现仓库级代码演化

Xutian Li, Yifeng Zhu, Xianlin Zhao, Yanzhen Zou, Lu Zhang, Bing Xie

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 提出特征导向工具FeatX,通过提取层次化史诗-特征结构并调用三阶段演化代理,将特征编辑转化为代码补丁,显著降低认知负荷并提升修改定位F1达42.6%。

Comments 4 pages, Accepted to the Tools and Datasets Track of ASE 2026

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2606.28279 2026-06-29 cs.AR cs.AI 新提交 79%

Agentic Hardware Design as Repository-Level Code Evolution

代理硬件设计作为仓库级代码演化

Cunxi Yu, Chenhui Deng, Nathaniel Pinckney, Brucek Khailany

机构 * NVIDIA Research(NVIDIA研究)

专题命中 仓库级理解 :repository(title,abstract);分类 cs.AI

AI总结 提出HORIZON自演化代理框架,将硬件设计视为仓库级代码演化,通过Markdown编译项目包和免手代理循环实现全自动基准测试,在多个基准上达到100%完成率。

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2604.02852 2026-06-03 cs.SE 79%

Dependency-Guided Repository-Level C-to-Rust Translation with Reinforcement Alignment

依赖引导的仓库级C到Rust翻译与强化对齐

Jia Feng, Wenjie Gan, Cuiyun Gao, Chaozheng Wang, Feng Luo, Xin Xia, Ge Li, Kui Liu

专题命中 仓库级理解 :repository(title,abstract);分类 cs.SE

AI总结 提出DepTrans框架,通过强化对齐语法训练和依赖引导迭代精炼,实现仓库级C到Rust的高效翻译,编译成功率和计算准确性分别提升22.8和17.3个百分点。

Comments Accepted by FSE 2026 Industry

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2603.16572 2026-06-02 cs.CR cs.AI 79%

Context Matters: Repository-Aware Security Analysis of the Agent Skill Ecosystem

上下文很重要:基于仓库感知的代理技能生态系统安全分析

Florian Holzbauer, David Schmidt, Gabriel Gegenhuber, Sebastian Schrittwieser, Johanna Ullrich

机构 * Interdisciplinary Transformation University (IT:U)(交叉学科转化大学) University of Vienna(维也纳大学) CDL AsTra Faculty of Computer Science(计算机科学学院CDL AsTra系)

专题命中 仓库级理解 :repository(title,abstract);分类 cs.AI

AI总结 通过仓库上下文感知分析,发现现有扫描器高估了恶意技能比例(从46.8%降至0.52%),并识别出废弃仓库劫持等新攻击向量。

Comments AgentSkills '26 Workshop: ACM Conference on AI and Agentic Systems (CAIS), Best Paper Award

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2605.06125 2026-05-08 cs.SE 79%

Breaking, Stale, or Missing? Benchmarking Coding Agents on Project-Level Test Evolution

打破、过时或缺失?基于项目级测试演变的基准测试

Ye Shang, Quanjun Zhang, Haichuan Hu, Chunrong Fang, Liang Xiao, Zhenyu Chen

专题命中 仓库级理解 :coding agent(title);repository(abstract);分类 cs.SE

AI总结 本文提出TEBenchmark,首个项目级测试演变基准,评估系统自主识别需修改的测试、确定新测试需求并生成测试补丁的能力,揭示测试演变任务的性能上限。

Comments 15 pages, 5 figures

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