代码大模型 / AI 编程

Learning Semantics-aware Search Operators for Genetic Programming

Piotr Wyrwiński, Krzysztof Krawiec

机构 * Poznan University of Technology（波兹南理工大学） 纠错

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.LG

Comments Submitted to GECCO 2025

Security Weaknesses of Copilot-Generated Code in GitHub Projects: An Empirical Study

Yujia Fu, Peng Liang, Amjed Tahir, Zengyang Li, Mojtaba Shahin, Jiaxin Yu, Jinfu Chen

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments Preprint accepted for publication in ACM Transactions on Software Engineering and Methodology (TOSEM), 2025

Resource-Efficient & Effective Code Summarization

Saima Afrin, Joseph Call, Khai-Nguyen Nguyen, Oscar Chaparro, Antonio Mastropaolo

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

LLMs for Generation of Architectural Components: An Exploratory Empirical Study in the Serverless World

Shrikara Arun, Meghana Tedla, Karthik Vaidhyanathan

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments Accepted to IEEE International Conference on Software Architecture (ICSA) 2025 Main Track (https://conf.researchr.org/home/icsa-2025)

AI-Powered, But Power-Hungry? Energy Efficiency of LLM-Generated Code

Lola Solovyeva, Sophie Weidmann, Fernando Castor

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source Data

Zifan Song, Yudong Wang, Wenwei Zhang, Kuikun Liu, Chengqi Lyu, Demin Song, Qipeng Guo, Hang Yan, Dahua Lin, Kai Chen, Cairong Zhao

机构 * Tongji University（同济大学） ； Shanghai AI Laboratory（上海人工智能实验室） ； Chinese University of Hong Kong（香港中文大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL

Comments Preprint with 20 pages and 20 figures. Source code and models at https://github.com/InternLM/AlchemistCoder

Autonomous Legacy Web Application Upgrades Using a Multi-Agent System

Valtteri Ala-Salmi, Zeeshan Rasheed, Abdul Malik Sami, Zheying Zhang, Kai-Kristian Kemell, Jussi Rasku, Shahbaz Siddeeq, Mika Saari, Pekka Abrahamsson

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments 13 pages, 2 figures

Programming by Examples Meets Historical Linguistics: A Large Language Model Based Approach to Sound Law Induction

Atharva Naik, Darsh Agrawal, Hong Sng, Clayton Marr, Kexun Zhang, Nathaniel R Robinson, Kalvin Chang, Rebecca Byrnes, Aravind Mysore, Carolyn Rose, David R Mortensen

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL

ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics

Atin Sakkeer Hussain

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI

Guiding ChatGPT to Fix Web UI Tests via Explanation-Consistency Checking

Zhuolin Xu, Qiushi Li, Shin Hwei Tan

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments Accepted at the International Conference on Software Testing, Verification and Validation (ICST) 2025

SOP-Agent: Empower General Purpose AI Agent with Domain-Specific SOPs

Anbang Ye, Qianran Ma, Jia Chen, Muqi Li, Tong Li, Fujiao Liu, Siqi Mai, Meichen Lu, Haitao Bao, Yang You

机构 * HPC-AI Tech（HPC-AI科技） ； Grab Holdings Inc（Grab控股公司） ； National University of Singapore（新加坡国立大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI

Comments 35 pages, 5 figures

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion

Yannis Flet-Berliac, Nathan Grinsztajn, Florian Strub, Bill Wu, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Mohammad Gheshlaghi Azar, Olivier Pietquin, Matthieu Geist

机构 * Cohere（科here公司） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.LG

Comments EMNLP 2024

Improving the Ability of Pre-trained Language Model by Imparting Large Language Model's Experience

Xin Yin, Chao Ni, Xiaodan Xu, Xinrui Li, Xiaohu Yang

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Executable Multi-Layered Software

Lukas Radosky, Ivan Polasek

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments 13 pages, 8 figures

BioAgents: Democratizing Bioinformatics Analysis with Multi-Agent Systems

Nikita Mehandru, Amanda K. Hall, Olesya Melnichenko, Yulia Dubinina, Daniel Tsirulnikov, David Bamman, Ahmed Alaa, Scott Saponas, Venkat S. Malladi

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI

The Future of AI: Exploring the Potential of Large Concept Models

Hussain Ahmad, Diksha Goel

机构 * The University of Adelaide（阿德莱德大学） ； CSIRO’s Data61（澳大利亚联邦科学与工业研究组织数据61部门） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL

Language Models for Code Optimization: Survey, Challenges and Future Directions

Jingzhi Gong, Vardan Voskanyan, Paul Brookes, Fan Wu, Wei Jie, Jie Xu, Rafail Giavrimis, Mike Basios, Leslie Kanthan, Zheng Wang

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments Submitted to the ACM Computing Surveys (CSUR)

Evaluating Large Language Models on Spatial Tasks: A Multi-Task Benchmarking Study

Liuchang Xu, Shuo Zhao, Qingming Lin, Luyao Chen, Qianqian Luo, Sensen Wu, Xinyue Ye, Hailin Feng, Zhenhong Du

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL

CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code

Batu Guan, Yao Wan, Zhangqian Bi, Zheng Wang, Hongyu Zhang, Pan Zhou, Lichao Sun

机构 * Huazhong University of Science and Technology（华中科技大学） ； University of Leeds（利兹大学） ； Chongqing University（重庆大学） ； Lehigh University（理海大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL

Comments 16 pages, 13 figures

The Current Challenges of Software Engineering in the Era of Large Language Models

Cuiyun Gao, Xing Hu, Shan Gao, Xin Xia, Zhi Jin

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments Accepted by ACM Transactions on Software Engineering and Methodology (TOSEM)

Emerging Security Challenges of Large Language Models

Herve Debar, Sven Dietrich, Pavel Laskov, Emil C. Lupu, Eirini Ntoutsi

机构 * Télécom SudParis（巴黎高等电信学院） ； City University of New York（纽约城市大学） ； Universität Liechtenstein（列支敦士登大学） ； Imperial College London（伦敦帝国学院） ； Universität der Bundeswehr München（慕尼黑联邦国防军大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI

Comments A version of this appeared in the larger Dagstuhl seminar 23431 report (https://doi.org/10.4230/DagRep.13.10.90)

Training LLMs for Generating IEC 61131-3 Structured Text with Online Feedback

Aaron Haag, Bertram Fuchs, Altay Kacan, Oliver Lohse

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments Accepted at LLM4Code Workshop @ ICSE 2025. This work has been submitted to the IEEE for possible publication

Breaking the Programming Language Barrier: Multilingual Prompting to Empower Non-Native English Learners

James Prather, Brent N. Reeves, Paul Denny, Juho Leinonen, Stephen MacNeil, Andrew Luxton-Reilly, João Orvalho, Amin Alipour, Ali Alfageeh, Thezyrie Amarouche, Bailey Kimmel, Jared Wright, Musa Blake, Gweneth Barbre

机构 * Abilene Christian University（阿比林基督大学） ； The University of Auckland（奥克兰大学） ； Aalto University（阿尔托大学） ； Temple University（天普大学） ； Polytechnic University of Coimbra（科英布拉理工大学） ； University of Houston（休斯顿大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.AI

Comments 10 pages, 3 tables. Accepted for publication at the 27th Australasian Computing Education Conference (ACE 2025)

Generating Move Smart Contracts based on Concepts

Rabimba Karanjai, Sam Blackshear, Lei Xu, Weidong Shi

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

I-SHEEP: Self-Alignment of LLM from Scratch through an Iterative Self-Enhancement Paradigm

Yiming Liang, Ge Zhang, Xingwei Qu, Tianyu Zheng, Jiawei Guo, Xinrun Du, Zhenzhu Yang, Jiaheng Liu, Chenghua Lin, Lei Ma, Wenhao Huang, Jiajun Zhang

机构 * School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院） ； Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所） ； BAAI（北京智源人工智能研究院） ； University of Waterloo（滑铁卢大学） ； M-A-P ； The University of Manchester（曼彻斯特大学） ； Peking University（北京大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL

ConceptSearch: Towards Efficient Program Search Using LLMs for Abstraction and Reasoning Corpus (ARC)

Kartik Singhal, Gautam Shroff

机构 * TCS Research（TCS研究院） 纠错

专题命中 代码生成 ：program synthesis(abstract)；分类 cs.LG

Comments Pre-print of paper accepted at AAAI 2025

Exploring Coding Spot: Understanding Parametric Contributions to LLM Coding Performance

Dongjun Kim, Minhyuk Kim, YongChan Chun, Chanjun Park, Heuiseok Lim

机构 * Korea University（高丽大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL

Towards an Understanding of Large Language Models in Software Engineering Tasks

Zibin Zheng, Kaiwen Ning, Qingyuan Zhong, Jiachi Chen, Wenqing Chen, Lianghong Guo, Weicheng Wang, Yanlin Wang

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

From Image to UML: First Results of Image Based UML Diagram Generation Using LLMs

Aaron Conrardy, Jordi Cabot

专题命中 代码生成 ：code generation(abstract)；分类 cs.SE

Comments Accepted in First Large Language Models for Model-Driven Engineering Workshop (LLM4MDE 2024)

Journal ref STAF Workshops 2024: 55-65

Evaluating and Aligning CodeLLMs on Human Preference

Jian Yang, Jiaxi Yang, Ke Jin, Yibo Miao, Lei Zhang, Liqun Yang, Zeyu Cui, Yichang Zhang, Binyuan Hui, Junyang Lin

机构 * Alibaba Group（阿里巴巴集团） ； Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院） ； University of Chinese Academy of Sciences（中国科学院大学） ； Shanghai Jiao Tong University（上海交通大学） 纠错

专题命中 代码生成 ：code generation(abstract)；分类 cs.CL