代码大模型 / AI 编程

Relative Positioning Based Code Chunking Method For Rich Context Retrieval In Repository Level Code Completion Task With Code Language Model

Imranur Rahman, Md Rayhanur Rahman

机构 * North Carolina State University（北卡罗来纳州立大学） ； The University of Alabama（阿拉巴马大学） 纠错

专题命中 代码生成 ：repository(title,abstract)；分类 cs.SE、cs.AI、cs.LG

Comments Accepted to Context Collection Workshop co-located with ASE 2025

VisCoder: Fine-Tuning LLMs for Executable Python Visualization Code Generation

Yuansheng Ni, Ping Nie, Kai Zou, Xiang Yue, Wenhu Chen

机构 * University of Waterloo（滑铁卢大学） ； Carnegie Mellon University（卡内基梅隆大学） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

QHackBench: Benchmarking Large Language Models for Quantum Code Generation Using PennyLane Hackathon Challenges

Abdul Basit, Minghao Shao, Muhammad Haider Asif, Nouhaila Innan, Muhammad Kashif, Alberto Marchisio, Muhammad Shafique

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.PL

Comments To appear at the IEEE International Conference on Quantum Artificial Intelligence (QAI), Naples, Italy, November 2025

Correctness-Guaranteed Code Generation via Constrained Decoding

Lingxiao Li, Salar Rahili, Yiwei Zhao

机构 * Netflix 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.LG、cs.PL

Comments Published at COLM 2025

LyS at SemEval 2025 Task 8: Zero-Shot Code Generation for Tabular QA

Adrián Gude, Roi Santos-Ríos, Francisco Prado-Valiño, Ana Ezquerro, Jesús Vilares

机构 * Universidade da Coruña（科鲁纳大学） ； CITIC Departamento de Ciencias de la Computación y Tecnologías de la Información（CITIC计算机科学与信息技术部门） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments Accepted to SemEval 2025. Camera-ready version

More Than a Score: Probing the Impact of Prompt Specificity on LLM Code Generation

Yangtian Zi, Harshitha Menon, Arjun Guha

机构 * Northeastern University（东北大学） ； Lawrence Livermore National Laboratory（劳伦斯利弗莫尔国家实验室） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.CL、cs.LG、cs.PL

GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities

Diganta Misra, Nizar Islah, Victor May, Brice Rauby, Zihan Wang, Justine Gehring, Antonio Orvieto, Muawiz Chaudhary, Eilif B. Muller, Irina Rish, Samira Ebrahimi Kahou, Massimo Caccia

机构 * ELLIS Institute Tübingen（图宾根ELLIS研究所） ； MPI-IS Tübingen（图宾根MPI研究所） ； Mila Quebec AI Institute（魁北克AI研究所） ； Google（谷歌） ； Polytechnique Montréal（蒙特利尔高等理工学院） ； McGill University（麦吉尔大学） ； Moderne（Moderne公司） ； Gologic（Gologic公司） ； Tübingen AI Center（图宾根人工智能中心） ； Université de Montréal（蒙特利尔大学） ； ServiceNow Research（ServiceNow研究） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.PL

Comments Version 2 of the dataset from: arXiv:2411.05830

Multilingual Multimodal Software Developer for Code Generation

Linzheng Chai, Jian Yang, Shukai Liu, Wei Zhang, Liran Wang, Ke Jin, Tao Sun, Congnan Liu, Chenchen Zhang, Hualei Zhu, Jiaheng Liu, Xianjie Wu, Ge Zhang, Tianyu Liu, Zhoujun Li

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

Comments Preprint

The Impact of Prompt Programming on Function-Level Code Generation

Ranim Khojah, Francisco Gomes de Oliveira Neto, Mazen Mohamad, Philipp Leitner

机构 * Chalmers University of Technology and University of Gothenburg（查尔姆斯理工大学和哥德堡大学） ； RISE Research Institutes of Sweden（瑞典RISE研究机构） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.LG

Comments Accepted at Transactions on Software Engineering (TSE). CodePromptEval dataset and replication package on GitHub: https://github.com/icetlab/CodePromptEval

Smaller = Weaker? Benchmarking Robustness of Quantized LLMs in Code Generation

Sen Fang, Weiyuan Ding, Antonio Mastropaolo, Bowen Xu

机构 * NC State University（北卡罗来纳州立大学） ； William & Mary（威廉与玛丽学院） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.PL

Comments 13 pages, 6 figures

Towards Generalized and Stealthy Watermarking for Generative Code Models

Haoxuan Li, Jiale Zhang, Xiaobing Sun, Xiapu Luo

专题命中 代码生成 ：code model(title,abstract)；code generation(abstract)

Comments 13 pages

Multi-Turn Code Generation Through Single-Step Rewards

Arnav Kumar Jain, Gonzalo Gonzalez-Pumariega, Wayne Chen, Alexander M Rush, Wenting Zhao, Sanjiban Choudhury

机构 * Mila- Quebec AI Institute（魁北克AI研究所） ； Cornell University（康奈尔大学） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 9 pages (not including references or appendix); 5 figures (in main paper); (v2) camera-ready version

Evaluating Long Range Dependency Handling in Code Generation LLMs

Yannick Assogba, Donghao Ren

机构 * Apple（苹果公司） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.CL、cs.AI、cs.LG

Comments 36 pages, 18 figures

Journal ref Transactions on Machine Learning Research, 2025. ISSN 2835-8856. https://openreview.net/forum?id=yzACI2vFaX

SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflows

Rebecca Saul, Hao Wang, Koushik Sen, David Wagner

专题命中 代码生成 ：code generation(title,abstract)；coding agent(abstract)

Chain of Grounded Objectives: Bridging Process and Goal-oriented Prompting for Code Generation

Sangyeop Yeo, Seung-won Hwang, Yu-Seung Ma

机构 * Electronics and Telecommunications Research Institute（电子电信研究院） ； Department of Computer Science and Engineering, Seoul National University（计算机科学与工程系，首尔国立大学） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

Comments Accepted by ECOOP 2025 main conference

GiFT: Gibbs Fine-Tuning for Code Generation

Haochen Li, Wanjin Feng, Xin Zhou, Zhiqi Shen

机构 * Nanyang Technological University（南洋理工大学） 纠错

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.LG

Comments Accepted to ACL 2025

AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models

Shuyang Hou, Zhangxiao Shen, Huayi Wu, Jianyuan Liang, Haoyue Jiao, Yaxian Qing, Xiaopu Zhang, Xu Li, Zhipeng Gui, Xuefeng Guan, Longgang Xiang

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

Prism: Dynamic and Flexible Benchmarking of LLMs Code Generation with Monte Carlo Tree Search

Vahid Majdinasab, Amin Nikanjam, Foutse Khomh

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.LG

Shedding Light in Task Decomposition in Program Synthesis: The Driving Force of the Synthesizer Model

Janis Zenkner, Tobias Sesterhenn, Christian Bartelt

专题命中 代码生成 ：program synthesis(title,abstract)；分类 cs.SE、cs.LG、cs.PL

Comments Accepted at ICLR 2025 Workshop Deep Learning for Code

Top General Performance = Top Domain Performance? DomainCodeBench: A Multi-domain Code Generation Benchmark

Dewu Zheng, Yanlin Wang, Ensheng Shi, Xilin Liu, Yuchi Ma, Hongyu Zhang, Zibin Zheng

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments

Hojae Han, Seung-won Hwang, Rajhans Samdani, Yuxiong He

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

Comments ICLR 2025

Deep-Bench: Deep Learning Benchmark Dataset for Code Generation

Alireza Daghighfarsoodeh, Chung-Yu Wang, Hamed Taherkhani, Melika Sepidband, Mohammad Abdollahi, Hadi Hemmati, Hung Viet Pham

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.LG

Prompting Techniques for Secure Code Generation: A Systematic Investigation

Catherine Tony, Nicolás E. Díaz Ferreyra, Markus Mutas, Salem Dhiff, Riccardo Scandariato

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.LG

Comments Work partially supported by the EU-funded project Sec4AI4Sec: Cybersecurity for AI-Augmented Systems (grant no. 101120393) - ACCEPTED at ACM Transactions on Software Engineering and Methodology (Feb. 2025)

LiCoEval: Evaluating LLMs on License Compliance in Code Generation

Weiwei Xu, Kai Gao, Hao He, Minghui Zhou

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.LG

Comments The 47th International Conference on Software Engineering(ICSE 2025)

Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation Capabilities

Hanbin Wang, Xiaoxuan Zhou, Zhipeng Xu, Keyuan Cheng, Yuxin Zuo, Kai Tian, Jingwei Song, Junting Lu, Wenhui Hu, Xueyang Liu

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

Comments 15 pages

Proving the Coding Interview: A Benchmark for Formally Verified Code Generation

Quinn Dougherty, Ronak Mehta

专题命中 代码生成 ：code generation(title)；program synthesis(abstract)；分类 cs.SE、cs.AI、cs.LG

Comments 8 pages, to appear at the 2025LLM4Code Workshop at ICSE 2025

GLLM: Self-Corrective G-Code Generation using Large Language Models with User Feedback

Mohamed Abdelaal, Samuel Lokadjaja, Gilbert Engert

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.LG

Journal ref Industrial Track of 21st Conference on Database Systems for Business, Technology and Web (BTW), 2025

OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

Tianyu Zheng, Ge Zhang, Tianhao Shen, Xueling Liu, Bill Yuchen Lin, Jie Fu, Wenhu Chen, Xiang Yue

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.AI

Effective LLM-Driven Code Generation with Pythoness

Kyla H. Levin, Kyle Gwilt, Emery D. Berger, Stephen N. Freund

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.AI、cs.PL

Comments 5 pages

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models

Martin Weyssow, Xin Zhou, Kisub Kim, David Lo, Houari Sahraoui

专题命中 代码生成 ：code generation(title,abstract)；分类 cs.SE、cs.CL、cs.LG