代码大模型 / AI 编程

AdaptFlow: Adaptive Workflow Optimization via Meta-Learning

Runchuan Zhu, Bowen Jiang, Lingrui Mei, Fangkai Yang, Lu Wang, Haoxiang Gao, Fengshuo Bai, Pu Zhao, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang

机构 * Peking University（北京大学） ； University of Chinese Academy of Sciences（中国科学院大学） ； Microsoft（微软公司） ； Shanghai Jiaotong University（上海交通大学） 纠错

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

A Taxonomy of Inefficiencies in LLM-Generated Python Code

Altaf Allah Abbassi, Leuson Da Silva, Amin Nikanjam, Foutse Khomh

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

Optimizing Prompt Sequences using Monte Carlo Tree Search for LLM-Based Optimization

Fei Xu Yu, Gina Adam, Nathaniel D. Bastian, Tian Lan

机构 * The George Washington University（乔治·华盛顿大学） ； United States Military Academy（美国军事学院） 纠错

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

KG-Augmented Executable CoT for Mathematical Coding

Xingyu Chen, Junxiu An, Jun Guo, Li Wang, Jingcai Guo

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

Comments 9 pages,2figures,6 tables

Analyzing Prominent LLMs: An Empirical Study of Performance and Complexity in Solving LeetCode Problems

Everton Guimaraes, Nathalia Nascimento, Chandan Shivalingaiah, Asish Nelapati

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

Comments 11 pages, 13 figures, 29th International Conference on Evaluation and Assessment in Software Engineering (EASE)

A Human Centric Requirements Engineering Framework for Assessing Github Copilot Output

Soroush Heydari

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

Comments 8 pages

RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution

Shang Liu, Wenji Fang, Yao Lu, Qijun Zhang, Hongce Zhang, Zhiyao Xie

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

Comments This is the LAD Conference version of RTLCoder, for the TCAD extension version, please refer to: arXiv:2312.08617v4

SmartLLMs Scheduler: A Framework for Cost-Effective LLMs Utilization

Yueyue Liu, Hongyu Zhang, Yuantian Miao

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

Everyone Contributes! Incentivizing Strategic Cooperation in Multi-LLM Systems via Sequential Public Goods Games

Yunhao Liang, Yuan Qu, Jingyuan Yang, Shaochong Lin, Zuo-Jun Max Shen

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

Testing the Untestable? An Empirical Study on the Testing Process of LLM-Powered Software Systems

Cleyton Magalhaes, Italo Santos, Brody Stuart-Verner, Ronnie de Souza Santos

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

Is LLM-Generated Code More Maintainable \& Reliable than Human-Written Code?

Alfred Santa Molison, Marcia Moraes, Glaucia Melo, Fabio Santos, Wesley K. G. Assuncao

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

Comments Accepted ESEM2025

Comparison of Large Language Models for Deployment Requirements

Alper Yaman, Jannik Schwab, Christof Nitsche, Abhirup Sinha, Marco Huber

机构 * Fraunhofer Institute for Manufacturing Engineering and Automation IPA（弗劳恩霍夫智能制造与自动化研究所） 纠错

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

Journal ref Proceedings of the First International Conference on Generative Pre-trained Transformer Models and Beyond (GPTMB 2024), Porto, Portugal, Jun. 2024, pp. 41-44, ISBN: 978-1-68558-182-4

OR-LLM-Agent: Automating Modeling and Solving of Operations Research Optimization Problems with Reasoning LLM

Bowen Zhang, Pengcheng Luo, Genke Yang, Boon-Hee Soong, Chau Yuen

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

Comments 8 pages, 13 figures

Vulnerability Handling of AI-Generated Code -- Existing Solutions and Open Challenges

Sabrina Kaniewski, Dieter Holstein, Fabian Schmidt, Tobias Heer

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

Comments Accepted for publication @ IEEE AIxSET 2024; 4 pages, 2 Figures

A Multi-Agent Generative AI Framework for IC Module-Level Verification Automation

Wenbo Liu, Forbes Hou, Jon Zhang, Hong Liu, Allen Lei

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

Comments 20 pages, 12 figures. DVCon China 2025

Curiosity by Design: An LLM-based Coding Assistant Asking Clarification Questions

Harsh Darji, Thibaud Lutellier

机构 * University of Alberta（阿尔伯塔大学） 纠错

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

Technical Report of TeleChat2, TeleChat2.5 and T1

Zihan Wang, Xinzhang Liu, Yitong Yao, Chao Wang, Yu Zhao, Zhihao Yang, Wenmin Deng, Kaipeng Jia, Jiaxin Peng, Yuyao Huang, Sishi Xiong, Zhuo Jiang, Kaidong Yu, Xiaohui Hu, Fubei Yao, Ruiyu Fang, Zhuoru Jiang, Ruiting Song, Qiyi Xie, Rui Xue, Xuewei He, Yanlei Xue, Zhu Yuan, Zhaoxi Zhang, Zilu Huang, Shiquan Wang, Xin Wang, Hanming Wu, Mingyuan Wang, Xufeng Zhan, Yuhan Sun, Zhaohu Xing, Yuhao Jiang, Bingkai Yang, Shuangyong Song, Yongxiang Li, Zhongjiang He, Xuelong Li

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

Comments 32 pages, 5 figures

PhaseNAS: Language-Model Driven Architecture Search with Dynamic Phase Adaptation

Fei Kong, Xiaohan Shan, Yanwei Hu, Jianmin Li

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

Comments 14pages

LLMs-guided adaptive compensator: Bringing Adaptivity to Automatic Control Systems with Large Language Models

Zhongchao Zhou, Yuxi Lu, Yaonan Zhu, Yifan Zhao, Bin He, Liang He, Wenwen Yu, Yusuke Iwasawa

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

MoL-RL: Distilling Multi-Step Environmental Feedback into LLMs for Feedback-Independent Reasoning

Kang Yang, Jingxue Chen, Qingkun Tang, Tianxiang Zhang, Qianchun Lu

机构 * Dalian University of Technology（大连理工大学） ； Wired Product Operation Division, ZTE Corporation（中兴通讯无线产品运营部） 纠错

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

Comments 12pages,3figures

Semantics of Sets of Programs

Jinwoo Kim, Shaan Nagy, Thomas Reps, Loris D'Antoni

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

Comments 47 pages, 8 Figures

ChartGen: Scaling Chart Understanding Via Code-Guided Synthetic Chart Generation

Jovana Kondic, Pengyuan Li, Dhiraj Joshi, Zexue He, Shafiq Abedin, Jennifer Sun, Ben Wiesel, Eli Schwartz, Ahmed Nassar, Bo Wu, Assaf Arbelle, Aude Oliva, Dan Gutfreund, Leonid Karlinsky, Rogerio Feris

机构 * MIT（麻省理工学院） ； MIT-IBM Watson AI Labs（麻省理工-IBM沃森人工智能实验室） ； IBM Research（IBM研究院） 纠错

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

Agent0: Leveraging LLM Agents to Discover Multi-value Features from Text for Enhanced Recommendations

Blaž Škrlj, Benoît Guilleminot, Andraž Tori

机构 * Teads 纠错

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

Comments Agent4IR, KDD '25

3LM: Bridging Arabic, STEM, and Code through Benchmarking

Basma El Amel Boussaha, Leen AlQadi, Mugariya Farooq, Shaikha Alsuwaidi, Giulia Campesan, Ahmed Alzubaidi, Mohammed Alyafeai, Hakim Hacid

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

Megrez2 Technical Report

Boxun Li, Yadong Li, Zhiyuan Li, Congyi Liu, Weilin Liu, Guowei Niu, Zheyue Tan, Haiyang Xu, Zhuyu Yao, Tao Yuan, Dong Zhou, Yueqing Zhuang, Bo Zhao, Guohao Dai, Yu Wang

机构 * Infinigence-AI ； Aalto University（Aalto大学） ； Shanghai Jiao Tong University（上海交通大学） ； Tsinghua University（清华大学） 纠错

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

Adaptive Graph Pruning for Multi-Agent Communication

Boyi Li, Zhonghan Zhao, Der-Horng Lee, Gaoang Wang

机构 * Zhejiang University - University of Illinois Urbana-Champaign Institute（浙江大学 - 印第安纳大学厄巴纳-香槟分校研究所） ； Zhejiang University, College of Computer Science and Technology（浙江大学计算机科学与技术学院） 纠错

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

Comments ECAI 2025

Evaluating Intermediate Reasoning of Code-Assisted Large Language Models for Mathematics

Zena Al-Khalili, Nick Howell, Dietrich Klakow

机构 * Saarland University（萨尔兰大学） 纠错

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

Preventing Rogue Agents Improves Multi-Agent Collaboration

Ohav Barbi, Ori Yoran, Mor Geva

机构 * Blavatnik School of Computer Science and AI, Tel Aviv University（布劳维茨克计算机科学与人工智能学院，特拉维夫大学） 纠错

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

Comments Accepted as a spotlight to REALM (First Workshop for Research on Agent Language Models) at ACL 2025

VeriOpt: PPA-Aware High-Quality Verilog Generation via Multi-Role LLMs

Kimia Tasnia, Alexander Garcia, Tasnuva Farheen, Sazadur Rahman

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

Comments 9 pages, 7 figures, Accepted for ICCAD 2025, Munich, Germany

Faster and Space Efficient Indexing for Locality Sensitive Hashing

Bhisham Dev Verma, Rameshwar Pratap

机构 * Indian Institute of Technology Mandi（印度理工学院曼迪分校） ； Indian Institute of Technology Hyderabad（印度理工学院海得拉巴分校） 纠错

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