代码大模型 / AI 编程

Pel, A Programming Language for Orchestrating AI Agents

Behnam Mohammadi

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

Comments 1. Updated author email address (I graduated so I added my alumni email). 2. Changed mono-font color to blue for better readability

Test-driven Software Experimentation with LASSO: an LLM Prompt Benchmarking Example

Marcus Kessel

机构 * University of Mannheim（曼海姆大学） 纠错

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

Comments under review

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models

Rihui Jin, Zheyu Xin, Xing Xie, Zuoyi Li, Guilin Qi, Yongrui Chen, Xinbang Dai, Tongtong Wu, Gholamreza Haffari

机构 * Southeast University（东南大学） ； Monash University（墨尔本大学） 纠错

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

ProSec: Fortifying Code LLMs with Proactive Security Alignment

Xiangzhe Xu, Zian Su, Jinyao Guo, Kaiyuan Zhang, Zhenting Wang, Xiangyu Zhang

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

Comments The first two authors contributed equally to this work

Generating Automotive Code: Large Language Models for Software Development and Verification in Safety-Critical Systems

Sven Kirchner, Alois C. Knoll

机构 * Technical University of Munich（慕尼黑技术大学） 纠错

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

Comments 8 pages; Accepted for publication at the 36th IEEE Intelligent Vehicles Symposium (IV), Cluj-Napoca, Romania, June 22-25, 2025

Mind the Gap: A Practical Attack on GGUF Quantization

Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, Martin Vechev

机构 * ETH Zurich, Switzerland（苏黎世联邦理工学院） ； The University of Tokyo, Japan（东京大学） ； University of California, Berkeley, USA（加州大学伯克利分校） 纠错

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

Comments ICML 2025

DeepSeek in Healthcare: A Survey of Capabilities, Risks, and Clinical Applications of Open-Source Large Language Models

Jiancheng Ye, Sophie Bronstein, Jiarui Hai, Malak Abu Hashish

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

HyGenar: An LLM-Driven Hybrid Genetic Algorithm for Few-Shot Grammar Generation

Weizhi Tang, Yixuan Li, Chris Sypherd, Elizabeth Polgreen, Vaishak Belle

机构 * University of Edinburgh（爱丁堡大学） 纠错

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

Comments Accepted to ACL 2025 Findings. Code available at https://github.com/RutaTang/HyGenar

CleanAgent: Automating Data Standardization with LLM-based Agents

Danrui Qi, Zhengjie Miao, Jiannan Wang

机构 * Simon Fraser University（西蒙弗雷泽大学） 纠错

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

Using Reasoning Models to Generate Search Heuristics that Solve Open Instances of Combinatorial Design Problems

Christopher D. Rosin

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

Comments arXiv admin note: text overlap with arXiv:2501.17725

LLM for SoC Security: A Paradigm Shift

Dipayan Saha, Shams Tarek, Katayoon Yahyaei, Sujan Kumar Saha, Jingbo Zhou, Mark Tehranipoor, Farimah Farahmandi

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

Comments 42 pages

MRT at SemEval-2025 Task 8: Maximizing Recovery from Tables with Multiple Steps

Maximiliano Hormazábal Lagos, Álvaro Bueno Saez, Héctor Cerezo-Costas, Pedro Alonso Doval, Jorge Alcalde Vesteiro

机构 * Fundación Centro Tecnolóxico de Telecomunicacións de Galicia (GRADIANT)（加利西亚电信技术基金会（GRADIANT）） 纠错

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

Comments 7 pages, 6 tables

Large Language Models for IT Automation Tasks: Are We There Yet?

Md Mahadi Hassan, John Salvador, Akond Rahman, Santu Karmaker

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

Comments 8 pages

Evaluating the Energy-Efficiency of the Code Generated by LLMs

Md Arman Islam, Devi Varaprasad Jonnala, Ritika Rekhi, Pratik Pokharel, Siddharth Cilamkoti, Asif Imran, Tevfik Kosar, Bekir Turkkan

机构 * University at Buffalo（布法罗大学） ； IBM Research（IBM研究院） 纠错

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

ComplexFormer: Disruptively Advancing Transformer Inference Ability via Head-Specific Complex Vector Attention

Jintian Shao, Hongyi Huang, Jiayi Wu, Beiwen Zhang, ZhiYu Wu, You Shan, MingKai Zheng

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

Comments We are withdrawing this submission as the underlying experiment is currently incomplete. We require additional time to gather more data and supplement the existing findings to ensure a comprehensive and robust presentation. We intend to resubmit once these additions are finalized

Subtle Errors in Reasoning: Preference Learning via Error-injected Self-editing

Kaishuai Xu, Tiezheng Yu, Wenjun Hou, Yi Cheng, Chak Tou Leong, Liangyou Li, Xin Jiang, Lifeng Shang, Qun Liu, Wenjie Li

机构 * The Hong Kong Polytechnic University（香港理工大学） ； Huawei Noah’s Ark Lab（华为诺亚实验室） 纠错

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

Comments accepted as ACL 2025 main

Large Language Models in Code Co-generation for Safe Autonomous Vehicles

Ali Nouri, Beatriz Cabrero-Daniel, Zhennan Fei, Krishna Ronanki, Håkan Sivencrona, Christian Berger

机构 * Volvo Cars（沃尔沃汽车公司） ； University of Gothenburg（哥德堡大学） ； Chalmers University of Technology（查尔姆斯理工大学） 纠错

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

Comments Accepted in the 44th International Conference on Computer Safety, Reliability and Security (SafeComp 2025)

Win Fast or Lose Slow: Balancing Speed and Accuracy in Latency-Sensitive Decisions of LLMs

Hao Kang, Qingru Zhang, Han Cai, Weiyuan Xu, Tushar Krishna, Yilun Du, Tsachy Weissman

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

Training Turn-by-Turn Verifiers for Dialogue Tutoring Agents: The Curious Case of LLMs as Your Coding Tutors

Jian Wang, Yinpei Dai, Yichi Zhang, Ziqiao Ma, Wenjie Li, Joyce Chai

机构 * The Hong Kong Polytechnic University（香港理工大学） ； University of Michigan（密歇根大学） 纠错

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

Comments Accepted to Findings of ACL 2025

Generalizing Large Language Model Usability Across Resource-Constrained

Yun-Da Tsai

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

Comments Doctoral disstertation

Planning-Driven Programming: A Large Language Model Programming Workflow

Chao Lei, Yanchuan Chang, Nir Lipovetzky, Krista A. Ehinger

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

Genetic Instruct: Scaling up Synthetic Generation of Coding Instructions for Large Language Models

Somshubra Majumdar, Vahid Noroozi, Mehrzad Samadi, Sean Narenthiran, Aleksander Ficek, Wasi Uddin Ahmad, Jocelyn Huang, Jagadeesh Balam, Boris Ginsburg

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

Comments Accepted to be presented in ACL 2025

ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction Tuning

Xinyi Wang, Jiashui Wang, Jinbo Su, Ke Wang, Peng Chen, Yanming Liu, Long Liu, Xiang Li, Yangdong Wang, Qiyuan Chen, Rongze Chen, Chunfu Jia

机构 * Nankai University（南开大学） ； Zhejiang University（浙江大学） ； Ant Group（蚂蚁集团） ； Renmin University of China（中国人民大学） ； University of the Chinese Academy of Sciences（中国科学院大学） 纠错

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

Comments 9 pages, multiple figures

CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction

Junlong Li, Daya Guo, Dejian Yang, Runxin Xu, Yu Wu, Junxian He

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

Comments ICML 2025

CodeGRAG: Bridging the Gap between Natural Language and Programming Language via Graphical Retrieval Augmented Generation

Kounianhua Du, Jizheng Chen, Renting Rui, Huacan Chai, Lingyue Fu, Wei Xia, Yasheng Wang, Ruiming Tang, Yong Yu, Weinan Zhang

机构 * Shanghai Jiao Tong University（上海交通大学） ； Huawei Noah’s Ark Lab Shanghai（华为诺亚实验室） 纠错

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

AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection

Tiankai Yang, Junjun Liu, Wingchun Siu, Jiahang Wang, Zhuangzhuang Qian, Chanjuan Song, Cheng Cheng, Xiyang Hu, Yue Zhao

机构 * University of Southern California（南加州大学） ； Carnegie Mellon University（卡内基梅隆大学） ； Arizona State University（亚利桑那州立大学） 纠错

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

Reasoning with OmniThought: A Large CoT Dataset with Verbosity and Cognitive Difficulty Annotations

Wenrui Cai, Chengyu Wang, Junbing Yan, Jun Huang, Xiangzhong Fang

机构 * Shanghai Jiao Tong University（上海交通大学） ； Alibaba Cloud Computing（阿里云计算） 纠错

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

Robust Learning of Diverse Code Edits

Tushar Aggarwal, Swayam Singh, Abhijeet Awasthi, Aditya Kanade, Nagarajan Natarajan

机构 * Microsoft Research India（微软印度研究院） 纠错

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

Comments To appear in ICML 2025 as 'NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits'

An Invitation to Deep Reinforcement Learning

Bernhard Jaeger, Andreas Geiger

机构 * University of Tübingen, Tübingen AI Center（图宾根大学，图宾根人工智能中心） 纠错

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

Comments Published at Foundations and Trends in Optimization

Journal ref Foundations and Trends in Optimization, 2024, Vol. 7: No. 1, pp 1-80

SynQ: An Embedded DSL for Synchronous System Design with Quantitative Types

Rui Chen, Ingo Sander

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

Comments 45 pages, 15 figures