代码大模型 / AI 编程

LTLCodeGen: Code Generation of Syntactically Correct Temporal Logic for Robot Task Planning

Behrad Rabiei, Mahesh Kumar A. R., Zhirui Dai, Surya L. S. R. Pilla, Qiyue Dong, Nikolay Atanasov

机构 * Contextual Robotics Institute, University of California San Diego（情境机器人研究所，加州大学圣地亚哥分校） 纠错

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

Comments Accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS) 2025

GP and LLMs for Program Synthesis: No Clear Winners

Jose Guadalupe Hernandez, Anil Kumar Saini, Gabriel Ketron, Jason H. Moore

专题命中 代码生成 ：program synthesis(title)

CodeTool: Enhancing Programmatic Tool Invocation of LLMs via Process Supervision

Yifei Lu, Fanghua Ye, Jian Li, Qiang Gao, Cheng Liu, Haibo Luo, Nan Du, Xiaolong Li, Feiliang Ren

机构 * Northeastern University（东北大学） ； Hunyuan AI Digital Human（文英AI数字人） 纠错

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

Comments ACL2025

ASTRA: Autonomous Spatial-Temporal Red-teaming for AI Software Assistants

Xiangzhe Xu, Guangyu Shen, Zian Su, Siyuan Cheng, Hanxi Guo, Lu Yan, Xuan Chen, Jiasheng Jiang, Xiaolong Jin, Chengpeng Wang, Zhuo Zhang, Xiangyu Zhang

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

Comments The first two authors (Xiangzhe Xu and Guangyu Shen) contributed equally to this work

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

Tool-integrated Reinforcement Learning for Repo Deep Search

Zexiong Ma, Chao Peng, Qunhong Zeng, Pengfei Gao, Yanzhen Zou, Bing Xie

机构 * Peking University（北京大学） ； ByteDance（字节跳动） ； Beijing Institute of Technology（北京理工大学） 纠错

专题命中 软件智能体 ：repository(abstract)；分类 cs.SE、cs.AI

Rubric Is All You Need: Enhancing LLM-based Code Evaluation With Question-Specific Rubrics

Aditya Pathak, Rachit Gandhi, Vaibhav Uttam, Arnav Ramamoorthy, Pratyush Ghosh, Aaryan Raj Jindal, Shreyash Verma, Aditya Mittal, Aashna Ased, Chirag Khatri, Yashwanth Nakka, Devansh, Jagat Sesh Challa, Dhruv Kumar

机构 * BITS Pilani（比特斯理工学院） 纠错

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

Comments Accepted in ICER 2025

Experimental Analysis of Productive Interaction Strategy with ChatGPT: User Study on Function and Project-level Code Generation Tasks

Sangwon Hyun, Hyunjun Kim, Jinhyuk Jang, Hyojin Choi, M. Ali Babar

机构 * Adelaide University（阿德莱德大学） ； Korea Advanced Institute of Science（韩国科学技术院） 纠错

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

Comments The benchmark repository has not been publicly released yet due to the IP policy in our institutions. If you would like to use the benchmark or collaborate on extension, please contact "dr.sangwon.hyun@gmail.com"