代码大模型 / AI 编程

Sens-Merging: Sensitivity-Guided Parameter Balancing for Merging Large Language Models

Shuqi Liu, Han Wu, Bowei He, Xiongwei Han, Mingxuan Yuan, Linqi Song

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

Explore-Construct-Filter: An Automated Framework for Rich and Reliable API Knowledge Graph Construction

Yanbang Sun, Qing Huang, Xiaoxue Ren, Zhenchang Xing, Xiaohong Li, Junjie Wang

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

An Interpretable Automated Mechanism Design Framework with Large Language Models

Jiayuan Liu, Mingyu Guo, Vincent Conitzer

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

Model Cascading for Code: A Cascaded Black-Box Multi-Model Framework for Cost-Efficient Code Completion with Self-Testing

Boyuan Chen, Mingzhi Zhu, Brendan Dolan-Gavitt, Muhammad Shafique, Siddharth Garg

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

Copyright in Generative Deep Learning

Giorgio Franceschelli, Mirco Musolesi

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

Comments Published in Data & Policy at https://www.cambridge.org/core/journals/data-and-policy/article/copyright-in-generative-deep-learning/C401539FDF79A6AC6CEE8C5256508B5E

Journal ref Data & Policy. 2022;4:e17

Verifying LLM-Generated Code in the Context of Software Verification with Ada/SPARK

Marcos Cramer, Lucian McIntyre

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

Reranking Laws for Language Generation: A Communication-Theoretic Perspective

António Farinhas, Haau-Sing Li, André F. T. Martins

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

Comments NeurIPS 2024 (spotlight)

Beyond Autoregression: Fast LLMs via Self-Distillation Through Time

Justin Deschenaux, Caglar Gulcehre

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

Logic-Q: Improving Deep Reinforcement Learning-based Quantitative Trading via Program Sketch-based Tuning

Zhiming Li, Junzhe Jiang, Yushi Cao, Aixin Cui, Bozhi Wu, Bo Li, Yang Liu, Danny Dongning Sun

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

Comments accepted by AAAI 2025

Analysis of LLMs vs Human Experts in Requirements Engineering

Cory Hymel, Hiroe Johnson

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

Comments 8 pages, 15 figures

If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs

Muhammad Khalifa, Yi-Chern Tan, Arash Ahmadian, Tom Hosking, Honglak Lee, Lu Wang, Ahmet Üstün, Tom Sherborne, Matthias Gallé

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

Comments 13 pages, 9 figures

PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback

Kanika Goswami, Puneet Mathur, Ryan Rossi, Franck Dernoncourt

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

From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation

Xingchen Wan, Han Zhou, Ruoxi Sun, Hootan Nakhost, Ke Jiang, Sercan Ö. Arık

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

Comments Expanded version of the ICLR 2025 paper

Enhancing Large Language Model Efficiencyvia Symbolic Compression: A Formal Approach Towards Interpretability

Lumen AI, Tengzhou No. 1 Middle School, Shihao Ji, Zihui Song, Fucheng Zhong, Jisen Jia, Zhaobo Wu, Zheyi Cao, Tianhao Xu

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

Compositional Hardness of Code in Large Language Models -- A Probabilistic Perspective

Yotam Wolf, Binyamin Rothberg, Dorin Shteyman, Amnon Shashua

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

Turbulence: Systematically and Automatically Testing Instruction-Tuned Large Language Models for Code

Shahin Honarvar, Mark van der Wilk, Alastair Donaldson

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

Comments Updated to the ICST2025 conference version

ARCEAK: An Automated Rule Checking Framework Enhanced with Architectural Knowledge

Junyong Chen, Ling-I Wu, Minyu Chen, Xiaoying Qian, Haoze Zhu, Qiongfang Zhang, Guoqiang Li

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

Comments 12 pages, 5 figures

Beyond the Sum: Unlocking AI Agents Potential Through Market Forces

Jordi Montes Sanabria, Pol Alvarez Vecino

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

Comments 20 pages, 5 figures

Pseudocode-Injection Magic: Enabling LLMs to Tackle Graph Computational Tasks

Chang Gong, Wanrui Bian, Zhijie Zhang, Weiguo Zheng

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

Comments 24 pages

CodeHalu: Investigating Code Hallucinations in LLMs via Execution-based Verification

Yuchen Tian, Weixiang Yan, Qian Yang, Xuandong Zhao, Qian Chen, Wen Wang, Ziyang Luo, Lei Ma, Dawn Song

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

Comments Accepted by AAAI 2025 main conference

SYNAPSE: SYmbolic Neural-Aided Preference Synthesis Engine

Sadanand Modak, Noah Patton, Isil Dillig, Joydeep Biswas

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

Comments Accepted (oral) at AAAI 25

Practical Design and Benchmarking of Generative AI Applications for Surgical Billing and Coding

John C. Rollman, Bruce Rogers, Hamed Zaribafzadeh, Daniel Buckland, Ursula Rogers, Jennifer Gagnon, Ozanan Meireles, Lindsay Jennings, Jim Bennett, Jennifer Nicholson, Nandan Lad, Linda Cendales, Andreas Seas, Alessandro Martinino, E. Shelley Hwang, Allan D. Kirk

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

Comments 21 pages, 3 figures, 2 tables

RTLSquad: Multi-Agent Based Interpretable RTL Design

Bowei Wang, Qi Xiong, Zeqing Xiang, Lei Wang, Renzhi Chen

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

Do Code LLMs Understand Design Patterns?

Zhenyu Pan, Xuefeng Song, Yunkun Wang, Rongyu Cao, Binhua Li, Yongbin Li, Han Liu

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

Comments accpeted by llm4code workshop in ICSE 2025

ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono

Jingquan Wang, Harry Zhang, Khailanii Slaton, Shu Wang, Radu Serban, Jinlong Wu, Dan Negrut

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

CodeVision: Detecting LLM-Generated Code Using 2D Token Probability Maps and Vision Models

Zhenyu Xu, Victor S. Sheng

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

Seed-CTS: Unleashing the Power of Tree Search for Superior Performance in Competitive Coding Tasks

Hao Wang, Boyi Liu, Yufeng Zhang, Jie Chen

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

M-Ped: Multi-Prompt Ensemble Decoding for Large Language Models

Jiaxin Guo, Daimeng Wei, Yuanchang Luo, Shimin Tao, Hengchao Shang, Zongyao Li, Shaojun Li, Jinlong Yang, Zhanglin Wu, Zhiqiang Rao, Hao Yang

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

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

Aman Chaturvedi, Daniel Nichols, Siddharth Singh, Abhinav Bhatele

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

Tree-of-Code: A Hybrid Approach for Robust Complex Task Planning and Execution

Ziyi Ni, Yifan Li, Daxiang Dong

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

Comments Submitted to the Neurips Workshop "System 2 Reasoning" in September, 2024. The openreview is avaliable at https://openreview.net/forum?id=8NKAL8Ngxk