代码大模型 / AI 编程

Towards Large Language Model Aided Program Refinement

Yufan Cai, Zhe Hou, Xiaokun Luan, David Miguel Sanan Baena, Yun Lin, Jun Sun, Jin Song Dong

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

Optimizing Large Language Models for OpenAPI Code Completion

Bohdan Petryshyn, Mantas Lukoševičius

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

Comments Update: a better quality and readability of figures, better explanation of code infilling and document splitting in training, some text polishing, making it more compact

How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition

Guanting Dong, Hongyi Yuan, Keming Lu, Chengpeng Li, Mingfeng Xue, Dayiheng Liu, Wei Wang, Zheng Yuan, Chang Zhou, Jingren Zhou

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

Comments Accepted to ACL 2024 Main Conference

WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning

Zhaojian Yu, Xin Zhang, Ning Shang, Yangyu Huang, Can Xu, Yishujie Zhao, Wenxiang Hu, Qiufeng Yin

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

Rewriting the Code: A Simple Method for Large Language Model Augmented Code Search

Haochen Li, Xin Zhou, Zhiqi Shen

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

Comments Accepted to ACL 2024

Bayesian Program Learning by Decompiling Amortized Knowledge

Alessandro B. Palmarini, Christopher G. Lucas, N. Siddharth

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

LangProp: A code optimization framework using Large Language Models applied to driving

Shu Ishida, Gianluca Corrado, George Fedoseev, Hudson Yeo, Lloyd Russell, Jamie Shotton, João F. Henriques, Anthony Hu

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

Fewer Truncations Improve Language Modeling

Hantian Ding, Zijian Wang, Giovanni Paolini, Varun Kumar, Anoop Deoras, Dan Roth, Stefano Soatto

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

Comments ICML 2024

Batched Low-Rank Adaptation of Foundation Models

Yeming Wen, Swarat Chaudhuri

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

Comments 16 pages, 3 figures

IRCoder: Intermediate Representations Make Language Models Robust Multilingual Code Generators

Indraneil Paul, Goran Glavaš, Iryna Gurevych

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

Analyzing the Performance of Large Language Models on Code Summarization

Rajarshi Haldar, Julia Hockenmaier

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

Xiwu: A Basis Flexible and Learnable LLM for High Energy Physics

Zhengde Zhang, Yiyu Zhang, Haodong Yao, Jianwen Luo, Rui Zhao, Bo Huang, Jiameng Zhao, Yipu Liao, Ke Li, Lina Zhao, Jun Cao, Fazhi Qi, Changzheng Yuan

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

Comments 15 pages, 8 figures

Synergy of Large Language Model and Model Driven Engineering for Automated Development of Centralized Vehicular Systems

Nenad Petrovic, Fengjunjie Pan, Krzysztof Lebioda, Vahid Zolfaghari, Sven Kirchner, Nils Purschke, Muhammad Aqib Khan, Viktor Vorobev, Alois Knoll

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

Testing the Effect of Code Documentation on Large Language Model Code Understanding

William Macke, Michael Doyle

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

Comments 7 pages, 5 figures, 2 tables. Accepted as a Findings paper in the "Generation" track to NAACL 2024. MITRE Public Release Case Number 23-4132

Advancing LLM Reasoning Generalists with Preference Trees

Lifan Yuan, Ganqu Cui, Hanbin Wang, Ning Ding, Xingyao Wang, Jia Deng, Boji Shan, Huimin Chen, Ruobing Xie, Yankai Lin, Zhenghao Liu, Bowen Zhou, Hao Peng, Zhiyuan Liu, Maosong Sun

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

Comments Models and data are available at https://github.com/OpenBMB/Eurus

Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models

Thomas P. Zollo, Todd Morrill, Zhun Deng, Jake C. Snell, Toniann Pitassi, Richard Zemel

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

Comments 34 pages, 10 figures, published as conference paper at ICLR 2024, and accepted to the Socially Responsible Language Modelling Research (SoLaR) workshop at NeurIPS 2023

SoD$^2$: Statically Optimizing Dynamic Deep Neural Network

Wei Niu, Gagan Agrawal, Bin Ren

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

The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?

Alex Gu, Wen-Ding Li, Naman Jain, Theo X. Olausson, Celine Lee, Koushik Sen, Armando Solar-Lezama

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

Comments 54 pages, 25 figures

A Machine Learning Approach Towards SKILL Code Autocompletion

Enrique Dehaerne, Bappaditya Dey, Wannes Meert

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

Comments Accepted for SPIE Advanced Lithography + Patterning, 2024

Are ChatGPT and Other Similar Systems the Modern Lernaean Hydras of AI?

Dimitrios Ioannidis, Jeremy Kepner, Andrew Bowne, Harriet S. Bryant

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

Comments 40 pages, 100+ references, to appear in Fordham Law Review

Learning logic programs by discovering higher-order abstractions

Céline Hocquette, Sebastijan Dumančić, Andrew Cropper

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

Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code

Jie JW Wu

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

Comments 6 pages, 2 figures, 1 table. Accepted and presented at the 7th Annual Symposium on Machine Programming (MAPS 2023 Workshop, see https://mapsworkshop.github.io/). Reference: "Wu, Jie JW. Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code. The 7th Annual Symposium on Machine Programming (MAPS 23), December 3, 2023, San Francisco, CA, USA"

Grammar-Constrained Decoding for Structured NLP Tasks without Finetuning

Saibo Geng, Martin Josifoski, Maxime Peyrard, Robert West

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

Comments Accepted at EMNLP 2023 Main Conference

Lightweight reranking for language model generations

Siddhartha Jain, Xiaofei Ma, Anoop Deoras, Bing Xiang

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

LLM Augmented LLMs: Expanding Capabilities through Composition

Rachit Bansal, Bidisha Samanta, Siddharth Dalmia, Nitish Gupta, Shikhar Vashishth, Sriram Ganapathy, Abhishek Bapna, Prateek Jain, Partha Talukdar

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

Comments 17 pages, 2 figures, 8 tables

Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models

Terry Yue Zhuo, Armel Zebaze, Nitchakarn Suppattarachai, Leandro von Werra, Harm de Vries, Qian Liu, Niklas Muennighoff

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

Comments 25 pages (12 main), 19 figures, 8 tables

CodeScholar: Growing Idiomatic Code Examples

Manish Shetty, Koushik Sen, Ion Stoica

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

Coarse-Tuning Models of Code with Reinforcement Learning Feedback

Abhinav Jain, Chima Adiole, Swarat Chaudhuri, Thomas Reps, Chris Jermaine

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

Comments 23 pages

Exploring Distributional Shifts in Large Language Models for Code Analysis

Shushan Arakelyan, Rocktim Jyoti Das, Yi Mao, Xiang Ren

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

EvoPrompting: Language Models for Code-Level Neural Architecture Search

Angelica Chen, David M. Dohan, David R. So

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

Comments NeurIPS 2023