代码大模型 / AI 编程

Conceptual Model Interpreter for Large Language Models

Felix Härer

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

Comments ER Forum 2023, 42nd International Conference on Conceptual Modeling (ER 2023), November 6-9, 2023, Lisbon, PT

ChatGPT for GTFS: Benchmarking LLMs on GTFS Understanding and Retrieval

Saipraneeth Devunuri, Shirin Qiam, Lewis Lehe

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

Comments 22 pages, 8 figures, 1 table, Public Transport

FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language

Mukul Singh, José Cambronero, Sumit Gulwani, Vu Le, Carina Negreanu, Elnaz Nouri, Mohammad Raza, Gust Verbruggen

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

Comments Contains inappropriately sourced conjecture of OpenAI's ChatGPT parameter count from www.forbes.com/sites/forbestechcouncil/2023/02/17/is-bigger-better-why-the-chatgpt-vs-gpt-3-vs-gpt-4-battle-is-just-a-family-chat, a citation which was omitted. The authors do not have direct knowledge or verification of this information, and relied solely on this article, which may lead to public confusion

How is ChatGPT's behavior changing over time?

Lingjiao Chen, Matei Zaharia, James Zou

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

Comments add more evaluations on instruction following

SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models

Hongxin Li, Jingran Su, Yuntao Chen, Qing Li, Zhaoxiang Zhang

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

Comments Accepted to NeurIPS 2023

TST$^\mathrm{R}$: Target Similarity Tuning Meets the Real World

Anirudh Khatry, Sumit Gulwani, Priyanshu Gupta, Vu Le, Ananya Singha, Mukul Singh, Gust Verbruggen

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

Comments Accepted for EMNLP-Findings, 2023

Towards the Imagenets of ML4EDA

Animesh Basak Chowdhury, Shailja Thakur, Hammond Pearce, Ramesh Karri, Siddharth Garg

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

Comments Invited paper, ICCAD 2023

Journal ref ICCAD 2023

Mistral 7B

Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed

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

Comments Models and code are available at https://mistral.ai/news/announcing-mistral-7b/

Unveiling the potential of large language models in generating semantic and cross-language clones

Palash R. Roy, Ajmain I. Alam, Farouq Al-omari, Banani Roy, Chanchal K. Roy, Kevin A. Schneider

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

Comments Accepted in IWSC

Towards Top-Down Automated Development in Limited Scopes: A Neuro-Symbolic Framework from Expressibles to Executables

Jian Gu, Harald C. Gall

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

Comments 5 pages, 3 figures, 2 tables, accepted by ESEC/FSE 2023, the camera-ready version

Code Detection for Hardware Acceleration Using Large Language Models

Pablo Antonio Martínez, Gregorio Bernabé, José Manuel García

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

Natural Language Generation and Understanding of Big Code for AI-Assisted Programming: A Review

Man Fai Wong, Shangxin Guo, Ching Nam Hang, Siu Wai Ho, Chee Wei Tan

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

Journal ref Entropy(2023), 25(6), 888

Exploring the Robustness of Large Language Models for Solving Programming Problems

Atsushi Shirafuji, Yutaka Watanobe, Takumi Ito, Makoto Morishita, Yuki Nakamura, Yusuke Oda, Jun Suzuki

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

Compositional Exemplars for In-context Learning

Jiacheng Ye, Zhiyong Wu, Jiangtao Feng, Tao Yu, Lingpeng Kong

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

Comments Accepted in ICML 2023

Analysis of ChatGPT on Source Code

Ahmed R. Sadik, Antonello Ceravola, Frank Joublin, Jibesh Patra

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

Comments 40 pages, examples provided for each experiment. arXiv admin note: text overlap with arXiv:2107.03374 by other authors

CodeT5+: Open Code Large Language Models for Code Understanding and Generation

Yue Wang, Hung Le, Akhilesh Deepak Gotmare, Nghi D. Q. Bui, Junnan Li, Steven C. H. Hoi

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

Comments 26 pages, preprint

Does Synthetic Data Generation of LLMs Help Clinical Text Mining?

Ruixiang Tang, Xiaotian Han, Xiaoqian Jiang, Xia Hu

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

Comments 10 pages, 8 tables, 4 figures

InCoder: A Generative Model for Code Infilling and Synthesis

Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, Mike Lewis

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

Comments ICLR 2023. v3: camera-ready that includes PLBART and OpenAI baselines

WikiCoder: Learning to Write Knowledge-Powered Code

Théo Matricon, Nathanaël Fijalkow, Gaëtan Margueritte

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

Comments Published in the proceedings of SPIN 2023

Large Language Models Are Human-Level Prompt Engineers

Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba

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

Learning Deep Semantics for Test Completion

Pengyu Nie, Rahul Banerjee, Junyi Jessy Li, Raymond J. Mooney, Milos Gligoric

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

Comments Accepted as a conference paper in ICSE 2023

SantaCoder: don't reach for the stars!

Loubna Ben Allal, Raymond Li, Denis Kocetkov, Chenghao Mou, Christopher Akiki, Carlos Munoz Ferrandis, Niklas Muennighoff, Mayank Mishra, Alex Gu, Manan Dey, Logesh Kumar Umapathi, Carolyn Jane Anderson, Yangtian Zi, Joel Lamy Poirier, Hailey Schoelkopf, Sergey Troshin, Dmitry Abulkhanov, Manuel Romero, Michael Lappert, Francesco De Toni, Bernardo García del Río, Qian Liu, Shamik Bose, Urvashi Bhattacharyya, Terry Yue Zhuo, Ian Yu, Paulo Villegas, Marco Zocca, Sourab Mangrulkar, David Lansky, Huu Nguyen, Danish Contractor, Luis Villa, Jia Li, Dzmitry Bahdanau, Yacine Jernite, Sean Hughes, Daniel Fried, Arjun Guha, Harm de Vries, Leandro von Werra

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

PADL: Language-Directed Physics-Based Character Control

Jordan Juravsky, Yunrong Guo, Sanja Fidler, Xue Bin Peng

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

Generation-Augmented Query Expansion For Code Retrieval

Dong Li, Yelong Shen, Ruoming Jin, Yi Mao, Kuan Wang, Weizhu Chen

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

Capturing Failures of Large Language Models via Human Cognitive Biases

Erik Jones, Jacob Steinhardt

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

Comments Published at NeurIPS 2022

Probing Pretrained Models of Source Code

Sergey Troshin, Nadezhda Chirkova

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

When Language Model Meets Private Library

Daoguang Zan, Bei Chen, Zeqi Lin, Bei Guan, Yongji Wang, Jian-Guang Lou

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

Comments EMNLP 2022 Findings

Leveraging Language to Learn Program Abstractions and Search Heuristics

Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas

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

Comments appeared in Thirty-eighth International Conference on Machine Learning (ICML 2021)

Learning to Synthesize Programs as Interpretable and Generalizable Policies

Dweep Trivedi, Jesse Zhang, Shao-Hua Sun, Joseph J. Lim

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

Comments NeurIPS 2021. 53 pages, 16 figures, 12 tables. Website at https://clvrai.github.io/leaps/

Explanatory Learning: Beyond Empiricism in Neural Networks

Antonio Norelli, Giorgio Mariani, Luca Moschella, Andrea Santilli, Giambattista Parascandolo, Simone Melzi, Emanuele Rodolà

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

Comments Main paper: 10 pages, References: 3 pages, Appendix: 7 pages