Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs

English as a Very High Level Language for Simulation Programming. In Proceedings of the ACM SIGPLAN Symposium on Very High Level Languages . Association for Computing Machinery, New York, NY, USA, 91–100

George E. Heidorn. 1974 · 1974

Earlier work this paper cites.

Automatic Evaluation of Machine Translation Quality Using Longest Common Subsequence and Skip-Bigram Statistics. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04) . Barcelona, Spain, 605–612

Chin-Yew Lin and Franz Josef Och. 2004 · 2004

Earlier work this paper cites.

Understanding the Factors That Impact the Popularity of GitHub Repositories. In 2016 IEEE International Conference on Software Maintenance and Evolution (ICSME) . 334–344

Hudson Borges, Andre Hora, and Marco Tulio Valente. 2016 · 2016

Earlier work this paper cites.

GitHub on BigQuery: Analyze All the Open Source Code

Felipe Hoffa. 2016 · 2016

Earlier work this paper cites.

Automated Unit Test Generation for Python. In Proceedings of the 12th Symposium on Search-based Software Engineering (SSBSE 2020, Bari, Italy, October 7–8) (Lecture Notes in Computer Science, Vol. 12420) . Springer, 9–24

Stephan Lukasczyk, Florian Kroiß, and Gordon Fraser. 2020 · 2020

Earlier work this paper cites.

ZeRO: Memory Optimizations toward Training Trillion Parameter Models. In International Conference for High Performance Computing, Networking, Storage and Analysis (SC)

Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase, and Yuxiong He. 2020 · 2020

Earlier work this paper cites.

Transformers: State-of-the-Art Natural Language Processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations , Qun Liu and David Schlangen (Eds.). Association for Computational Linguistics, 38–45

Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020

Earlier work this paper cites.

Program Synthesis with Large Language Models

Original

Jacob Austin, Augustus Odena, Maxwell Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie Cai, Michael Terry, Quoc Le, and Charles Sutton. 2021 · 2021

Earlier work this paper cites.

Evaluating large language models trained on code

Original

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021

Earlier work this paper cites.

Leveraging Automated Unit Tests for Unsupervised Code Translation. In International Conference on Learning Representations

Baptiste Roziere, Jie Zhang, Francois Charton, Mark Harman, Gabriel Synnaeve, and Guillaume Lample. 2021 · 2021

Earlier work this paper cites.

Multilingual training for software engineering. In Proceedings of the 44th International Conference on Software Engineering (Pittsburgh, Pennsylvania) (ICSE ’22) . Association for Computing Machinery, New York, NY, USA, 1443–1455

Toufique Ahmed and Premkumar Devanbu. 2022 · 2022

Earlier work this paper cites.

Multi-Lingual Evaluation of Code Generation Models. In The Eleventh International Conference on Learning Representations

Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, Xiaopeng Li, Yuchen Tian, Ming Tan, Wasi Uddin Ahmad, Shiqi Wang, Qing Sun, Mingyue Shang, Sujan Kumar Gonugondla, Hantian Ding, Varun Kumar, Nathan Fulton, Arash Farahani, Siddhartha Jain, Robert Giaquinto, Haifeng Qian, Murali Krishna Ramanathan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Sudipta Sengupta, Dan Roth, and Bing Xiang. 2022 · 2022

Earlier work this paper cites.

Code Generation Tools (Almost) for Free? A Study of Few-Shot, Pre-Trained Language Models on Code

Original

Patrick Bareiß, Beatriz Souza, Marcelo d’Amorim, and Michael Pradel. 2022 · 2022

Earlier work this paper cites.

On the Transferability of Pre-Trained Language Models for Low-Resource Programming Languages. In IEEE/ACM International Conference on Program Comprehension (ICPC) . Association for Computing Machinery, 401–412

Fuxiang Chen, Fatemeh H. Fard, David Lo, and Timofey Bryksin. 2022 · 2022

Earlier work this paper cites.

An empirical analysis of compute-optimal large language model training. In Advances in Neural Information Processing Systems , Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho (Eds.)

Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katherine Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Oriol Vinyals, Jack William Rae, and Laurent Sifre. 2022 · 2022

Earlier work this paper cites.

Deduplicating Training Data Makes Language Models Better. In Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . Association for Computational Linguistics, Dublin, Ireland, 8424–8445

Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, and Nicholas Carlini. 2022 · 2022

Earlier work this paper cites.

Training Language Models to Follow Instructions with Human Feedback. In Advances in Neural Information Processing Systems (NeurIPS) , Vol. 35. Curran Associates, Inc

Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022

Earlier work this paper cites.

A Systematic Evaluation of Large Language Models of Code. In Deep Learning for Code Workshop (DL4C)

Frank F. Xu, Uri Alon, Graham Neubig, and Vincent J. Hellendoorn. 2022 · 2022

Earlier work this paper cites.

Productivity Assessment of Neural Code Completion. In Proceedings of the 6th ACM SIGPLAN International Symposium on Machine Programming (San Diego, CA, USA) (MAPS 2022) . Association for Computing Machinery, New York, NY, USA, 21–29

Albert Ziegler, Eirini Kalliamvakou, X. Alice Li, Andrew Rice, Devon Rifkin, Shawn Simister, Ganesh Sittampalam, and Edward Aftandilian. 2022 · 2022

Earlier work this paper cites.

SantaCoder: Don’t Reach for the Stars!. In Deep Learning for Code Workshop (DL4C)

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, and Leandro von Werra. 2023 · 2023

Earlier work this paper cites.

PaLM 2 Technical Report

Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernandez Abrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vlad Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, Guy Gur-Ari, Steven Hand, Hadi Hashemi, Le Hou, Joshua Howland, Andrea Hu, Jeffrey Hui, Jeremy Hurwitz, Michael Isard, Abe Ittycheriah, Matthew Jagielski, Wenhao Jia, Kathleen Kenealy, Maxim Krikun, Sneha Kudugunta, Chang Lan, Katherine Lee, Benjamin Lee, Eric Li, Music Li, Wei Li, YaGuang Li, Jian Li, Hyeontaek Lim, Hanzhao Lin, Zhongtao Liu, Frederick Liu, Marcello Maggioni, Aroma Mahendru, Joshua Maynez, Vedant Misra, Maysam Moussalem, Zachary Nado, John Nham, Eric Ni, Andrew Nystrom, Alicia Parrish, Marie Pellat, Martin Polacek, Alex Polozov, Reiner Pope, Siyuan Qiao, Emily Reif, Bryan Richter, Parker Riley, Alex Castro Ros, Aurko Roy, Brennan Saeta, Rajkumar Samuel, Renee Shelby, Ambrose Slone, Daniel Smilkov, David R. So, Daniel Sohn, Simon Tokumine, Dasha Valter, Vijay Vasudevan, Kiran Vodrahalli, Xuezhi Wang, Pidong Wang, Zirui Wang, Tao Wang, John Wieting, Yuhuai Wu, Kelvin Xu, Yunhan Xu, Linting Xue, Pengcheng Yin, Jiahui Yu, Qiao Zhang, Steven Zheng, Ce Zheng, Weikang Zhou, Denny Zhou, Slav Petrov, and Yonghui Wu. 2023 · 2023

Earlier work this paper cites.

Model Card and Evaluations for Claude Models

Anthropic. 2023a · 2023

Earlier work this paper cites.

Terms of Service

Anthropic. 2023b · 2023

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Federico Cassano, John Gouwar, Daniel Nguyen, Sydney Nguyen, Luna Phipps-Costin, Donald Pinckney, Ming-Ho Yee, Yangtian Zi, Carolyn Jane Anderson, Molly Q. Feldman, Arjun Guha, Michael Greenberg, and Abhinav Jangda. 2023 · 2023

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Data Race Detection Using Large Language Models. In Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W) . Association for Computing Machinery, New York, NY, USA, 215–223

Le Chen, Xianzhong Ding, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, and Chunhua Liao. 2023 · 2023

Cited alongside, same era.

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CodeWhisperer. 2023 · 2023

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