Exploring Data-Efficient Adaptation of Large Language Models for Code Generation
Xue Jiang, Yihong Dong, Zhiyuan Fan, Zhi Jin, Wenpin Jiao, Ge Li
机构
*
Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education(高可信软件技术重点实验室(北京大学))
;
School of Computer Science, Peking University, Beijing(计算机学院(北京大学))
CWM: An Open-Weights LLM for Research on Code Generation with World Models
FAIR CodeGen team, Jade Copet, Quentin Carbonneaux, Gal Cohen, Jonas Gehring, Jacob Kahn, Jannik Kossen, Felix Kreuk, Emily McMilin, Michel Meyer, Yuxiang Wei, David Zhang, Kunhao Zheng, Jordi Armengol-Estapé, Pedram Bashiri, Maximilian Beck, Pierre Chambon, Abhishek Charnalia, Chris Cummins, Juliette Decugis, Zacharias V. Fisches, François Fleuret, Fabian Gloeckle, Alex Gu, Michael Hassid, Daniel Haziza, Badr Youbi Idrissi, Christian Keller, Rahul Kindi, Hugh Leather, Gallil Maimon, Aram Markosyan, Francisco Massa, Pierre-Emmanuel Mazaré, Vegard Mella, Naila Murray, Keyur Muzumdar, Peter O'Hearn, Matteo Pagliardini, Dmitrii Pedchenko, Tal Remez, Volker Seeker, Marco Selvi, Oren Sultan, Sida Wang, Luca Wehrstedt, Ori Yoran, Lingming Zhang, Taco Cohen, Yossi Adi, Gabriel Synnaeve
Chain of Grounded Objectives: Bridging Process and Goal-oriented Prompting for Code Generation
Sangyeop Yeo, Seung-won Hwang, Yu-Seung Ma
机构
*
Electronics and Telecommunications Research Institute(电子电信研究院)
;
Department of Computer Science and Engineering, Seoul National University(计算机科学与工程系,首尔国立大学)
CommentsWork partially supported by the EU-funded project Sec4AI4Sec: Cybersecurity for AI-Augmented Systems (grant no. 101120393) - ACCEPTED at ACM Transactions on Software Engineering and Methodology (Feb. 2025)