ResearchTrend.AI
CWM: An Open-Weights LLM for Research on Code Generation with World Models

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 W. 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
A. Gu
Michael Hassid
Daniel Haziza
Badr Youbi Idrissi
Christian Keller
Rahul Kindi
Hugh Leather
Gallil Maimon
Aram H. 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 I. Wang
Luca Wehrstedt
Ori Yoran
Lingming Zhang
Taco Cohen
Yossi Adi
Gabriel Synnaeve
ArXiv (abs)PDFHTMLHuggingFace (2 upvotes)Github (629★)

Papers citing "CWM: An Open-Weights LLM for Research on Code Generation with World Models"

1 / 1 papers shown
Title
The Art of Scaling Reinforcement Learning Compute for LLMs
The Art of Scaling Reinforcement Learning Compute for LLMs
Devvrit Khatri
Lovish Madaan
Rishabh Tiwari
Rachit Bansal
Sai Surya Duvvuri
Manzil Zaheer
Inderjit Dhillon
David Brandfonbrener
Rishabh Agarwal
OffRL
12
1
0
15 Oct 2025