Stable LM 2 1.6B Technical Report. - Marco Bellagente; Jonathan Tow; Dakota Mahan; Duy Phung; Maksym Zhuravinskyi; Reshinth Adithyan; James Baicoianu; Ben Brooks; Nathan Cooper; Ashish Datta; Meng Lee; Emad Mostaque; et al. (CoRR, 2024)

Stable Code Technical Report. - Nikhil Pinnaparaju; Reshinth Adithyan; Duy Phung; Jonathan Tow; James Baicoianu; Ashish Datta; Maksym Zhuravinskyi; Dakota Mahan; Marco Bellagente; Carlos Riquelme; Nathan Cooper (CoRR, 2024)

Generative Reward Models. - Dakota Mahan; Duy Phung; Rafael Rafailov; Chase Blagden; Nathan Lile; Louis Castricato; Jan-Philipp Fränken; Chelsea Finn; Alon Albalak (CoRR, 2024)

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models. - Alex Havrilla; Andrew Dai 001; Laura O'Mahony; Koen Oostermeijer; Vera Zisler; Alon Albalak; Fabrizio Milo; Sharath Chandra Raparthy; Kanishk Gandhi; Baber Abbasi; Duy Phung; Maia Iyer; et al. (CoRR, 2024)

Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought. - Violet Xiang; Charlie Snell; Kanishk Gandhi; Alon Albalak; Anikait Singh; Chase Blagden; Duy Phung; Rafael Rafailov; Nathan Lile; Dakota Mahan; Louis Castricato; Jan-Philipp Fränken; et al. (CoRR, 2025)

Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models. - Alon Albalak; Duy Phung; Nathan Lile; Rafael Rafailov; Kanishk Gandhi; Louis Castricato; Anikait Singh; Chase Blagden; Violet Xiang; Dakota Mahan; Nick Haber (CoRR, 2025)