From Centralized to Self-Supervised: Pursuing Realistic Multi-Agent Reinforcement Learning. - Violet Xiang; Logan Cross; Jan-Philipp Fränken; Nick Haber (CoRR, 2023)

The BabyView dataset: High-resolution egocentric videos of infants' and young children's everyday experiences. - Bria Long; Violet Xiang; Stefan Stojanov; Robert Z. Sparks; Zi Yin; Grace E. Keene; Alvin W. M. Tan; Steven Y. Feng; Chengxu Zhuang; Virginia A. Marchman; Daniel L. K. Yamins; Michael C. Frank (CoRR, 2024)

Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models. - Logan Cross; Violet Xiang; Agam Bhatia; Daniel L. K. Yamins; Nick Haber (ICLR, 2025)

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)

ResearchCodeBench: Benchmarking LLMs on Implementing Novel Machine Learning Research Code. - Tianyu Hua; Harper Hua; Violet Xiang; Benjamin Klieger; Sang T. Truong; Weixin Liang; Fan-Yun Sun; Nick Haber (CoRR, 2025)

Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning. - Violet Xiang; Chase Blagden; Rafael Rafailov; Nathan Lile; Sang T. Truong; Chelsea Finn; Nick Haber (CoRR, 2025)

LitBench: A Benchmark and Dataset for Reliable Evaluation of Creative Writing. - Daniel Fein; Sebastian Russo; Violet Xiang; Kabir Jolly; Rafael Rafailov; Nick Haber (CoRR, 2025)