H2Lab @ UW

We explore fundamental research in generative AI and NLP to create solutions with real-world impact, advancing a future of AI that is open, transparent, and scientifically grounded. Our team's research spans:

• Large language models — developing pioneering methods, data technologies, and architectures to make these systems more powerful, efficient, and effective.
• Reasoning and Agents — developing Reinforcement Learning methods, reasoning algorithms, tool use, and agents.
• Open AI initiatives — building some of the first truly open models, such as OLMo and Tulu. We release state-of-the-art systems, datasets, training resources, and tools to the public to ensure traceability, reproducibility, and accessibility.
• Science of AI and evaluation — systematically examining the capabilities, limitations, and behaviors of AI systems to better understand how large models learn, reason, and make decisions.
• AI for science — creating systems that interpret scientific text and data, with a focus on integrating tools and intelligent agents to accelerate discovery.

Our work is regularly published at leading AI, ML, and NLP conferences (NeurIPS, ICLR, ICML, ACL, EMNLP, NAACL, COLM). Our open-source data, code, and models are hosted on Hugging Face and GitHub. As of 2025, our models have been downloaded over 10 million times. We are affiliated with UW-NLP and UW-AI.

• December 19, 2025:

  Akari Asai’s dissertation titled Beyond Scaling: Frontiers of Retrieval-Augmented Language Models received the 2025 AAAI/ACM SIGAI Dissertation Award.

• December 11, 2025:

  Congratulations to Prof. Hanna Hajishirzi for being named Fellows of the Association for Computational Linguistics 2025!

• November 25, 2025:

  Congratulations to Dr. Jiacheng Liu for successfully defending his Ph.D.

• November 1, 2025:

  Hao Xu’s and Jiacheng Liu’s Infini-gram mini received the best paper award at EMNLP 2025.

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