Rowan Zellers
Rowan Zellers is an AI researcher known for commonsense benchmarks and multimodal models that learn from video. During his University of Washington PhD under Yejin Choi and Ali Farhadi, he coauthored the SWAG and HellaSwag datasets, was lead author of the Grover fake-news paper, and shared a NeurIPS 2021 Outstanding Paper award for MAUVE. His MERLOT and MERLOT Reserve models learned from millions of YouTube videos. After finishing his PhD in 2022 he chose OpenAI, where he worked on GPT-4 and led video perception for GPT-4o in 2024. He is a researcher at Thinking Machines, working on vision and large language models.
- Now at
- Thinking Machines Lab
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Timeline
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2016
Harvey Mudd and a UW PhD
He graduates from Harvey Mudd College in 2016 with majors in computer science and mathematics. His PhD at the University of Washington, advised by Yejin Choi and Ali Farhadi, runs from 2016 to 2022.
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2018–2019
SWAG and HellaSwag datasets
In 2018, he coauthors the SWAG dataset of 113k multiple choice questions about grounded situations with Yonatan Bisk, Roy Schwartz and Yejin Choi. In 2019, he coauthors HellaSwag with Ari Holtzman, Yonatan Bisk, Ali Farhadi and Yejin Choi, a commonsense challenge dataset on which state-of-the-art models struggle.
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2019
Grover and neural fake news
He is lead author of the NeurIPS 2019 paper "Defending Against Neural Fake News", which presents Grover, a model that writes an article from a headline. Grover raises detection of AI-written news from 73% to 92% accuracy, and he argues for releasing the model to researchers so that defenses can improve.
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2021
A NeurIPS Outstanding Paper
MAUVE, a comparison measure for open-ended text generation, receives a NeurIPS 2021 Outstanding Paper award. He coauthors it with Krishna Pillutla, Swabha Swayamdipta, John Thickstun, Sean Welleck, Yejin Choi and Zaid Harchaoui, and it compares the distribution of a text generation model with the distribution of human-written text.
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2021–2022
MERLOT learns from YouTube
In 2021, he is first author of MERLOT, a model that learns multimodal script knowledge from millions of YouTube videos with transcribed speech. In 2022, he is first author of MERLOT Reserve, which learns from audio, subtitles and video frames and pretrains on 20 million YouTube videos.
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2022
Joining OpenAI after the PhD
He finishes his PhD at the University of Washington in June 2022. After a job search that brings academic offers, he signs with OpenAI.
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2023–2024
GPT-4 and GPT-4o at OpenAI
At OpenAI, he works on text and image understanding and evaluation for GPT-4 in 2023. For GPT-4o in 2024, he leads video perception, including architecture, pretraining, data and evaluations, and helps make a real-time audio and video demo happen.
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As of October 2026
Researcher at Thinking Machines
He is a researcher at Thinking Machines working on vision and large language models across the stack, and lives in San Francisco.
Career
- NowThinking Machines LabResearcher
- Until 2024OpenAI
Education
- 2022University of WashingtonPhD
- 2016Harvey Mudd CollegeUndergraduate student
Sources and credits
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- Rowan Zellers' Homepage
- Rowan Zellers (U. of Washington) - Grounding Language by Seeing, Hearing, and Interacting | DSI
- Why I chose OpenAI over academia: reflections on the CS academic and industry job markets (part 2) - Rowan Zellers' blog
- SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference - ACL Anthology
- HellaSwag: Can a Machine Really Finish Your Sentence? - ACL Anthology
- Allen School and AI2 researchers unveil Grover, a new tool for fighting fake news in the age of AI
- To detect fake news, this AI first learned to write it | TechCrunch
- NeurIPS 2021 Awards
- MERLOT: Multimodal Neural Script Knowledge Models
- MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound
- Reflections on the CS academic and industry job markets (part 1) - Rowan Zellers' blog

