MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos. - Amir Zadeh 001; Rowan Zellers; Eli Pincus; Louis-Philippe Morency (CoRR, 2016)

Multimodal Sentiment Intensity Analysis in Videos: Facial Gestures and Verbal Messages. - Amir Zadeh 001; Rowan Zellers; Eli Pincus; Louis-Philippe Morency (IEEE Intell. Syst., 2016)

Zero-Shot Activity Recognition with Verb Attribute Induction. - Rowan Zellers; Yejin Choi 001 (EMNLP, 2017)

Neural Motifs: Scene Graph Parsing With Global Context. - Rowan Zellers; Mark Yatskar; Sam Thomson; Yejin Choi 001 (CVPR, 2018)

SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference. - Rowan Zellers; Yonatan Bisk; Roy Schwartz 001; Yejin Choi 001 (EMNLP, 2018)

HellaSwag: Can a Machine Really Finish Your Sentence? - Rowan Zellers; Ari Holtzman; Yonatan Bisk; Ali Farhadi; Yejin Choi 001 (ACL (1), 2019)

From Recognition to Cognition: Visual Commonsense Reasoning. - Rowan Zellers; Yonatan Bisk; Ali Farhadi; Yejin Choi 001 (CVPR, 2019)

Defending Against Neural Fake News. - Rowan Zellers; Ari Holtzman; Hannah Rashkin; Yonatan Bisk; Ali Farhadi; Franziska Roesner; Yejin Choi 001 (NeurIPS, 2019)

PIQA: Reasoning about Physical Commonsense in Natural Language. - Yonatan Bisk; Rowan Zellers; Ronan Le Bras 001; Jianfeng Gao 001; Yejin Choi 001 (AAAI, 2020)

Adversarial Filters of Dataset Biases. - Ronan Le Bras 001; Swabha Swayamdipta; Chandra Bhagavatula; Rowan Zellers; Matthew E. Peters; Ashish Sabharwal; Yejin Choi 001 (ICML, 2020)

Evaluating Machines by their Real-World Language Use. - Rowan Zellers; Ari Holtzman; Elizabeth Clark; Lianhui Qin; Ali Farhadi; Yejin Choi 001 (CoRR, 2020)

Probing Text Models for Common Ground with Visual Representations. - Gabriel Ilharco; Rowan Zellers; Ali Farhadi; Hannaneh Hajishirzi (CoRR, 2020)

Edited Media Understanding: Reasoning About Implications of Manipulated Images. - Jeff Da; Maxwell Forbes; Rowan Zellers; Anthony Zheng; Jena D. Hwang; Antoine Bosselut; Yejin Choi 001 (CoRR, 2020)

Edited Media Understanding Frames: Reasoning About the Intent and Implications of Visual Misinformation. - Jeff Da; Maxwell Forbes; Rowan Zellers; Anthony Zheng; Jena D. Hwang; Antoine Bosselut; Yejin Choi 001 (ACL/IJCNLP (1), 2021)

PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World. - Rowan Zellers; Ari Holtzman; Matthew E. Peters; Roozbeh Mottaghi; Aniruddha Kembhavi; Ali Farhadi; Yejin Choi 001 (ACL/IJCNLP (1), 2021)

Probing Contextual Language Models for Common Ground with Visual Representations. - Gabriel Ilharco; Rowan Zellers; Ali Farhadi; Hannaneh Hajishirzi (NAACL-HLT, 2021)

NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints. - Ximing Lu; Peter West; Rowan Zellers; Ronan Le Bras 001; Chandra Bhagavatula; Yejin Choi 001 (NAACL-HLT, 2021)

TuringAdvice: A Generative and Dynamic Evaluation of Language Use. - Rowan Zellers; Ari Holtzman; Elizabeth Clark; Lianhui Qin; Ali Farhadi; Yejin Choi 001 (NAACL-HLT, 2021)

MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers. - Krishna Pillutla; Swabha Swayamdipta; Rowan Zellers; John Thickstun; Sean Welleck; Yejin Choi 001; Zaïd Harchaoui (NeurIPS, 2021)

MERLOT: Multimodal Neural Script Knowledge Models. - Rowan Zellers; Ximing Lu; Jack Hessel; Youngjae Yu; Jae Sung Park; Jize Cao; Ali Farhadi; Yejin Choi 001 (NeurIPS, 2021)

MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation. - Krishna Pillutla; Swabha Swayamdipta; Rowan Zellers; John Thickstun; Yejin Choi 001; Zaïd Harchaoui (CoRR, 2021)

MERLOT RESERVE: Neural Script Knowledge through Vision and Language and Sound. - Rowan Zellers; Jiasen Lu; Ximing Lu; Youngjae Yu; Yanpeng Zhao; Mohammadreza Salehi; Aditya Kusupati; Jack Hessel; Ali Farhadi; Yejin Choi 001 (CVPR, 2022)

The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning. - Jack Hessel; Jena D. Hwang; Jae Sung Park; Rowan Zellers; Chandra Bhagavatula; Anna Rohrbach; Kate Saenko; Yejin Choi 001 (ECCV (36), 2022)

NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics. - Ximing Lu; Sean Welleck; Peter West; Liwei Jiang; Jungo Kasai; Daniel Khashabi; Ronan Le Bras 001; Lianhui Qin; Youngjae Yu; Rowan Zellers; Noah A. Smith; Yejin Choi 001 (NAACL-HLT, 2022)

Connecting the Dots between Audio and Text without Parallel Data through Visual Knowledge Transfer. - Yanpeng Zhao; Jack Hessel; Youngjae Yu; Ximing Lu; Rowan Zellers; Yejin Choi 001 (NAACL-HLT, 2022)

Multimodal Knowledge Alignment with Reinforcement Learning. - Youngjae Yu; Jiwan Chung; Heeseung Yun; Jack Hessel; Jae Sung Park; Ximing Lu; Prithviraj Ammanabrolu; Rowan Zellers; Ronan Le Bras 001; Gunhee Kim; Yejin Choi 001 (CoRR, 2022)

Grounding Language by Seeing, Hearing, and Interacting - Rowan Zellers (2022)

Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contest. - Jack Hessel; Ana Marasovic; Jena D. Hwang; Lillian Lee; Jeff Da; Rowan Zellers; Robert Mankoff; Yejin Choi 001 (ACL (1), 2023)

Fusing Pre-Trained Language Models with Multimodal Prompts through Reinforcement Learning. - Youngjae Yu; Jiwan Chung; Heeseung Yun; Jack Hessel; Jae Sung Park; Ximing Lu; Rowan Zellers; Prithviraj Ammanabrolu; Ronan Le Bras 001; Gunhee Kim; Yejin Choi 001 (CVPR, 2023)

UNIFIED-IO: A Unified Model for Vision, Language, and Multi-modal Tasks. - Jiasen Lu; Christopher Clark; Rowan Zellers; Roozbeh Mottaghi; Aniruddha Kembhavi (ICLR, 2023)

MAUVE Scores for Generative Models: Theory and Practice. - Krishna Pillutla; Lang Liu; John Thickstun; Sean Welleck; Swabha Swayamdipta; Rowan Zellers; Sewoong Oh; Yejin Choi 001; Zaïd Harchaoui (J. Mach. Learn. Res., 2023)