Yejin Choi Wissner-Slivka Chair MacArthur Fellow Office: 578 Allen Center Fax: 206-685-2969 email: yejin@cs.washington.edu |
Paul G. Allen School of Computer Science & Engineering University of Washington Box 352350 185 E Stevens Way NE Seattle, WA 98195-2350 Allen Institute for Artificial Intelligence 2157 N Northlake Way, Suite 110 Seattle, WA 98103 |
News:
- A TED talk: "Why AI is Incredibly Smart --- and Shockingly Stupid"
- MacArthur Fellow (class of 2022); 2 min YouTube reel
→here
- Keynote at ACL: "2082: An ACL Odyssey: The Dark Matter of Language and Intelligence"
along with a fireside chat on "The Trajectory of ACL and the Next 60 years" and a pre-recorded talk
→here
- An invited article,
"The Curious Case of Commonsense Intelligence"
for the Daedalus's special issue on AI & Society
- A podcast interview with the Gradient on
commonsense and morality
- Featured by New Yorker: "Can Computers Learn Common Sense?"
- The TWIML AI Podcast with Sam Charrington on "Why is language the best medium for reasoning?"
- An interview by Dhruv Batra on Humans of AI: Stories, Not Stats
- Featured by NY Times on Delphi: "Can a Machine Learn Morality?"
- Promoted to a full professor as of Apr 2021, the new title effective on Sep 2021
- Endowed with the Brett Helsel Career Development Professorship (2020 - 2023)
- Won the AAAI Outstanding Paper Award 2020
- Featured by Quanta Magazine --- 🤖"Common Sense Comes Closer to Computers"🤖
- Our UW
Sounding Board team is
the winnner of the Alexa Prize!
- Our UW team (with Pooja, Max, Ari) won
the Facebook ParlAI award!
Awards:
Best/Outstanding Paper Awards:
- Best Paper Award at ACL 2023
- Outstanding Paper Award at ACL 2023
- Outstanding Paper Award at ICML 2022
- Best Paper Award at NAACL 2022
- Outstanding Paper Award at NeurIPS 2021
- Outstanding Paper Award at AAAI 2020
- Marr Prize at ICCV 2013
Test of Time:
- Longuet Higgins Prize at CVPR 2021
- Test of Time Award at ACL 2021
Finalists:
- IROS RoboCup Best Paper Finalist at IROS 2019
- Best Paper Nomination at ACL 2019
Recognition:
- Distinguished Research Fellow at the Institute for Ethics in AI at Oxford (2023)
- Wissner-Slivka Chair (2023 - current)
- MacArthur Fellow (2022)
- ACL Fellow (2022)
- Brett Helsel Career Development Professorship (2020 - 2023)
- Borg Early Career Award (BECA) (2018)
- IEEE AI's 10 to Watch (2016)
Recent Talks (2018 - 2023):
- Best Paper Award at ACL 2023
- Outstanding Paper Award at ACL 2023
- Outstanding Paper Award at ICML 2022
- Best Paper Award at NAACL 2022
- Outstanding Paper Award at NeurIPS 2021
- Outstanding Paper Award at AAAI 2020
- Marr Prize at ICCV 2013
Test of Time:
- Longuet Higgins Prize at CVPR 2021
- Test of Time Award at ACL 2021
Finalists:
- IROS RoboCup Best Paper Finalist at IROS 2019
- Best Paper Nomination at ACL 2019
Recognition:
- Distinguished Research Fellow at the Institute for Ethics in AI at Oxford (2023)
- Wissner-Slivka Chair (2023 - current)
- MacArthur Fellow (2022)
- ACL Fellow (2022)
- Brett Helsel Career Development Professorship (2020 - 2023)
- Borg Early Career Award (BECA) (2018)
- IEEE AI's 10 to Watch (2016)
Recent Talks (2018 - 2023):
Fall 2023 | Colloquium at MIT BCS |
Oct 2023 | Distinguished Lecture at TTIC |
Sep 2023 | Talk at the Department of Philosophy at NYU |
Sep 2023 | Talk at Cornell Tech |
Sep 2023 | Talk at MSR @ NYC |
Aug 2023 | Keynote at VLDB |
Aug 2023 | Talk at Duolingo |
Jun 2023 | Keynote at CVPR |
Jun 2023 |
Talk at the Institute for Ethics in AI at Oxford with the recorded talk ![]() |
May 2023 | Keynote at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS) |
May 2023 | Talk at MPI Tubingen |
May 2023 | Talk at the Caltech Class on Large Language and Vision Models |
May 2023 | Talk at the Institute for Assured Autonomy at Johns Hopkins University |
May 2023 | Talk at Harvard ML Foundations Seminar Series | May 2023 | SAIL Distinguished Lecture at Stanford |
Apr 2023 |
Talk at TED with the recorded talk ![]() |
Mar 2023 | Talk at AI For Tigray --- cancelled | Mar 2023 | Colloquium at Berkeley |
Mar 2023 | Guest Lecture at the Stanford CS324A: Advances in Foundation Models |
Feb 2023 | Guest Lecture at the Stanford CS25: Transformers United V2 |
Feb 2023 | Talk at the Continual Causality AAAI bridge program |
Jan 2023 | Talk at IBM Workshop on Neuro-Symbolic AI |
Jan 2023 | Talk at ALPS, the NLP winter school |
Dec 2022 |
Panel at AI Debate 3
with the recorded talk ![]() |
Dec 2022 | Talk at the NeurIPS workshop on Robustness in Sequence Modeling |
Nov 2022 |
Talk at SoCal NLP Symposium
with the recorded talk ![]() |
Nov 2022 | Talk at AI2050 |
Oct 2022 | Colloquium at Hebrew University |
Oct 2022 | YanDex Distinguished Lecture at Tel-Aviv University |
Oct 2022 | Panel at Microsoft Research Summit on What’s next in large-scale AI |
Oct 2022 | Tutorial at COLING on NS4NLP: Neuro-Symbolic Modeling for NLP |
Sep 2022 |
Keynote at Interspeech with the recorded talk ![]() |
Sep 2022 | Talk at the Simons Foundation Symposium on New Directions in Theoretical Machine Learning |
Sep 2022 | Talk at Penn State University |
Sep 2022 | Keynote at the 19th International Conference on Principles of Knowledge Representation and Reasoning (KR 2022) |
July 2022 | Keynote at the NAACL Workshop on Narrative Understanding |
May 2022 |
Keynote ACL "2082: An ACL Odyssey: The Dark Matter of Language and Intelligence" and a fireside chat on "The Trajectory of ACL and the Next 60 years" with the pre-recorded talk ![]() |
May 2022 | Keynote at the ACL Workshop on Deep Learning Inside Out (DeeLIO): Knowledge Extraction and Integration for Deep Learning Architectures |
Apr 2022 | Panel on "Ethics, Safety, and AI: Can we have it all?" at the Center for Advancing Safety of Machine Intelligence |
Mar 2022 | Distinguished Lecture at Microsoft Research |
Mar 2022 | Keynote at the AAAI Spring Symposium on Ethical Computing: Metrics for Measuring AI’s Proficiency and Competency for Ethical Reasoning |
Mar 2022 | Distinguished Lecture at Max Planck Institute |
Feb 2022 | Keynote at WSDM |
Dec 2021 | Keynote at the NeurIPS workshop on Efficient Natural Language and Speech Processing (ENLSP) |
Dec 2021 | Keynote at the NeurIPS workshop on CtrlGen: Controllable Generative Modeling in Language and Vision |
Nov 2021 | Talk at the SNU AI Policy Initiative, SAPI |
Nov 2021 | Talk at the University of Texas Austin |
Nov 2021 | Keynote at the EMNLP workshop on Novel Ideas in Learning-to-Learn through Interaction (NILLI) |
Oct 2021 | Panel at Microsoft Research Summit on Large-scale Neural Platform Models: Opportunities, Concerns, and Directions |
Oct 2021 | Colloquium at UPenn |
Oct 2021 | Talk at Georgia Tech: "Knowledge is Power: Symbolic Knowledge Distillation, Commonsense Morality, and Multimodal Script Knowledge" |
Aug 2021 |
Keynote at the Stanford FORUM Workshop on Universal Models: "David V.S. Goliath: the Art of Leaderboarding in the Era of Extreme-Scale Neural Models"
with the recorded talk ![]() ![]() |
Aug 2021 | Panel at the ACL workshop on NLP for Positive Impact |
Jul 2021 | Distinguished Lecture at Sony |
Jun 2021 | Keynote at the NAACL workshop on Visually Grounded Interaction and Language (ViGIL) |
Jun 2021 | Keynote at the NAACL workshop on Advances in Language and Vision Research (ALVR) |
May 2021 | Keynote at the ICLR workshop on Workshop on Enormous Language Models (WELM): "David V.S. Goliath in the Era of Gigantic Neural Networks" |
May 2021 | Keynote at ICLR: "Commonsense AI: Myth and Truth" |
Apr 2021 | Keynote at WebConf (formerly WWW) |
Mar 2021 | Talk at Facebook AI |
Feb 2021 |
Keynote at the 1st ELLIS NLP Symposium
with a recorded talk ![]() |
Feb 2021 | Keynote at the AAAI Workshop on Commonsense Knowledge Graphs |
Jan 2021 |
Teaching at the ALPS Winter School with recorded lectures ![]() |
Jan 2021 |
Talk at UCL Dark Lab with a recorded talk ![]() |
Dec 2020 |
Panel at AI Debate 2 at Montreal.ai with a recorded talk ![]() ![]() |
Dec 2020 | Keynote at the Neurips Workshop on Self-Supervised Learning -- Theory and Practice |
Dec 2020 | Keynote at the Neurips Workshop on Dataset Curation and Security |
Dec 2020 | Talk at ByteDance |
Nov 2020 | Keynote at the AAAI Fall Symposium on Abstraction and Analogy |
Nov 2020 | Talk at the Distinguished Lecture Series at NSF CISE on "Intuitive Reasoning as (Un)supervised Neural Generation" |
Nov 2020 |
Talk at MIT CSAIL Embodied Intelligence
with a recorded talk ![]() |
Oct 2020 |
Keynote at the Fall Stanford Human-Centered AI (HAI) Conference on Triangulating Intelligence: Melding Neuroscience, Psychology, and AI
with a recorded talk ![]() |
Oct 2020 | Distinguished Lecture (Department Colloquium) at Columbia University |
Oct 2020 |
Colloquium at CMU LTI with a recorded talk ![]() |
Oct 2020 | Colloquium at University of Maryland CLIP |
Oct 2020 | Keynote at the Amazon ML Conference 2020 |
Oct 2020 | Talk at Amazon AI |
Sep 2020 | Talk at SNU Data Science |
Aug 2020 |
Keynote at the ECCV Workshop on
Video Turing Test (VTT): Toward Human-Level Video Story Understanding
with a pre-recorded talk ![]() |
Aug 2020 |
Keynote at CIFAR Deep Learning Seminar Summer School
with a pre-recorded talk ![]() |
Jul 2020 |
ACL Tutorial on Commonsense
with a recorded talk ![]() |
Jul 2020 | Keynote at the ACL Workshop on Multimodal Language |
Jul 2020 |
Keynote at the ACL Workshop on Fact Extraction and Verification (FEVER)
with a recorded talk ![]() |
Jun 2020 |
CVPR tutorial on Neuro-Symbolic Visual Reasoning and Program Synthesis
with a recorded talk ![]() |
Jun 2020 | Keynote at the Workshop on Symbolic-Neural Learning (SNL-2020) --- cancelled until 2021 |
Apr 2020 | Panel at the ICLR Workshop on Bridging Cognitive Science and AI (BAICS) |
Feb 2020 | Keynote at the AAAI Workshop on Statistical Relational AI (StarAI) |
Dec 2019 | Keynote at the Neurips Workshop on KR2ML - Knowledge Representation and Reasoning Meets Machine Learning |
Dec 2019 | Keynote at the Neurips Workshop on Learning with Rich Experience: Integration of Learning Paradigms |
Nov 2019 | Keynote at the Natural Language, Dialog and Speech (NDS) Symposium @ the New York Academy of Sciences |
Nov 2019 | Keynote at the EMNLP Workshop on COmmonsense INference in NLP (COIN) |
Nov 2019 | Keynote at the ICCV Workshop on Extreme Vision Modeling |
Nov 2019 | Keynote at the ICCV Workshop on Scene Graph Representation and Learning |
Nov 2019 | Keynote at the ICCV Workshop on Closing the Loop Between Vision and Language (CLVL) |
Oct 2019 | Talk at UIUC + TTIC + Northwestern |
Aug 2019 | Keynote at the ACL Workshop on Conversational AI (ConvAI): "The Curious Case of Neural Conversation Degeneration" |
July 2019 | Panel at MSR Faculty Summit on the Future of Work + Keynote at KCCV |
Jun 2019 | Keynote at the NAACL Workshop onNeuralGen : "The Enigma of Neural Text Degeneration as the First Defense to Neural Fake News." |
May 2019 | Keynote at AKBC + Elemental Cognition + IBM Research: "From Atomic to Comet: Commonsense AKBC." |
July 2018 | Keynote at the ACL Workshop on Representation Learning for NLP |
July 2018 | Keynote at LxMLS Lisbon Machine Learning School |
Jun 2018 | Keynote at the CVPR Workshop on Visual Question Answering |
Jun 2018 | Keynote at the NAACL Workshop on Generalization in Deep Learning: ``Why NLU Doesn't Generalize Well to NLG.'' |
Apr 2018 |
Keynote at NW-NLP: recorded talk
![]() |
Feb 2018 | Keynote at AAAI |
Research Interests:
My primary research interests are in the fields of Natural Language Processing, Machine Learning, Artificial Intelligence,
with broader interests in Computer Vision and Digital Humanities.
Language and X ∈ {vision, knowledge, world, mind, society...} :
Intelligent communication requires the ability to read between the lines and to reason beyond what is said explicitly.
My recent research has been under two broad themes:
(i) learning the contextual, grounded meaning of language from various contexts in which language is used
— both physical (e.g., visual) and abstract (e.g., social, cognitive), and
(ii) learning the background knowledge about how the world works, latent in large-scale multimodal data.
More specifically, my research interests include:
- Language Grounding with Vision:
Learning semantic correspondences between language and vision at a very large scale,
addressing tasks such as image captioning, multimodal knowledge learning, and reasoning.
- Physical Commonsense Reasoning:
Learning naive physics type knowledge from language and other modalities; modeling action causality and entailment using frame semantic style representation.
- Social Commonsense Reasoning and Connotation Frames:
Modeling connotative implications of actions and events;
modeling why people do (intent) what they do and the (emotional) causal impact of different actions and events.
- Language Generation and Conversational AI:
Modeling the long-term context; tracking and simulating the world representend in a story or a narrative; learning to write; integrating physical and social commonsense in storytelling
- AI for Social Good:
fake review / news detection; political factchecking; identifying unwanted bias in modern films and literature
Recent Preprints:
🍔 Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing
Jaehun Jung, Peter West, Liwei Jiang, Faeze Brahman, Ximing Lu, Jillian Fisher, Taylor Sorensen, Yejin Choi
arXiv:2305.16635
Faith and Fate: Limits of Transformers on Compositionality
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, Yejin Choi
arXiv:2305.18654
🍺 Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning
Ximing Lu, Faeze Brahman, Peter West, Jaehun Jang, Khyathi Chandu, Abhilasha Ravichander, Lianhui Qin, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Yuchen Lin, Skyler Hallinan, Xiang Ren, Sean Welleck, Yejin Choi
arXiv:2305.15065
PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, Jena D. Hwang, Xiang Lorraine Li, Hirona J. Arai, Soumya Sanyal, Keisuke Sakaguchi, Xiang Ren, Yejin Choi
arXiv:2305.19472
Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models
Natalie Shapira, Mosh Levy, Seyed Hossein Alavi, Xuhui Zhou, Yejin Choi, Yoav Goldberg, Maarten Sap, Vered Shwartz
arXiv:2305.14763
Vera: A General-Purpose Plausibility Estimation Model for Commonsense Statements
Jiacheng Liu, Wenya Wang, Dianzhuo Wang, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
arXiv:2305.03695
SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks
Bill Yuchen Lin, Yicheng Fu, Karina Yang, Prithviraj Ammanabrolu, Faeze Brahman, Shiyu Huang, Chandra Bhagavatula, Yejin Choi, Xiang Ren
arXiv:2305.17390
ArK: Augmented Reality with Knowledge Interactive Emergent Ability
Qiuyuan Huang, Jae Sung Park, Abhinav Gupta, Paul Bennett, Ran Gong, Subhojit Som, Baolin Peng, Owais Khan Mohammed, Chris Pal, Yejin Choi, Jianfeng Gao
arXiv:2305.00970
We're Afraid Language Models Aren't Modeling Ambiguity
Alisa Liu, Zhaofeng Wu, Julian Michael, Alane Suhr, Peter West, Alexander Koller, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
arXiv:2304.14399
CHAMPAGNE: Learning Real-world Conversation from Large-Scale Web Videos
Seungju Han, Jack Hessel, Nouha Dziri, Yejin Choi, Youngjae Yu
arXiv:2303.09713
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text
Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, Yejin Choi
arXiv:2304.06939
SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization
Hyunwoo Kim, Jack Hessel, Liwei Jiang, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, Yejin Choi
arXiv:2212.10465
Can Machines Learn Morality? The Delphi: Experiment
Liwei Jiang, Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, Maxwell Forbes, Jon Borchardt, Jenny Liang, Oren Etzioni, Maarten Sap, Yejin Choi
arXiv.2110.07574
*Demo
RealTime QA: What's the Answer Right Now?
Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, Ronan Le Bras, Akari Asai, Xinyan Yu, Dragomir Radev, Noah A. Smith, Yejin Choi, Kentaro Inui
arXiv.2207.13332
*Project
Recent Publications (2016 - 2023):
Do Embodied Agents Dream of Pixelated Sheep?: Embodied Decision Making using Language Guided World Modelling
Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hannaneh Hajishirzi, Sameer Singh, Roy Fox
ICML 2023
Minding Language Models' (Lack of) Theory of Mind: A Plug-and-Play Multi-Character Belief Tracker
Melanie Sclar, Sachin Kumar, Peter West, Alane Suhr, Yejin Choi and Yulia Tsvetkov
ACL 2023 -- Outstanding Paper Award
Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step
Liunian Harold Li, Jack Hessel, Youngjae Yu, Xiang Ren, Kai-Wei Chang and Yejin Choi
ACL 2023
Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contest
Jack Hessel, Ana Marasović, Jena D. Hwang, Lillian Lee, Jeff Da, Rowan Zellers, Robert Mankoff, Yejin Choi
ACL 2023 -- Best Paper Award
ClarifyDelphi: Reinforced Clarification Questions with Defeasibility Rewards for Social and Moral Situations
Valentina Pyatkin, Jena D. Hwang, Vivek Srikumar, Ximing Lu, Liwei Jiang, Yejin Choi, Chandra Bhagavatula
ACL 2023
I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation
Chandra Bhagavatula, Jena D. Hwang, Doug Downey, Ronan Le Bras, Ximing Lu, Keisuke Sakaguchi, Swabha Swayamdipta, Peter West, Yejin Choi
ACL 2023
SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created through Human-Machine Collaboration
Hwaran Lee, Seokhee Hong, Joonsuk Park, Takyoung Kim, Meeyoung Cha, Yejin Choi, BYOUNGPIL KIM, Gunhee Kim, Eun-Ju Lee, Yong Lim, Alice Oh, Sangchul Park and Jung-Woo Ha
ACL 2023
An AI Dungeon Master's Guide: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons
Pei Zhou, Andrew Zhu, Jennifer Hu, Jay Pujara, Xiang Ren, Chris Callison-Burch, Yejin Choi and Prithviraj Ammanabrolu
ACL 2023
Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts
Skyler Hallinan, Alisa Liu, Yejin Choi and Maarten Sap
ACL 2023
Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-text Rationales
Brihi Joshi, Ziyi Liu, Sahana Ramnath, Aaron Chan, Zhewei Tong, Shaoliang Nie, Qifan Wang, Yejin Choi and Xiang Ren
ACL 2023
From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Models
Julia Mendelsohn, Ronan Le Bras, Yejin Choi and Maarten Sap
ACL 2023
Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generation
Kung-Hsiang Huang, Kathleen McKeown, Preslav Nakov, Yejin Choi and Heng Ji
ACL 2023
REV: Information-Theoretic Evaluation of Free-Text Rationales
Hanjie Chen, Faeze Brahman, Xiang Ren, Yangfeng Ji, Yejin Choi and Swabha Swayamdipta
ACL 2023
Commonsense Knowledge Transfer for Pre-trained Language Models
Wangchunshu Zhou, Ronan Le Bras and Yejin Choi
ACL Findings 2023
Modularized Encoder-Decoder Models for Flexible Sequence-to-Sequence Compression
Wangchunshu Zhou, Ronan Le Bras and Yejin Choi
ACL Findings 2023
Multimodal Knowledge Alignment with Reinforcement Learning
Youngjae Yu, Jiwan Chung, Heeseung Yun, Jack Hessel, Jae Sung Park, Ximing Lu, Rowan Zellers, Prithviraj Ammanabrolu, Ronan Le Bras, Gunhee Kim, Yejin Choi
CVPR 2023
Influence Diagnostics under Self-concordance
Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, and Zaid Harchaoui
AISTAT 2023
Penguins Don't Fly: Reasoning about Generics through Instantiations and Exceptions
Emily Allaway, Jena D. Hwang, Chandra Bhagavatula, Kathleen McKeown, Doug Downey, Yejin Choi
EACL 2023
Generating Sequences by Learning to [Self-]Correct
Sean Welleck*, Ximing Lu*, Peter West+, Faeze Brahman+, Tianxiao Shen, Daniel Khashabi, Yejin Choi
ICLR 2023
Is Reinforcement Learning (Not) for Natural Language Processing?: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley, Jack Hessel, Rafet Sifa, Christian Bauckhage, Hannaneh Hajishirzi, Yejin Choi
ICLR 2023
*Project
🍏 The Curious Case of Commonsense Intelligence
Yejin Choi
Daedalus's special issue on AI & Society, 2022
Quark: Controllable Text Generation with Reinforced Unlearning
Ximing Lu, Sean Welleck, Liwei Jiang, Jack Hessel, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, Yejin Choi
NeurIPS 2022
COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics
Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi
NeurIPS 2022
NaturalProver: Grounded Mathematical Proof Generation with Language Models
Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi
NeurIPS 2022
Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation
Melanie Sclar, Peter West, Sachin Kumar, Yulia Tsvetkov and Yejin Choi
EMNLP 2022
Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations
Jaehun Jung, Lianhui Qin, Sean Welleck, Faeze Brahman, Chandra Bhagavatula, Ronan Le Bras and Yejin Choi
EMNLP 2022
Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering
Jiacheng Liu, Skyler Hallinan, Ximing Lu, Pengfei He, Sean Welleck, Hannaneh Hajishirzi, Yejin Choi
EMNLP 2022
Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs
Maarten Sap, Ronan Le Bras, Daniel Fried and Yejin Choi
EMNLP 2022
ProsocialDialog: A Prosocial Backbone for Conversational Agents
Hyunwoo Kim, Youngjae Yu, Liwei Jiang, Ximing Lu, Daniel Khashabi, Gunhee Kim, Yejin Choi and Maarten Sap
EMNLP 2022
*Data
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ Tasks
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, Atharva Naik, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Maitreya Patel, Kuntal Kumar Pal, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Shailaja Keyur Sampat, Savan Doshi, Siddhartha Mishra, Sujan Reddy, Sumanta Patro, Tanay Dixit, Xudong Shen, Chitta Baral, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi and Daniel Khashabi
EMNLP 2022
*Project
Twist Decoding: Diverse Generators Guide Each Other
Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Hao Peng, Ximing Lu, Dragomir Radev, Yejin Choi, Noah A. Smith
EMNLP 2022
Toward Reproducible and Standardized Human Evaluation for Text Generation
Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith and Daniel Weld
EMNLP 2022
*Project
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation
Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
EMNLP 2022 Findings
NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation
Phillip Howard, Gadi Singer, Vasudev Lal, Yejin Choi and Swabha Swayamdipta
EMNLP 2022 Findings
NaturalAdversaries: Can Natural Adversaries Be As Effective As Artificial Adversaries?
Saadia Gabriel, Hamid Palangi and Yejin Choi
EMNLP 2022 Findings
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
ECCV 2022
Information-Theoretic Measures of Dataset Difficulty
Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta
ICML 2022 -- Outstanding Paper Award
MERLOT Reserve: Multimodal 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
CVPR 2022
*Project
Quantifying the Narrative Flow of Imagined versus Autobiographical Stories
Maarten Sap, Anna Jafarpour, Yejin Choi, Noah A. Smith, James W. Pennebaker, Eric Horvitz
PNAS 2022
It’s not Rocket Science: Interpreting Figurative Language in Narratives
Tuhin Chakrabarty , Yejin Choi and Vered Shwartz
TACL 2022
Aligning to Social Norms and Values in Interactive Narratives
Prithviraj Ammanabrolu, Liwei Jiang, Maarten Sap, Hanna Hajishirzi, Yejin Choi
NAACL 2022
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
Peter West, Chandra Bhagavatula, Jack Hessel, Jena D. Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, Yejin Choi
NAACL 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,
Lianhui Qin, Youngjae Yu, Rowan Zellers, Noah Smith, Yejin Choi
NAACL 2022 -- Best Paper Award
Promp Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts
Daniel Khashabi, Shane Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sameer Singh, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal and Yejin Choi
NAACL 2022
Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand
Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Lavinia Dunagan, Jacob Morrison, Alexander R. Fabbri, Yejin Choi, Noah A. Smith
NAACL 2022
Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection
Maarten Sap, Swabha Swayamdipta, Laura Vianna, Xuhui Zhou, Yejin Choi, Noah A. Smith
NAACL 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
NAACL 2022
Transparent Human Evaluation for Image Captioning
Jungo Kasai, Keisuke Sakaguchi, Lavinia Dunagan, Jacob Morrison, Ronan Le Bras, Yejin Choi, Noah A. Smith
NAACL 2022
Reframing Human-AI Collaboration for Generating Free-Text Explanations
Sarah Wiegreffe, Jack Hessel, Swabha Swayamdipta, Mark Riedl, Yejin Choi
NAACL 2022
Exposing the Limits of Video-Text Models through Contrast Sets
Jae Sung Park, Sheng Shen, Ali Farhadi, Trevor Darrell, Yejin Choi, Anna Rohrbach
NAACL 2022
🎃 Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text
Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, Noah A. Smith, Yejin Choi
ACL 2022
Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlines
Saadia Gabriel, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi, Yejin Choi
ACL 2022
Generated Knowledge Prompting for Commonsense Reasoning
Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, Hannaneh Hajishirzi
ACL 2022
Reframing Instructional Prompts to GPTk's Language
Swaroop Mishra, Daniel Khashabi, Chitta Baral, Yejin Choi, Hannaneh Hajishirzi
ACL 2022, Findings
Probing Factually Grounded Content Transfer with Factual Ablation
Peter West, Chris Quirk, Michel Galley, Yejin Choi
ACL 2022, Findings
Symbolic Brittleness in Sequence Models: on Systematic Generalization in Symbolic Mathematics
Sean Welleck, Peter West, Jize Cao, Yejin Choi
AAAI 2022
🍷MERLOT: Multimodal Neural Script Knowledge Models
Rowan Zellers*, Ximing Lu*, Jack Hessel*, Youngjae Yu, Jae Sung Park, Jize Cao, Ali Farhadi, Yejin Choi
NeurIPS 2021, Oral (1%)
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers
Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaid Harchaoui
NeurIPS 2021, Oral (1%) -- Outstanding Paper Award
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral
Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui
NeurIPS 2021
NaturalProofs: Mathematical Theorem Proving in Natural Language
Sean Welleck, Jiacheng Liu, Ronan Le Bras, Hannaneh Hajishirzi, Yejin Choi, Kyunghyun Cho
NeurIPS 2021 Datasets and Benchmarks Track, Oral (1%)
CommonsenseQA 2.0: Exposing the Limits of AI through Gamification
Alon Talmor, Ori Yoran, Ronan Le Bras, Chandra Bhagavatula, Yoav Goldberg, Yejin Choi, Jonathan Berant
NeurIPS 2021 Datasets and Benchmarks Track
CLIPScore: A Reference-free Evaluation Metric for Image Captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras and Yejin Choi
EMNLP 2021
Moral Stories: Learning to Reason about Norms, Intents, Actions, and their Consequences from Short Narratives
Denis Emelin, Ronan Le Bras, Jena D. Hwang, Maxwell Forbes and Yejin Choi
EMNLP 2021
Conversational Multi-hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules
Forough Arabshahi, Jennifer Lee, Antoine Bosselut, Yejin Choi and Tom Mitchell
EMNLP 2021
Contrastive Explanations for Model Interpretability
Alon Jacovi, Swabha Swayamdipta, Shauli Ravfogel, Yanai Elazar, Yejin Choi and Yoav Goldberg
EMNLP 2021
Surface Form Competition: Why the Highest Probability Answer Isn’t Always Right
Ari Holtzman*, Peter West*, Vered Shwartz, Yejin Choi and Luke Zettlemoyer
EMNLP 2021
proScript: Partially Ordered Scripts Generation
Keisuke Sakaguchi, Chandra Bhagavatula, Ronan Le Bras, Niket Tandon, Peter Clark and Yejin Choi
EMNLP Findings 2021
Analyzing Commonsense Emergence in Few-shot Knowledge Models
Jeff Da, Ronan Le Bras, Ximing Lu, Yejin Choi, Antoine Bosselut
AKBC 2021
DExperts: On-the-Fly Controlled Text Generation with Experts and Anti-Experts
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah Smith and Yejin Choi
ACL 2021
PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World
Rowan Zellers, Ari Holtzman, Matthew Peters, Roozbeh Mottaghi, Aniruddha Kembhavi, Ali Farhadi and Yejin Choi
ACL 2021
TIMEDIAL: Temporal Commonsense Reasoning in Dialog
Lianhui Qin, Aditya Gupta, Shyam Upadhyay, Luheng He, Yejin Choi and Manaal Faruqui
ACL 2021
Reflective Decoding: Beyond Unidirectional Generation with Off-the-shelf Language Models
Peter West, Ximing Lu, Ari Holtzman, Chandra Bhagavatula, Jena D. Hwang and Yejin Choi
ACL 2021
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 and Yejin Choi
ACL 2021
On-the-Fly Attention Modulation for Neural Generation
Yue Dong, Chandra Bhagavatula, Ximing Lu, Jena D. Hwang, Antoine Bosselut, Jackie Chi Kit Cheung and Yejin Choi
ACL 2021 Findings
Go Figure: A Meta Evaluation of Factuality in Summarization
Saadia Gabriel, Asli Celikyilmaz, Rahul Jha, Yejin Choi and Jianfeng Gao
ACL 2021 Findings
VinVL: Making Visual Representations Matter in Vision-Language Models
Pengchuan Zhang*, Xiujun Li*, Xiaowei Hu, Jianwei Yang, Lei Zhang, Lijuan Wang, Yejin Choi, Jianfeng Gao
CVPR 2021
TuringAdvice: A Generative and Dynamic Evaluation of Language Use
Rowan Zellers, Ari Holtzman, Elizabeth Clark, Lianhui Qin, Ali Farhadi, Yejin Choi
NAACL 2021
*Project Page
NeuroLogic Decoding: (Un)supervised Neural Text Generation with Predicate Logic Constraints
Ximing Lu, Peter West, Rowan Zellers, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
NAACL 2021
"I'm Not Mad": Commonsense Implications of Negation and Contradiction
Liwei Jiang, Antoine Bosselut, Chandra Bhagavatula, Yejin Choi
NAACL 2021
Discourse Understanding and Factual Consistency in Abstractive Summarization
Saadia Gabriel, Antoine Bosselut, Jeff Da, Ari Holtzman, Jan Buys, Kyle Lo, Asli Celikyilmaz, Yejin Choi
EACL 2021
Challenges in Automated Debiasing for Toxic Language Detection
Xuhui Zhou, Maarten Sap, Swabha Swayamdipta, Noah A. Smith, and Yejin Choi
EACL 2021
(Comet-) Atomic 2020: On Symbolic and Neural Commonsense Knowledge Graphs
Jena Hwang*, Chandra Bhagavatula*, Ronan Le Bras, Jeff Da, Keisuke Sakaguchi, Antoine Bosselut, Yejin Choi
AAAI 2021
🦄 Unicorn on Rainbow: A Universal Commonsense Reasoning Model on a New Multitask Benchmark
Nicholas Lourie, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
AAAI 2021
Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering
Antoine Bosselut, Ronan Le Bras, Yejin Choi
AAAI 2021
Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision
Faeze Brahman, Vered Shwartz, Rachel Rudinger, Yejin Choi
AAAI 2021
Paragraph-level Commonsense Transformers with Recurrent Memory
Saadia Gabriel, Chandra Bhagavatula, Vered Shwartz, Ronan Le Bras, Maxwell Forbes, Yejin Choi
AAAI 2021
MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations
Yao Dou, Maxwell Forbes, Ari Holtzman, Yejin Choi
AAAI 2021
Scruples: A Corpus of Community Ethical Judgments on 32,000 Real-Life Anecdotes
Nicholas Lourie, Ronan Le Bras, Yejin Choi
AAAI 2021
🔮 Social Chemistry 101: Learning to Reason about Social and Moral Norms
Maxwell Forbes, Jena D. Hwang, Vered Shwartz, Maarten Sap and Yejin Choi
EMNLP, 2020
Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning (DeLorean)
Lianhui Qin, Vered Shwartz, Peter West, Chandra Bhagavatula, Jena D. Hwang, Ronan Le Bras, Antoine Bosselut and Yejin Choi
EMNLP, 2020
PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction
Xinyao Ma, Maarten Sap, Hannah Rashkin and Yejin Choi
EMNLP, 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
Swabha Swayamdipta, Roy Schwartz, Nicholas Lourie, Yizhong Wang, Hannaneh Hajishirzi, Noah A. Smith and Yejin Choi
EMNLP, 2020
PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi and Jianfeng Gao
EMNLP, 2020
Unsupervised Commonsense Question Answering with Self-Talk
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
EMNLP, 2020
Thinking Like a Skeptic: Defeasible Inference in Natural Language
Rachel Rudinger, Vered Shwartz, Jena D. Hwang, Chandra Bhagavatula, Maxwell Forbes, Ronan Le Bras, Noah A. Smith and Yejin Choi
Findings of EMNLP, 2020
RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi and Noah A. Smith
Findings of EMNLP, 2020
*Demo
Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs
Ana Marasovic, Chandra Bhagavatula, Jae sung Park, Ronan Le Bras, Noah A. Smith and Yejin Choi
Findings of EMNLP, 2020
CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning
Yuchen Lin, Wangchunshu Zhou, Ming Shen, Pei Zhou, Chandra Bhagavatula, Yejin Choi, Xiang Ren
Findings of EMNLP, 2020
*Project Page
Generative Data Augmentation for Commonsense Reasoning
Yiben Yang, Chaitanya Malaviya, Jared Fernandez, Swabha Swayamdipta, Ronan Le Bras, Ji-Ping Wang, Chandra Bhagavatula, Yejin Choi and Doug Downey
Findings of EMNLP, 2020
Visual Comet: Reasoning about the Dynamic Context of a Still Image
Jae Sung Park, Chandra Bhagavatula, Roozbeh Mottaghi, Ali Farhadi, Yejin Choi
ECCV, 2020
*Project Page
Oscar: Object-Semantics Aligned Pre-training for Vision-and-Language Tasks
Xiujun Li, Xi Yin, Chunyuan Li, Pengchuan Zhang, Xiaowei Hu, Lei Zhang, Lijuan Wang, Houdong Hu, Li Dong, Furu Wei, Yejin Choi, Jianfeng Gao
ECCV, 2020
Adversarial Filters of Dataset Biases
Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi
ICML, 2020
Social Bias Frames: Reasoning about Social and Power Implications of Language
Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A Smith & Yejin Choi
ACL, 2020
*Project Page
Recollection versus Imagination: Exploring Human Memory and Cognition via Neural Language Models
Maarten Sap, Eric Horvitz, Yejin Choi, Noah A Smith & James W Pennebaker
ACL, 2020
*Project Page
Procedural Reading Comprehension with Attribute-Aware Context Flow
Aida Amini, Antoine Bosselut, Bhavana Dalvi Mishra, Yejin Choi, Hannaneh Hajishirzi
AKBC, 2020 -- best paper nomination
The Curious Case of Neural Text Degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, Yejin Choi
ICLR, 2020
Abductive Commonsense Reasoning
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Wen-tau Yih and Yejin Choi
ICLR, 2020
WinoGrande: An Adversarial Winograd Schema Challenge at Scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
AAAI, 2020 -- Outstanding Paper Award (given to the single best paper)
*Leaderboard,
Annoucement
PIQA: Reasoning about Physical Commonsense in Natural Language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, Yejin Choi
AAAI, 2020
*Leaderboard
Commonsense Knowledge Base Completion with Structural and Semantic Context
Chaitanya Malaviya, Chandra Bhagavatula, Antoine Bosselut, Yejin Choi
AAAI, 2020
Do Neural Language Models Overcome Reporting Bias?
Vered Shwartz and Yejin Choi
COLING, 2020
Defending Against Neural Fake News (Grover)
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, Yejin Choi
NeurIPS, 2019
*Blog! (with additional experiments & analysis)
*Grover Demo!
*Project Page
BottleSum: Unsupervised and Self-supervised Sentence Summarization using the Information Bottleneck Principle
Peter West, Ari Holtzman, Jan Buys and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Project Page
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning
Lifu Huang, Ronan Le Bras, Chandra Bhagavatula and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Project Page & Leaderboard
Counterfactual Story Reasoning and Generation
Lianhui Qin, Antoine Bosselut, Ari Holtzman, Chandra Bhagavatula, Elizabeth Clark and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Code & Data
Social IQa: Commonsense Reasoning about Social Interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan Le Bras and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Project Page & Leaderboard
Robust Navigation with Language Pretraining and Stochastic Sampling
Xiujun Li, Chunyuan Li, Qiaolin Xia, Yonatan Bisk, Asli Celikyilmaz, Jianfeng Gao, Noah A. Smith and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Early Fusion for Goal Directed Robotic Vision
Aaron Walsman, Yonatan Bisk, Saadia Gabriel, Dipendra Misra, Yoav Artzi, Yejin Choi, Dieter Fox
International Conference on Intelligent Robots and Systems (IROS), 2019
-- best paper nomination
Do Neural Language Representations Learn Physical Commonsense?
Maxwell Forbes, Ari Holtzman, Yejin Choi
Conference of the Cognitive Science Society (CogSci), 2019
*Project Page
COMET: Commonsense Transformers for Knowledge Graph Construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz and Yejin Choi
Association for Computational Linguistics (ACL), 2019
*Demo
Hellaswag: Can a Machine Really Finish Your Sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi and Yejin Choi
Association for Computational Linguistics (ACL), 2019
*Project Page & Leaderboard
Featured in
ZdNet:
"No, This AI can't finish your sentence"
The Risk of Racial Bias in Hate Speech Detection
Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi and Noah A. Smith
Association for Computational Linguistics (ACL), 2019
-- best paper nomination
Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading
Lianhui Qin, Michel Galley, Chris Brockett, Xiaodong Liu, Xiang Gao, Bill Dolan, Yejin Choi and Jianfeng Gao
Association for Computational Linguistics (ACL), 2019
*Code & Data
From Recognition to Cognition: Visual Commonsense Reasoning (VCR)
Rowan Zellers, Yonatan Bisk, Ali Farhadi, Yejin Choi.
Conference on Computer Vision and Pattern Recognition (CVPR), 2019
*Project Page & Leaderboard
Tactical Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation
Liyiming Ke, Xiujun Li, Yonatan Bisk, Ari Holtzman, Zhe Gan, Jingjing Liu, Jianfeng Gao,
Yejin Choi and Siddhartha Srinivasa
Conference on Computer Vision and Pattern Recognition (CVPR), 2019
*Video Demo
ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning
Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith and Yejin Choi
Association for the Advancement of Artificial Intelligence (AAAI), 2019.
*Demo at AI2,
*Project Page at UW
MathQA Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
Aida Amini, Saadia Gabriel, Shanchuan Lin, Rik Koncel-Kedziorski, Yejin Choi and Hannaneh Hajishirzi.
North American Chapter of the Association for Computational Linguistics (NAACL), 2019
*Project Page & Leaderboard
Benchmarking Hierarchical Script Knowledge
Yonatan Bisk, Jan Buys, Karl Pichotta and Yejin Choi.
North American Chapter of the Association for Computational Linguistics (NAACL), 2019
DREAM: A Challenge Dataset and Models for Dialogue-Based Reading Comprehension
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, Claire Cardie
Transactions of the Association for Computational Linguistics (TACL), 2019.
*Leaderboard
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference
Rowan Zellers, Yonatan Bisk, Roy Schwartz and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
*Project Page
*Leaderboard
QuAC: Question Answering in Context
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang and Luke Zettlemoyer
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
*Leaderboard
Neural Metaphor Detection in Context
Ge Gao, Eunsol Choi, Yejin Choi and Luke Zettlemoyer
Conference on Empirical Methods in Natural Language Processing (EMNLP), short paper, 2018.
Modeling Naive Psychology of Characters in Simple Commonsense Stories
Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight and Yejin Choi
Association for Computational Linguistics (ACL), 2018.
*Project Page (with an online dataset browser!)
Learning to Write with Cooperative Discriminators
Ari Holtzman, Jan Buys, Maxwell Forbes, Antoine Bosselut, David Golub and Yejin Choi
Association for Computational Linguistics (ACL), 2018.
Event2Mind: Commonsense Inference on Events, Intents, and Reactions
Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A. Smith and Yejin Choi
Association for Computational Linguistics (ACL), 2018.
*Project Page (with an online dataset browser!)
Ultra-Fine Entity Typing
Eunsol Choi, Omer Levy, Yejin Choi and Luke Zettlemoyer
Association for Computational Linguistics (ACL), 2018.
*Project Page
Sounding Board: A User-Centric and Content-Driven Social Chatbot
Hao Fang, Hao Cheng, Maarten Sap, Elizabeth Clark, Ari Holtzman, Yejin Choi, Noah A. Smith, and Mari Ostendorf
North American Chapter of the Association for Computational Linguistics (NAACL), demo paper, 2018.
Discourse-Aware Neural Rewards for Coherent Text Generation
Antoine Bosselut, Asli Celikyilmaz, Xiaodong He, Jianfeng Gao, Po-sen Huang, and Yejin Choi
North American Chapter of the Association for Computational Linguistics (NAACL), 2018.
Deep Communicating Agents for Abstractive Summarization
Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, and Yejin Choi
North American Chapter of the Association for Computational Linguistics (NAACL), 2018.
Neural Poetry Translation
Marjan Ghazvininejad, Yejin Choi, and Kevin Knight
North American Chapter of the Association for Computational Linguistics (NAACL), short paper, 2018.
Neural Motifs: Scene Graph Parsing with Global Context
Rowan Zellers, Mark Yatskar, Sam Thomson, and Yejin Choi
Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Simulating Action Dynamics with Neural Process Networks
Antoine Bosselut, Omer Levy, Ari Holtzman, Corin Ennis, Dieter Fox, and Yejin Choi
International Conference on Learning Representations (ICLR), 2018.
[Podcast]
Learning Interpretable Spatial Operations in a Rich 3D Blocks World
Yonatan Bisk, Kevin J. Shih, Yejin Choi, and Daniel Marcu
Association for the Advancement of Artificial Intelligence (AAAI), 2018.
Bridging HMMs and RNNs through Architectural Transformations
Jan Buys, Yonatan Bisk, Yejin Choi
IRASL workshop @ NeurIPS, 2018.
Zero-Shot Activity Recognition with Verb Attribute Induction
Rowan Zellers and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
*Project Page
Dynamic Entity Representations in Neural Language Models
Yangfeng Ji, Chenhao Tan, Sebastian Martschat, Yejin Choi and Noah A. Smith
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
Truth of Varying Shades: On Political Fact-Checking and Fake News
Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), short paper, 2017.
*Project Page
Connotation Frames of Agency and Power in Modern Films
Maarten Sap, Marcella Cindy Prasettio, Ariel Holtzman, Hannah Rashkin and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), short paper, 2017.
*Project Page
*Demo Page
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi and Luke Zettlemoyer
Association for Computational Linguistics (ACL), 2017.
*Project Page
Verb Physics: Relative Physical Knowledge of Actions and Objects
Maxwell Forbes and Yejin Choi
Association for Computational Linguistics (ACL), 2017.
*Project Page
Multilingual Connotation Frames: A Case Study on Social Media for
Targeted Sentiment Analysis and Forecast
Hannah Rashkin, Eric Bell, Yejin Choi, and Svitlana Volkova
Association for Computational Linguistics (ACL), short paper, 2017.
*Project Page
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task
Roy Schwartz, Maarten Sap, Yannis Konstas, Li Zilles, Yejin Choi and Noah A. Smith
Conference on Computational Natural Language Learning (CoNLL), 2017.
Story Cloze Task: UW NLP System
Roy Schwartz, Maarten Sap, Yannis Konstas, Li Zilles, Yejin Choi and Noah A. Smith
LSDSem 2017 shared task (Best performing system), 2017.
Globally Coherent Text Generation with Neural Checklist Models
Chloé Kiddon, Luke Zettlemoyer, and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.
Generating Topical Poetry
Marjan Ghazvininejad, Xing Shi, Yejin Choi, and Kevin Knight
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.
Connotation Frames: A Data-Driven Investigation
Hannah Rashkin, Sameer Singh, and Yejin Choi
Association for Computational Linguistics (ACL), 2016.
*Project Page
Learning Prototypical Event Structure from Photo Albums
Antoine Bosselut, Jianfu Chen, David Warren, Hannaneh Hajishirzi, and Yejin Choi
Association for Computational Linguistics (ACL), 2016.
*Project Page
Document-level Sentiment Inference with Social, Faction, and Discourse Context
Eunsol Choi, Hannah Rashkin, Luke Zettlemoyer, and Yejin Choi
Association for Computational Linguistics (ACL), 2016.
*Project Page
Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects
Hessam Bagherinezhad, Hannaneh Hajishirzi, Yejin Choi, and Ali Farhadi
Association for the Advancement of Artificial Intelligence (AAAI), 2016.
Selected Publications (2011 - 2015):
Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing
Hamid Izadinia, Fereshteh Sadeghi, Santosh Kumar Divvala, Hannaneh Hajishirzi, Yejin Choi, and Ali Farhadi
International Conference on Computer Vision (ICCV), 2015. (oral)
Mise en Place: Unsupervised Interpretation of Instructional Recipes
Chloé Kiddon, Ganesa Thandavam Ponnuraj, Luke Zettlemoyer, and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2015.
TreeTalk: Composition and Compression of Trees for Image Descriptions
Polina Kuznetsova, Vicente Ordonez, Tamara Berg, and Yejin Choi.
Transaction of Association for Computational Linguistics
(TACL), 2014. (presented at EMNLP 2014)
From Large Scale Image Categorization to Entry-Level Categories.
Vicente Ordonez, Jia Deng, Yejin Choi, Alexander C Berg, and Tamara L Berg
International Conference on Computer Vision (ICCV), 2013. -- Marr Prize (best paper award)
Connotation Lexicon: A Dash of Sentiment Beneath the Surface
Meaning.
Song Feng, Jun Seok Kang, Polina Kuznetsova, and Yejin Choi.
Association for Computational Linguistics (ACL), 2013.
*Project Page
*Data: Connotation lexicon
Featured in
Fast Company
BabyTalk: Understanding and generating simple image descriptions
Girish Kulkarni, Visruth Premraj, Vicente Ordonez, Sagnik Dhar, Siming Li, Yejin Choi, Alexander C Berg, Tamara L Berg
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.
-- Longuet Higgins Prize (test of time award) at CVPR 2021
Finding Deceptive Opinion Spam by Any Stretch of the Imagination.
Myle Ott, Yejin Choi, Claire Cardie, and Jeffrey Hancock.
Association for Computational Linguistics (ACL), 2011.
-- Test of Time Award at ACL 2021
Featured in
WNBC
News for New York (Sep 2012, 5pm news);
NHPR Radio (Sep 22, 2011);
Bloomberg
Business Week (Oct 2011);
NY Times (Aug 19, 2011);
Full List of Publications:
Recent Teaching:
CSE 599 D1 (Grad) Exploration on Language, Knowledge, and Reasoning [Winter 2023]
CSEP 517 (Professional MS) Natural Language Processing [Winter 2021]
CSE 447 (Undergrad) Natural Language Processing [Winter 2020]
CSE 517 (Grad) Natural Language Processing [Winter 2019]
CSE 481 N (Undergrad Capstone) Natural Language Processing [Spring 2018]
CSE 447 (Undergrad) Natural Language Processing [Winter 2018]
CSE 481 N (Undergrad Capstone) Natural Language Processing [Spring 2017]
CSE 517 (Grad) Natural Language Processing [Winter 2017]
CSE 490 U (Undergrad) Natural Language Processing [Spring 2016]
CSEP 517 (Professional MS) Natural Language Processing [Autumn 2015]
CSE 599 (Grad) Advanced NLP [Spring 2015]
CSE 517 (Grad) Natural Language Processing [Winter 2015]
xlab:
- Current members:
Post Doc:
Sean Welleck (Postdoc/Young Investigator @ UW/AI2-> ✨starting his tenure-track at CMU in Jan 2024)
Lianhui (Karen) Qin (Young Investigator @ AI2 -> ✨starting her tenure-track at UCSD in 2024)
Yuntian Deng (Young Investigator @ AI2 -> ✨starting his tenure-track at Waterloo in 2024)
Fatemeh (Niloofar) Mireshghallah (Postdoc @ UW) - co-advised with Yulia Tsvetkov
Tianxiao Shen (Postdoc @ UW) - co-advised with Zaid Harchaoui
Abhilasha Ravichander (Young Investigator @ AI2)
Faeze Brahman (Young Investigator @ AI2)
Valentina Pyatkin (Young Investigator @ AI2)
Hyunwoo Kim (Young Investigator @ AI2)
PhD:
Peter West
Xiujun Li
Jae Sung (James) Park - co-advised with Ali Farhadi
Liwei Jiang
Alisa Liu - co-advised with Noah Smith
Jiacheng (Gary) Liu - co-advised with Hannaneh Hajishirzi
Jillian Fisher - co-advised with Zaid Harchaoui
Melanie Sclar - co-advised with Yulia Tsvetkov
Jaehun Jung
Taylor Sorensen
Ximing (Gloria) Lu
Ben Newman
Anas Awadalla - co-advised with Ludwig Schmidt
Linjie (Lidsey) Li
Undergrad:
Kavel Rao
- Former members:
Post Doc:
Nouha Dziri (-> Research Scientist @ AI2)
Yuchen (Bill) Lin (-> Research Scientist @ AI2)
Prithviraj Ammanabrolu (-> Assistant Professor at UCSD after a gap year at MosaicML)
Alane Suhr (-> Assistant Professor @ UC Berkeley)
Xiang Lorraine Li (-> Assistant Professor @ University of Pittsburgh)
Youngjae Yu (-> Assistant Professor @ Yonsei University)
Daniel Khashabi (-> Assistant Professor @ JHU)
Swabha Swayamdipta (-> Assistant Professor @ USC)
Vered Shwartz (-> Assistant Professor @ UBC)
Jack Hessel (-> Research Scientist @ AI2)
Rachel Rudinger (-> Assistant Professor @ University of Maryland)
Yonatan Bisk (-> Assistant Professor @ CMU LTI/Robotics)
Jan Buys (-> Assistant Professor @ University of Cape Town)
Yannis Konstas (-> Assistant Professor @ Heriot-Watt University)
PhD:
Saadia Gabriel (->Assistant Professor @ UCLA after a gap year at MIT and NYU)
Maarten Sap (-> Assistant Professor at CMU)
Rowan Zellers (-> OpenAI)
Maxwell Forbes (-> Wandering around the world)
Antoine Bosselut (-> Assistant Professor @ EPFL)
Hannah Rashkin (-> Research Scientist @ Google Research)
Eunsol Choi (-> Assistant Professor @ Texas Austin)
Chloé Kiddon (-> Google)
Jun Seok Kang (-> Blink Health)
Song Feng (-> Research Staff Member @ IBM Research)
Polina Kuznetsova (-> Research Scientist @ Facebook)
Ritwik Banerjee (-> Research Assistant Professor @ Stony Brook University)
Undergrad:
Jenny Liang (-> PYI @ AI2 -> PhD @ CMU)
Jeff Da (-> PYI @ AI2)
Yao Dou (-> PhD @ GaTech)
Xinyao (Michelle) Ma (-> Pinterest)
Ge Gao (-> PhD @ Cornell)
Emily Louise Allaway (-> PhD @ Columbia)
Marcella Cindy Prasetio (-> MS @ Stanford)
Ryan Benmalek (-> PhD @ Cornell)
Pooja Sethi (-> Facebook)
Short Bio:
Yejin Choi is Wissner-Slivka Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and also a senior research director at AI2 overseeing the project Mosaic. Her research investigates a wide variety problems across NLP and AI including commonsense knowledge and reasoning, neural language (de-)generation, language grounding with vision and experience, and AI for social good. She is a MacArthur Fellow and a co-recipient of the NAACL Best Paper Award in 2022, the ICML Outstanding Paper Award in 2022, the ACL Test of Time award in 2021, the CVPR Longuet-Higgins Prize (test of time award) in 2021, the NeurIPS Outstanding Paper Award in 2021, the AAAI Outstanding Paper Award in 2020, the Borg Early Career Award (BECA) in 2018, the inaugural Alexa Prize Challenge in 2017, IEEE AI's 10 to Watch in 2016, and the ICCV Marr Prize (best paper award) in 2013. She received her Ph.D. in Computer Science at Cornell University and BS in Computer Science and Engineering at Seoul National University in Korea.
Personal:
Scuba!
Jaehun Jung, Peter West, Liwei Jiang, Faeze Brahman, Ximing Lu, Jillian Fisher, Taylor Sorensen, Yejin Choi
arXiv:2305.16635
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, Yejin Choi
arXiv:2305.18654
Ximing Lu, Faeze Brahman, Peter West, Jaehun Jang, Khyathi Chandu, Abhilasha Ravichander, Lianhui Qin, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Yuchen Lin, Skyler Hallinan, Xiang Ren, Sean Welleck, Yejin Choi
arXiv:2305.15065
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, Jena D. Hwang, Xiang Lorraine Li, Hirona J. Arai, Soumya Sanyal, Keisuke Sakaguchi, Xiang Ren, Yejin Choi
arXiv:2305.19472
Natalie Shapira, Mosh Levy, Seyed Hossein Alavi, Xuhui Zhou, Yejin Choi, Yoav Goldberg, Maarten Sap, Vered Shwartz
arXiv:2305.14763
Jiacheng Liu, Wenya Wang, Dianzhuo Wang, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
arXiv:2305.03695
Bill Yuchen Lin, Yicheng Fu, Karina Yang, Prithviraj Ammanabrolu, Faeze Brahman, Shiyu Huang, Chandra Bhagavatula, Yejin Choi, Xiang Ren
arXiv:2305.17390
Qiuyuan Huang, Jae Sung Park, Abhinav Gupta, Paul Bennett, Ran Gong, Subhojit Som, Baolin Peng, Owais Khan Mohammed, Chris Pal, Yejin Choi, Jianfeng Gao
arXiv:2305.00970
Alisa Liu, Zhaofeng Wu, Julian Michael, Alane Suhr, Peter West, Alexander Koller, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
arXiv:2304.14399
Seungju Han, Jack Hessel, Nouha Dziri, Yejin Choi, Youngjae Yu
arXiv:2303.09713
Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, Yejin Choi
arXiv:2304.06939
Hyunwoo Kim, Jack Hessel, Liwei Jiang, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, Yejin Choi
arXiv:2212.10465
Liwei Jiang, Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, Maxwell Forbes, Jon Borchardt, Jenny Liang, Oren Etzioni, Maarten Sap, Yejin Choi
arXiv.2110.07574
*Demo
Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, Ronan Le Bras, Akari Asai, Xinyan Yu, Dragomir Radev, Noah A. Smith, Yejin Choi, Kentaro Inui
arXiv.2207.13332
*Project
Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hannaneh Hajishirzi, Sameer Singh, Roy Fox
ICML 2023
Melanie Sclar, Sachin Kumar, Peter West, Alane Suhr, Yejin Choi and Yulia Tsvetkov
ACL 2023 -- Outstanding Paper Award
Liunian Harold Li, Jack Hessel, Youngjae Yu, Xiang Ren, Kai-Wei Chang and Yejin Choi
ACL 2023
Jack Hessel, Ana Marasović, Jena D. Hwang, Lillian Lee, Jeff Da, Rowan Zellers, Robert Mankoff, Yejin Choi
ACL 2023 -- Best Paper Award
Valentina Pyatkin, Jena D. Hwang, Vivek Srikumar, Ximing Lu, Liwei Jiang, Yejin Choi, Chandra Bhagavatula
ACL 2023
Chandra Bhagavatula, Jena D. Hwang, Doug Downey, Ronan Le Bras, Ximing Lu, Keisuke Sakaguchi, Swabha Swayamdipta, Peter West, Yejin Choi
ACL 2023
Hwaran Lee, Seokhee Hong, Joonsuk Park, Takyoung Kim, Meeyoung Cha, Yejin Choi, BYOUNGPIL KIM, Gunhee Kim, Eun-Ju Lee, Yong Lim, Alice Oh, Sangchul Park and Jung-Woo Ha
ACL 2023
Pei Zhou, Andrew Zhu, Jennifer Hu, Jay Pujara, Xiang Ren, Chris Callison-Burch, Yejin Choi and Prithviraj Ammanabrolu
ACL 2023
Skyler Hallinan, Alisa Liu, Yejin Choi and Maarten Sap
ACL 2023
Brihi Joshi, Ziyi Liu, Sahana Ramnath, Aaron Chan, Zhewei Tong, Shaoliang Nie, Qifan Wang, Yejin Choi and Xiang Ren
ACL 2023
Julia Mendelsohn, Ronan Le Bras, Yejin Choi and Maarten Sap
ACL 2023
Kung-Hsiang Huang, Kathleen McKeown, Preslav Nakov, Yejin Choi and Heng Ji
ACL 2023
Hanjie Chen, Faeze Brahman, Xiang Ren, Yangfeng Ji, Yejin Choi and Swabha Swayamdipta
ACL 2023
Wangchunshu Zhou, Ronan Le Bras and Yejin Choi
ACL Findings 2023
Wangchunshu Zhou, Ronan Le Bras and Yejin Choi
ACL Findings 2023
Youngjae Yu, Jiwan Chung, Heeseung Yun, Jack Hessel, Jae Sung Park, Ximing Lu, Rowan Zellers, Prithviraj Ammanabrolu, Ronan Le Bras, Gunhee Kim, Yejin Choi
CVPR 2023
Jillian Fisher, Lang Liu, Krishna Pillutla, Yejin Choi, and Zaid Harchaoui
AISTAT 2023
Emily Allaway, Jena D. Hwang, Chandra Bhagavatula, Kathleen McKeown, Doug Downey, Yejin Choi
EACL 2023
Sean Welleck*, Ximing Lu*, Peter West+, Faeze Brahman+, Tianxiao Shen, Daniel Khashabi, Yejin Choi
ICLR 2023
Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley, Jack Hessel, Rafet Sifa, Christian Bauckhage, Hannaneh Hajishirzi, Yejin Choi
ICLR 2023
*Project
Yejin Choi
Daedalus's special issue on AI & Society, 2022
Ximing Lu, Sean Welleck, Liwei Jiang, Jack Hessel, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, Yejin Choi
NeurIPS 2022
Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi
NeurIPS 2022
Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi
NeurIPS 2022
Melanie Sclar, Peter West, Sachin Kumar, Yulia Tsvetkov and Yejin Choi
EMNLP 2022
Jaehun Jung, Lianhui Qin, Sean Welleck, Faeze Brahman, Chandra Bhagavatula, Ronan Le Bras and Yejin Choi
EMNLP 2022
Jiacheng Liu, Skyler Hallinan, Ximing Lu, Pengfei He, Sean Welleck, Hannaneh Hajishirzi, Yejin Choi
EMNLP 2022
Maarten Sap, Ronan Le Bras, Daniel Fried and Yejin Choi
EMNLP 2022
Hyunwoo Kim, Youngjae Yu, Liwei Jiang, Ximing Lu, Daniel Khashabi, Gunhee Kim, Yejin Choi and Maarten Sap
EMNLP 2022
*Data
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, Atharva Naik, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Maitreya Patel, Kuntal Kumar Pal, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Shailaja Keyur Sampat, Savan Doshi, Siddhartha Mishra, Sujan Reddy, Sumanta Patro, Tanay Dixit, Xudong Shen, Chitta Baral, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi and Daniel Khashabi
EMNLP 2022
*Project
Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Hao Peng, Ximing Lu, Dragomir Radev, Yejin Choi, Noah A. Smith
EMNLP 2022
Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith and Daniel Weld
EMNLP 2022
*Project
Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
EMNLP 2022 Findings
Phillip Howard, Gadi Singer, Vasudev Lal, Yejin Choi and Swabha Swayamdipta
EMNLP 2022 Findings
Saadia Gabriel, Hamid Palangi and Yejin Choi
EMNLP 2022 Findings
Jack Hessel, Jena D. Hwang, Jae Sung Park, Rowan Zellers, Chandra Bhagavatula, Anna Rohrbach, Kate Saenko, Yejin Choi
ECCV 2022
Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta
ICML 2022 -- Outstanding Paper Award
Rowan Zellers, Jiasen Lu, Ximing Lu, Youngjae Yu, Yanpeng Zhao, Mohammadreza Salehi, Aditya Kusupati, Jack Hessel, Ali Farhadi, Yejin Choi
CVPR 2022
*Project
Maarten Sap, Anna Jafarpour, Yejin Choi, Noah A. Smith, James W. Pennebaker, Eric Horvitz
PNAS 2022
Tuhin Chakrabarty , Yejin Choi and Vered Shwartz
TACL 2022
Prithviraj Ammanabrolu, Liwei Jiang, Maarten Sap, Hanna Hajishirzi, Yejin Choi
NAACL 2022
Peter West, Chandra Bhagavatula, Jack Hessel, Jena D. Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, Yejin Choi
NAACL 2022
Ximing Lu, *Sean Welleck, *Peter West, Liwei Jiang, Jungo Kasai, Daniel Khashabi, Ronan Le Bras, Lianhui Qin, Youngjae Yu, Rowan Zellers, Noah Smith, Yejin Choi
NAACL 2022 -- Best Paper Award
Daniel Khashabi, Shane Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sameer Singh, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal and Yejin Choi
NAACL 2022
Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Lavinia Dunagan, Jacob Morrison, Alexander R. Fabbri, Yejin Choi, Noah A. Smith
NAACL 2022
Maarten Sap, Swabha Swayamdipta, Laura Vianna, Xuhui Zhou, Yejin Choi, Noah A. Smith
NAACL 2022
Yanpeng Zhao, Jack Hessel, Youngjae Yu, Ximing Lu, Rowan Zellers, Yejin Choi
NAACL 2022
Jungo Kasai, Keisuke Sakaguchi, Lavinia Dunagan, Jacob Morrison, Ronan Le Bras, Yejin Choi, Noah A. Smith
NAACL 2022
Sarah Wiegreffe, Jack Hessel, Swabha Swayamdipta, Mark Riedl, Yejin Choi
NAACL 2022
Jae Sung Park, Sheng Shen, Ali Farhadi, Trevor Darrell, Yejin Choi, Anna Rohrbach
NAACL 2022
Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, Noah A. Smith, Yejin Choi
ACL 2022
Saadia Gabriel, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi, Yejin Choi
ACL 2022
Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, Hannaneh Hajishirzi
ACL 2022
Swaroop Mishra, Daniel Khashabi, Chitta Baral, Yejin Choi, Hannaneh Hajishirzi
ACL 2022, Findings
Peter West, Chris Quirk, Michel Galley, Yejin Choi
ACL 2022, Findings
Sean Welleck, Peter West, Jize Cao, Yejin Choi
AAAI 2022
Rowan Zellers*, Ximing Lu*, Jack Hessel*, Youngjae Yu, Jae Sung Park, Jize Cao, Ali Farhadi, Yejin Choi
NeurIPS 2021, Oral (1%)
Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaid Harchaoui
NeurIPS 2021, Oral (1%) -- Outstanding Paper Award
Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui
NeurIPS 2021
Sean Welleck, Jiacheng Liu, Ronan Le Bras, Hannaneh Hajishirzi, Yejin Choi, Kyunghyun Cho
NeurIPS 2021 Datasets and Benchmarks Track, Oral (1%)
Alon Talmor, Ori Yoran, Ronan Le Bras, Chandra Bhagavatula, Yoav Goldberg, Yejin Choi, Jonathan Berant
NeurIPS 2021 Datasets and Benchmarks Track
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras and Yejin Choi
EMNLP 2021
Denis Emelin, Ronan Le Bras, Jena D. Hwang, Maxwell Forbes and Yejin Choi
EMNLP 2021
Forough Arabshahi, Jennifer Lee, Antoine Bosselut, Yejin Choi and Tom Mitchell
EMNLP 2021
Alon Jacovi, Swabha Swayamdipta, Shauli Ravfogel, Yanai Elazar, Yejin Choi and Yoav Goldberg
EMNLP 2021
Ari Holtzman*, Peter West*, Vered Shwartz, Yejin Choi and Luke Zettlemoyer
EMNLP 2021
Keisuke Sakaguchi, Chandra Bhagavatula, Ronan Le Bras, Niket Tandon, Peter Clark and Yejin Choi
EMNLP Findings 2021
Jeff Da, Ronan Le Bras, Ximing Lu, Yejin Choi, Antoine Bosselut
AKBC 2021
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah Smith and Yejin Choi
ACL 2021
Rowan Zellers, Ari Holtzman, Matthew Peters, Roozbeh Mottaghi, Aniruddha Kembhavi, Ali Farhadi and Yejin Choi
ACL 2021
Lianhui Qin, Aditya Gupta, Shyam Upadhyay, Luheng He, Yejin Choi and Manaal Faruqui
ACL 2021
Peter West, Ximing Lu, Ari Holtzman, Chandra Bhagavatula, Jena D. Hwang and Yejin Choi
ACL 2021
Jeff Da, Maxwell Forbes, Rowan Zellers, Anthony Zheng, Jena D. Hwang, Antoine Bosselut and Yejin Choi
ACL 2021
Yue Dong, Chandra Bhagavatula, Ximing Lu, Jena D. Hwang, Antoine Bosselut, Jackie Chi Kit Cheung and Yejin Choi
ACL 2021 Findings
Saadia Gabriel, Asli Celikyilmaz, Rahul Jha, Yejin Choi and Jianfeng Gao
ACL 2021 Findings
Pengchuan Zhang*, Xiujun Li*, Xiaowei Hu, Jianwei Yang, Lei Zhang, Lijuan Wang, Yejin Choi, Jianfeng Gao
CVPR 2021
Rowan Zellers, Ari Holtzman, Elizabeth Clark, Lianhui Qin, Ali Farhadi, Yejin Choi
NAACL 2021
*Project Page
Ximing Lu, Peter West, Rowan Zellers, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
NAACL 2021
Liwei Jiang, Antoine Bosselut, Chandra Bhagavatula, Yejin Choi
NAACL 2021
Saadia Gabriel, Antoine Bosselut, Jeff Da, Ari Holtzman, Jan Buys, Kyle Lo, Asli Celikyilmaz, Yejin Choi
EACL 2021
Xuhui Zhou, Maarten Sap, Swabha Swayamdipta, Noah A. Smith, and Yejin Choi
EACL 2021
Jena Hwang*, Chandra Bhagavatula*, Ronan Le Bras, Jeff Da, Keisuke Sakaguchi, Antoine Bosselut, Yejin Choi
AAAI 2021
Nicholas Lourie, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
AAAI 2021
Antoine Bosselut, Ronan Le Bras, Yejin Choi
AAAI 2021
Faeze Brahman, Vered Shwartz, Rachel Rudinger, Yejin Choi
AAAI 2021
Saadia Gabriel, Chandra Bhagavatula, Vered Shwartz, Ronan Le Bras, Maxwell Forbes, Yejin Choi
AAAI 2021
Yao Dou, Maxwell Forbes, Ari Holtzman, Yejin Choi
AAAI 2021
Nicholas Lourie, Ronan Le Bras, Yejin Choi
AAAI 2021
Maxwell Forbes, Jena D. Hwang, Vered Shwartz, Maarten Sap and Yejin Choi
EMNLP, 2020
Lianhui Qin, Vered Shwartz, Peter West, Chandra Bhagavatula, Jena D. Hwang, Ronan Le Bras, Antoine Bosselut and Yejin Choi
EMNLP, 2020
Xinyao Ma, Maarten Sap, Hannah Rashkin and Yejin Choi
EMNLP, 2020
Swabha Swayamdipta, Roy Schwartz, Nicholas Lourie, Yizhong Wang, Hannaneh Hajishirzi, Noah A. Smith and Yejin Choi
EMNLP, 2020
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi and Jianfeng Gao
EMNLP, 2020
Vered Shwartz, Peter West, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
EMNLP, 2020
Rachel Rudinger, Vered Shwartz, Jena D. Hwang, Chandra Bhagavatula, Maxwell Forbes, Ronan Le Bras, Noah A. Smith and Yejin Choi
Findings of EMNLP, 2020
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi and Noah A. Smith
Findings of EMNLP, 2020
*Demo
Ana Marasovic, Chandra Bhagavatula, Jae sung Park, Ronan Le Bras, Noah A. Smith and Yejin Choi
Findings of EMNLP, 2020
Yuchen Lin, Wangchunshu Zhou, Ming Shen, Pei Zhou, Chandra Bhagavatula, Yejin Choi, Xiang Ren
Findings of EMNLP, 2020
*Project Page
Yiben Yang, Chaitanya Malaviya, Jared Fernandez, Swabha Swayamdipta, Ronan Le Bras, Ji-Ping Wang, Chandra Bhagavatula, Yejin Choi and Doug Downey
Findings of EMNLP, 2020
Jae Sung Park, Chandra Bhagavatula, Roozbeh Mottaghi, Ali Farhadi, Yejin Choi
ECCV, 2020
*Project Page
Xiujun Li, Xi Yin, Chunyuan Li, Pengchuan Zhang, Xiaowei Hu, Lei Zhang, Lijuan Wang, Houdong Hu, Li Dong, Furu Wei, Yejin Choi, Jianfeng Gao
ECCV, 2020
Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi
ICML, 2020
Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A Smith & Yejin Choi
ACL, 2020
*Project Page
Maarten Sap, Eric Horvitz, Yejin Choi, Noah A Smith & James W Pennebaker
ACL, 2020
*Project Page
Aida Amini, Antoine Bosselut, Bhavana Dalvi Mishra, Yejin Choi, Hannaneh Hajishirzi
AKBC, 2020 -- best paper nomination
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, Yejin Choi
ICLR, 2020
Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Wen-tau Yih and Yejin Choi
ICLR, 2020
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi
AAAI, 2020 -- Outstanding Paper Award (given to the single best paper)
*Leaderboard, Annoucement
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, Yejin Choi
AAAI, 2020
*Leaderboard
Chaitanya Malaviya, Chandra Bhagavatula, Antoine Bosselut, Yejin Choi
AAAI, 2020
Vered Shwartz and Yejin Choi
COLING, 2020
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, Yejin Choi
NeurIPS, 2019
*Blog! (with additional experiments & analysis)
*Grover Demo!
*Project Page
Peter West, Ari Holtzman, Jan Buys and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Project Page
Lifu Huang, Ronan Le Bras, Chandra Bhagavatula and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Project Page & Leaderboard
Lianhui Qin, Antoine Bosselut, Ari Holtzman, Chandra Bhagavatula, Elizabeth Clark and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Code & Data
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan Le Bras and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
*Project Page & Leaderboard
Xiujun Li, Chunyuan Li, Qiaolin Xia, Yonatan Bisk, Asli Celikyilmaz, Jianfeng Gao, Noah A. Smith and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Aaron Walsman, Yonatan Bisk, Saadia Gabriel, Dipendra Misra, Yoav Artzi, Yejin Choi, Dieter Fox
International Conference on Intelligent Robots and Systems (IROS), 2019 -- best paper nomination
Maxwell Forbes, Ari Holtzman, Yejin Choi
Conference of the Cognitive Science Society (CogSci), 2019
*Project Page
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz and Yejin Choi
Association for Computational Linguistics (ACL), 2019
*Demo
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi and Yejin Choi
Association for Computational Linguistics (ACL), 2019
*Project Page & Leaderboard

Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi and Noah A. Smith
Association for Computational Linguistics (ACL), 2019 -- best paper nomination
Lianhui Qin, Michel Galley, Chris Brockett, Xiaodong Liu, Xiang Gao, Bill Dolan, Yejin Choi and Jianfeng Gao
Association for Computational Linguistics (ACL), 2019
*Code & Data
Rowan Zellers, Yonatan Bisk, Ali Farhadi, Yejin Choi.
Conference on Computer Vision and Pattern Recognition (CVPR), 2019
*Project Page & Leaderboard
Liyiming Ke, Xiujun Li, Yonatan Bisk, Ari Holtzman, Zhe Gan, Jingjing Liu, Jianfeng Gao, Yejin Choi and Siddhartha Srinivasa
Conference on Computer Vision and Pattern Recognition (CVPR), 2019
*Video Demo
Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith and Yejin Choi
Association for the Advancement of Artificial Intelligence (AAAI), 2019.
*Demo at AI2, *Project Page at UW
Aida Amini, Saadia Gabriel, Shanchuan Lin, Rik Koncel-Kedziorski, Yejin Choi and Hannaneh Hajishirzi.
North American Chapter of the Association for Computational Linguistics (NAACL), 2019
*Project Page & Leaderboard
Yonatan Bisk, Jan Buys, Karl Pichotta and Yejin Choi.
North American Chapter of the Association for Computational Linguistics (NAACL), 2019
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, Claire Cardie
Transactions of the Association for Computational Linguistics (TACL), 2019.
*Leaderboard
Rowan Zellers, Yonatan Bisk, Roy Schwartz and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
*Project Page *Leaderboard
Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang and Luke Zettlemoyer
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
*Leaderboard
Ge Gao, Eunsol Choi, Yejin Choi and Luke Zettlemoyer
Conference on Empirical Methods in Natural Language Processing (EMNLP), short paper, 2018.
Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight and Yejin Choi
Association for Computational Linguistics (ACL), 2018.
*Project Page (with an online dataset browser!)
Ari Holtzman, Jan Buys, Maxwell Forbes, Antoine Bosselut, David Golub and Yejin Choi
Association for Computational Linguistics (ACL), 2018.
Hannah Rashkin, Maarten Sap, Emily Allaway, Noah A. Smith and Yejin Choi
Association for Computational Linguistics (ACL), 2018.
*Project Page (with an online dataset browser!)
Eunsol Choi, Omer Levy, Yejin Choi and Luke Zettlemoyer
Association for Computational Linguistics (ACL), 2018.
*Project Page
Hao Fang, Hao Cheng, Maarten Sap, Elizabeth Clark, Ari Holtzman, Yejin Choi, Noah A. Smith, and Mari Ostendorf
North American Chapter of the Association for Computational Linguistics (NAACL), demo paper, 2018.
Antoine Bosselut, Asli Celikyilmaz, Xiaodong He, Jianfeng Gao, Po-sen Huang, and Yejin Choi
North American Chapter of the Association for Computational Linguistics (NAACL), 2018.
Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, and Yejin Choi
North American Chapter of the Association for Computational Linguistics (NAACL), 2018.
Marjan Ghazvininejad, Yejin Choi, and Kevin Knight
North American Chapter of the Association for Computational Linguistics (NAACL), short paper, 2018.
Rowan Zellers, Mark Yatskar, Sam Thomson, and Yejin Choi
Conference on Computer Vision and Pattern Recognition (CVPR), 2018
Antoine Bosselut, Omer Levy, Ari Holtzman, Corin Ennis, Dieter Fox, and Yejin Choi
International Conference on Learning Representations (ICLR), 2018.
[Podcast]
Yonatan Bisk, Kevin J. Shih, Yejin Choi, and Daniel Marcu
Association for the Advancement of Artificial Intelligence (AAAI), 2018.
Jan Buys, Yonatan Bisk, Yejin Choi
IRASL workshop @ NeurIPS, 2018.
Rowan Zellers and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
*Project Page
Yangfeng Ji, Chenhao Tan, Sebastian Martschat, Yejin Choi and Noah A. Smith
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), short paper, 2017.
*Project Page
Maarten Sap, Marcella Cindy Prasettio, Ariel Holtzman, Hannah Rashkin and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), short paper, 2017.
*Project Page *Demo Page
Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi and Luke Zettlemoyer
Association for Computational Linguistics (ACL), 2017.
*Project Page
Maxwell Forbes and Yejin Choi
Association for Computational Linguistics (ACL), 2017.
*Project Page
Hannah Rashkin, Eric Bell, Yejin Choi, and Svitlana Volkova
Association for Computational Linguistics (ACL), short paper, 2017.
*Project Page
Roy Schwartz, Maarten Sap, Yannis Konstas, Li Zilles, Yejin Choi and Noah A. Smith
Conference on Computational Natural Language Learning (CoNLL), 2017.
Roy Schwartz, Maarten Sap, Yannis Konstas, Li Zilles, Yejin Choi and Noah A. Smith
LSDSem 2017 shared task (Best performing system), 2017.
Chloé Kiddon, Luke Zettlemoyer, and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.
Marjan Ghazvininejad, Xing Shi, Yejin Choi, and Kevin Knight
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2016.
Hannah Rashkin, Sameer Singh, and Yejin Choi
Association for Computational Linguistics (ACL), 2016.
*Project Page
Antoine Bosselut, Jianfu Chen, David Warren, Hannaneh Hajishirzi, and Yejin Choi
Association for Computational Linguistics (ACL), 2016.
*Project Page
Eunsol Choi, Hannah Rashkin, Luke Zettlemoyer, and Yejin Choi
Association for Computational Linguistics (ACL), 2016.
*Project Page
Hessam Bagherinezhad, Hannaneh Hajishirzi, Yejin Choi, and Ali Farhadi
Association for the Advancement of Artificial Intelligence (AAAI), 2016.
Hamid Izadinia, Fereshteh Sadeghi, Santosh Kumar Divvala, Hannaneh Hajishirzi, Yejin Choi, and Ali Farhadi
International Conference on Computer Vision (ICCV), 2015. (oral)
Chloé Kiddon, Ganesa Thandavam Ponnuraj, Luke Zettlemoyer, and Yejin Choi
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2015.
Polina Kuznetsova, Vicente Ordonez, Tamara Berg, and Yejin Choi.
Transaction of Association for Computational Linguistics (TACL), 2014. (presented at EMNLP 2014)
Vicente Ordonez, Jia Deng, Yejin Choi, Alexander C Berg, and Tamara L Berg
International Conference on Computer Vision (ICCV), 2013. -- Marr Prize (best paper award)
Song Feng, Jun Seok Kang, Polina Kuznetsova, and Yejin Choi.
Association for Computational Linguistics (ACL), 2013.
*Project Page *Data: Connotation lexicon

Girish Kulkarni, Visruth Premraj, Vicente Ordonez, Sagnik Dhar, Siming Li, Yejin Choi, Alexander C Berg, Tamara L Berg
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. -- Longuet Higgins Prize (test of time award) at CVPR 2021
Myle Ott, Yejin Choi, Claire Cardie, and Jeffrey Hancock.
Association for Computational Linguistics (ACL), 2011. -- Test of Time Award at ACL 2021

Full List of Publications:
Recent Teaching:
CSE 599 D1 (Grad) Exploration on Language, Knowledge, and Reasoning [Winter 2023]
CSEP 517 (Professional MS) Natural Language Processing [Winter 2021]
CSE 447 (Undergrad) Natural Language Processing [Winter 2020]
CSE 517 (Grad) Natural Language Processing [Winter 2019]
CSE 481 N (Undergrad Capstone) Natural Language Processing [Spring 2018]
CSE 447 (Undergrad) Natural Language Processing [Winter 2018]
CSE 481 N (Undergrad Capstone) Natural Language Processing [Spring 2017]
CSE 517 (Grad) Natural Language Processing [Winter 2017]
CSE 490 U (Undergrad) Natural Language Processing [Spring 2016]
CSEP 517 (Professional MS) Natural Language Processing [Autumn 2015]
CSE 599 (Grad) Advanced NLP [Spring 2015]
CSE 517 (Grad) Natural Language Processing [Winter 2015]
xlab:
- Current members:
Post Doc:
Sean Welleck (Postdoc/Young Investigator @ UW/AI2-> ✨starting his tenure-track at CMU in Jan 2024)
Lianhui (Karen) Qin (Young Investigator @ AI2 -> ✨starting her tenure-track at UCSD in 2024)
Yuntian Deng (Young Investigator @ AI2 -> ✨starting his tenure-track at Waterloo in 2024)
Fatemeh (Niloofar) Mireshghallah (Postdoc @ UW) - co-advised with Yulia Tsvetkov
Tianxiao Shen (Postdoc @ UW) - co-advised with Zaid Harchaoui
Abhilasha Ravichander (Young Investigator @ AI2)
Faeze Brahman (Young Investigator @ AI2)
Valentina Pyatkin (Young Investigator @ AI2)
Hyunwoo Kim (Young Investigator @ AI2)
PhD:
Peter West
Xiujun Li
Jae Sung (James) Park - co-advised with Ali Farhadi
Liwei Jiang
Alisa Liu - co-advised with Noah Smith
Jiacheng (Gary) Liu - co-advised with Hannaneh Hajishirzi
Jillian Fisher - co-advised with Zaid Harchaoui
Melanie Sclar - co-advised with Yulia Tsvetkov
Jaehun Jung
Taylor Sorensen
Ximing (Gloria) Lu
Ben Newman
Anas Awadalla - co-advised with Ludwig Schmidt
Linjie (Lidsey) Li
Undergrad:
Kavel Rao
- Former members:
Post Doc:
Nouha Dziri (-> Research Scientist @ AI2)
Yuchen (Bill) Lin (-> Research Scientist @ AI2)
Prithviraj Ammanabrolu (-> Assistant Professor at UCSD after a gap year at MosaicML)
Alane Suhr (-> Assistant Professor @ UC Berkeley)
Xiang Lorraine Li (-> Assistant Professor @ University of Pittsburgh)
Youngjae Yu (-> Assistant Professor @ Yonsei University)
Daniel Khashabi (-> Assistant Professor @ JHU)
Swabha Swayamdipta (-> Assistant Professor @ USC)
Vered Shwartz (-> Assistant Professor @ UBC)
Jack Hessel (-> Research Scientist @ AI2)
Rachel Rudinger (-> Assistant Professor @ University of Maryland)
Yonatan Bisk (-> Assistant Professor @ CMU LTI/Robotics)
Jan Buys (-> Assistant Professor @ University of Cape Town)
Yannis Konstas (-> Assistant Professor @ Heriot-Watt University)
PhD:
Saadia Gabriel (->Assistant Professor @ UCLA after a gap year at MIT and NYU)
Maarten Sap (-> Assistant Professor at CMU)
Rowan Zellers (-> OpenAI)
Maxwell Forbes (-> Wandering around the world)
Antoine Bosselut (-> Assistant Professor @ EPFL)
Hannah Rashkin (-> Research Scientist @ Google Research)
Eunsol Choi (-> Assistant Professor @ Texas Austin)
Chloé Kiddon (-> Google)
Jun Seok Kang (-> Blink Health)
Song Feng (-> Research Staff Member @ IBM Research)
Polina Kuznetsova (-> Research Scientist @ Facebook)
Ritwik Banerjee (-> Research Assistant Professor @ Stony Brook University)
Undergrad:
Jenny Liang (-> PYI @ AI2 -> PhD @ CMU)
Jeff Da (-> PYI @ AI2)
Yao Dou (-> PhD @ GaTech)
Xinyao (Michelle) Ma (-> Pinterest)
Ge Gao (-> PhD @ Cornell)
Emily Louise Allaway (-> PhD @ Columbia)
Marcella Cindy Prasetio (-> MS @ Stanford)
Ryan Benmalek (-> PhD @ Cornell)
Pooja Sethi (-> Facebook)
Short Bio:
Yejin Choi is Wissner-Slivka Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and also a senior research director at AI2 overseeing the project Mosaic. Her research investigates a wide variety problems across NLP and AI including commonsense knowledge and reasoning, neural language (de-)generation, language grounding with vision and experience, and AI for social good. She is a MacArthur Fellow and a co-recipient of the NAACL Best Paper Award in 2022, the ICML Outstanding Paper Award in 2022, the ACL Test of Time award in 2021, the CVPR Longuet-Higgins Prize (test of time award) in 2021, the NeurIPS Outstanding Paper Award in 2021, the AAAI Outstanding Paper Award in 2020, the Borg Early Career Award (BECA) in 2018, the inaugural Alexa Prize Challenge in 2017, IEEE AI's 10 to Watch in 2016, and the ICCV Marr Prize (best paper award) in 2013. She received her Ph.D. in Computer Science at Cornell University and BS in Computer Science and Engineering at Seoul National University in Korea.
Personal:
Scuba!
CSEP 517 (Professional MS) Natural Language Processing [Winter 2021]
CSE 447 (Undergrad) Natural Language Processing [Winter 2020]
CSE 517 (Grad) Natural Language Processing [Winter 2019]
CSE 481 N (Undergrad Capstone) Natural Language Processing [Spring 2018]
CSE 447 (Undergrad) Natural Language Processing [Winter 2018]
CSE 481 N (Undergrad Capstone) Natural Language Processing [Spring 2017]
CSE 517 (Grad) Natural Language Processing [Winter 2017]
CSE 490 U (Undergrad) Natural Language Processing [Spring 2016]
CSEP 517 (Professional MS) Natural Language Processing [Autumn 2015]
CSE 599 (Grad) Advanced NLP [Spring 2015]
CSE 517 (Grad) Natural Language Processing [Winter 2015]
- Current members:
Post Doc:
Sean Welleck (Postdoc/Young Investigator @ UW/AI2-> ✨starting his tenure-track at CMU in Jan 2024)
Lianhui (Karen) Qin (Young Investigator @ AI2 -> ✨starting her tenure-track at UCSD in 2024)
Yuntian Deng (Young Investigator @ AI2 -> ✨starting his tenure-track at Waterloo in 2024)
Fatemeh (Niloofar) Mireshghallah (Postdoc @ UW) - co-advised with Yulia Tsvetkov
Tianxiao Shen (Postdoc @ UW) - co-advised with Zaid Harchaoui
Abhilasha Ravichander (Young Investigator @ AI2)
Faeze Brahman (Young Investigator @ AI2)
Valentina Pyatkin (Young Investigator @ AI2)
Hyunwoo Kim (Young Investigator @ AI2)
PhD:
Peter West
Xiujun Li
Jae Sung (James) Park - co-advised with Ali Farhadi
Liwei Jiang
Alisa Liu - co-advised with Noah Smith
Jiacheng (Gary) Liu - co-advised with Hannaneh Hajishirzi
Jillian Fisher - co-advised with Zaid Harchaoui
Melanie Sclar - co-advised with Yulia Tsvetkov
Jaehun Jung
Taylor Sorensen
Ximing (Gloria) Lu
Ben Newman
Anas Awadalla - co-advised with Ludwig Schmidt
Linjie (Lidsey) Li
Undergrad:
Kavel Rao
- Former members:
Post Doc:
Nouha Dziri (-> Research Scientist @ AI2)
Yuchen (Bill) Lin (-> Research Scientist @ AI2)
Prithviraj Ammanabrolu (-> Assistant Professor at UCSD after a gap year at MosaicML)
Alane Suhr (-> Assistant Professor @ UC Berkeley)
Xiang Lorraine Li (-> Assistant Professor @ University of Pittsburgh)
Youngjae Yu (-> Assistant Professor @ Yonsei University)
Daniel Khashabi (-> Assistant Professor @ JHU)
Swabha Swayamdipta (-> Assistant Professor @ USC)
Vered Shwartz (-> Assistant Professor @ UBC)
Jack Hessel (-> Research Scientist @ AI2)
Rachel Rudinger (-> Assistant Professor @ University of Maryland)
Yonatan Bisk (-> Assistant Professor @ CMU LTI/Robotics)
Jan Buys (-> Assistant Professor @ University of Cape Town)
Yannis Konstas (-> Assistant Professor @ Heriot-Watt University)
PhD:
Saadia Gabriel (->Assistant Professor @ UCLA after a gap year at MIT and NYU)
Maarten Sap (-> Assistant Professor at CMU)
Rowan Zellers (-> OpenAI)
Maxwell Forbes (-> Wandering around the world)
Antoine Bosselut (-> Assistant Professor @ EPFL)
Hannah Rashkin (-> Research Scientist @ Google Research)
Eunsol Choi (-> Assistant Professor @ Texas Austin)
Chloé Kiddon (-> Google)
Jun Seok Kang (-> Blink Health)
Song Feng (-> Research Staff Member @ IBM Research)
Polina Kuznetsova (-> Research Scientist @ Facebook)
Ritwik Banerjee (-> Research Assistant Professor @ Stony Brook University)
Undergrad:
Jenny Liang (-> PYI @ AI2 -> PhD @ CMU)
Jeff Da (-> PYI @ AI2)
Yao Dou (-> PhD @ GaTech)
Xinyao (Michelle) Ma (-> Pinterest)
Ge Gao (-> PhD @ Cornell)
Emily Louise Allaway (-> PhD @ Columbia)
Marcella Cindy Prasetio (-> MS @ Stanford)
Ryan Benmalek (-> PhD @ Cornell)
Pooja Sethi (-> Facebook)