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 - 2024):

Mar 2024	Keynote at the Weinberg Cognitive Science Symposium
Mar 2024	Colloquium at Harvard Psychology
Nov 2023	Visit at UC Irvine
Nov 2023	Talk at UCSD
Nov 2023	Colloquium at MIT Brain and Cognitive Sciences (BCS)
Nov 2023	Distinguished Lecture at UBC
Oct 2023	Talk at the MacArthuer Fellows Forum
Oct 2023	Distinguished Lecture at TTIC
Oct 2023	Talk at the Ohio State University
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 the Simons Institute Workshop on LLMs with the recorded talk →here
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 →here
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 →here
Mar 2023	Talk at AI For Tigray --- cancelled
Mar 2023	Colloquium at Berkeley
Mar 2023	Guest Lecture at the Stanford MLSys seminar co listed with 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 →here
Dec 2022	Talk at the NeurIPS workshop on Robustness in Sequence Modeling
Nov 2022	Talk at SoCal NLP Symposium with the recorded talk →here
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 →here
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 →here
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 →here and the panel →here
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 →here
Feb 2021	Keynote at the AAAI Workshop on Commonsense Knowledge Graphs
Jan 2021	Teaching at the ALPS Winter School with recorded lectures →here
Jan 2021	Talk at UCL Dark Lab with a recorded talk →here
Dec 2020	Panel at AI Debate 2 at Montreal.ai with a recorded talk →here (my 3 min pitch) and →here (the whole 3.5 hr debate)
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 →here
Oct 2020	Keynote at the Fall Stanford Human-Centered AI (HAI) Conference on Triangulating Intelligence: Melding Neuroscience, Psychology, and AI with a recorded talk →here (from 28:00 to 53:00)
Oct 2020	Distinguished Lecture (Department Colloquium) at Columbia University
Oct 2020	Colloquium at CMU LTI with a recorded talk →here
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 →here
Aug 2020	Keynote at CIFAR Deep Learning Seminar Summer School with a pre-recorded talk →here
Jul 2020	ACL Tutorial on Commonsense with a recorded talk →here
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 →here
Jun 2020	CVPR tutorial on Neuro-Symbolic Visual Reasoning and Program Synthesis with a recorded talk →here
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 →here
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:

The Generative AI Paradox: “What It Can Create, It May Not Understand”
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
arXiv:xxxx.xxxxx

Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties
Taylor Sorensen, Liwei Jiang, Jena Hwang, Sydney Levine, Valentina Pyatkin, Peter West, Nouha Dziri, Ximing Lu, Kavel Rao, Chandra Bhagavatula, Maarten Sap, John Tasioulas, Yejin Choi
arXiv:2309.00779

Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging
Joel Jang, Seungone Kim, Bill Yuchen Lin, Yizhong Wang, Jack Hessel, Luke Zettlemoyer, Hannaneh Hajishirzi, Yejin Choi, Prithviraj Ammanabrolu
arXiv:2310.11564

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement
Linlu Qiu, Liwei Jiang, Ximing Lu, Melanie Sclar, Valentina Pyatkin, Chandra Bhagavatula, Bailin Wang, Yoon Kim, Yejin Choi, Nouha Dziri, Xiang Ren
arXiv:2310.08559

Making PPO even better: Value-Guided Monte-Carlo Tree Search decoding
Jiacheng Liu, Andrew Cohen, Ramakanth Pasunuru, Yejin Choi, Hannaneh Hajishirzi, Asli Celikyilmaz
arXiv:2309.15028

Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi
arXiv:2310.17884

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

Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
Melanie Sclar, Yejin Choi, Yulia Tsvetkov, Alane Suhr
arXiv:2310.11324

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

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

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

FiLM: Fill-in Language Models for Any-Order Generation
Tianxiao Shen, Hao Peng, Ruoqi Shen, Yao Fu, Zaid Harchaoui, Yejin Choi
arXiv:2310.09930

Recent Publications (2016 - 2023):

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
NeurIPS 2023 spotlight

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
NeurIPS 2023 spotlight

Localized Symbolic Knowledge Distillation for Visual Commonsense Models
Jae Sung Park, Jack Hessel, Khyathi Chandu, Paul Pu Liang, Ximing Lu, Qiuyuan Huang, Peter West, Jianfeng Gao, Ali Farhadi, Yejin Choi
NeurIPS 2023

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
NeurIPS 2023, Dataset and Benchmarks Track

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
NeurIPS 2023, Dataset and Benchmarks Track
*Project

🍺 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
EMNLP 2023

Vera: A General-Purpose Plausibility Estimation Model for Commonsense Statements
Jiacheng Liu, Wenya Wang, Dianzhuo Wang, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
EMNLP 2023

Crystal: Introspective Reasoners Reinforced with Self-Feedback/a>
Jiacheng Liu, Ramakanth Pasunuru, Hannaneh Hajishirzi, Yejin Choi, Asli Celikyilmaz
EMNLP 2023

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
EMNLP 2023

FANToM: A Benchmark for Stress-Testing Theory of Mind in Interactions
Hyunwoo Kim, Jack Hessel, Liwei Jiang, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, Yejin Choi
EMNLP 2023

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
EMNLP 2023

Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms
Seungju Han, Junhyeok Kim, Jack Hessel, Liwei Jiang, Jiwan Chung, Yejin Son, Yejin Choi, Youngjae Yu
EMNLP 2023

NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation
Peter West, Ronan Le Bras, Taylor Sorensen, Bill Yuchen Lin, Liwei Jiang, Ximing Lu, Khyathi Chandu, Jack Hessel, Ashutosh Baheti, Chandra Bhagavatula, Yejin Choi
EMNLP 2023 Findings

What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations
Kavel Rao, Liwei Jiang, Valentina Pyatkin, Yuling Gu, Niket Tandon, Nouha Dziri, Faeze Brahman, Yejin Choi
EMNLP 2023 Findings

"You Are An Expert Linguistic Annotator": Limits of LLMs as Analyzers of Abstract Meaning Representation
Allyson Ettinger, Jena D. Hwang, Valentina Pyatkin, Chandra Bhagavatula, Yejin Choi
EMNLP 2023 Findings

STEER: Unified Style Transfer with Expert Reinforcement
Skyler Hallinan, Faeze Brahman, Ximing Lu, Jaehun Jung, Sean Welleck, Yejin Choi
EMNLP 2023 Findings

BotPercent: Estimating Bot Populations in Twitter Communities
Zhaoxuan Tan, Shangbin Feng, Melanie Sclar, Herun Wan, Minnan Luo, Yejin Choi, Yulia Tsvetkov
EMNLP 2023 Findings

CHAMPAGNE: Learning Real-world Conversation from Large-Scale Web Videos
Seungju Han, Jack Hessel, Nouha Dziri, Yejin Choi, Youngjae Yu
ICCV 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:

Google Scholar
Semantic Scholar

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)
         Mitchell L Gordon (Postdoc @ AI2 -> ✨starting his tenure-track at MIT in 2024) --- co-advised with Jeff Heer
  
         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 -> Samaya AI)
         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!