World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
105
Citations
39757
World Ranking
291
National Ranking
159

Overview

Yejin Choi is affiliated with the University of Washington in the United States and has contributed extensively to the field of computer science, particularly focusing on artificial intelligence and related subfields. Their research encompasses topics such as topic modeling, natural language processing techniques, multimodal machine learning applications, explainable artificial intelligence (XAI), speech and dialogue systems, text readability and simplification, and hate speech and cyberbullying detection.

The scientist has published a significant number of papers, with notable recent works including:

  • CLIPScore: A Reference-free Evaluation Metric for Image Captioning (2021), Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • WinoGrande: An Adversarial Winograd Schema Challenge at Scale (2020), Proceedings of the AAAI Conference on Artificial Intelligence
  • WinoGrande (2021), Communications of the ACM
  • Distributional Footprints of Deceptive Product Reviews (2021), Proceedings of the International AAAI Conference on Web and Social Media
  • Generated Knowledge Prompting for Commonsense Reasoning (2022), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Yejin Choi frequently collaborates with other researchers. Common coauthors include:

  • Ronan Le Bras
  • Ximing Lu
  • Chandra Bhagavatula
  • Hannaneh Hajishirzi
  • Liwei Jiang

Their work appears primarily in venues such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Proceedings of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference on Empirical Methods in Natural Language Processing, and Zenodo (CERN European Organization for Nuclear Research).

The main fields of study in their research encompass computer science with a strong emphasis on artificial intelligence. Subfields include artificial intelligence, computer vision and pattern recognition, information systems, sociology and political science, and safety research.

Best Publications

  • The Curious Case of Neural Text Degeneration

    Ari Holtzman;Jan Buys;Leo Du;Maxwell Forbes

  • Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

    Xiujun Li;Xi Yin;Chunyuan Li;Pengchuan Zhang

  • BabyTalk: Understanding and Generating Simple Image Descriptions

    Girish Kulkarni;Visruth Premraj;Vicente Ordonez;Sagnik Dhar

  • Finding Deceptive Opinion Spam by Any Stretch of the Imagination

    Myle Ott;Yejin Choi;Claire Cardie;Jeffrey T. Hancock

  • Neural Motifs: Scene Graph Parsing with Global Context

    Rowan Zellers;Mark Yatskar;Sam Thomson;Yejin Choi

  • Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking

    Hannah Rashkin;Eunsol Choi;Jin Yea Jang;Svitlana Volkova

  • VinVL: Revisiting Visual Representations in Vision-Language Models

    Pengchuan Zhang;Xiujun Li;Xiaowei Hu;Jianwei Yang

  • COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

    Antoine Bosselut;Hannah Rashkin;Maarten Sap;Chaitanya Malaviya

  • CLIPScore: A Reference-free Evaluation Metric for Image Captioning

    Jack Hessel;Ari Holtzman;Maxwell Forbes;Ronan Le Bras

  • SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

    Rowan Zellers;Yonatan Bisk;Roy Schwartz;Yejin Choi

  • QuAC: Question Answering in Context

    Eunsol Choi;He He;Mohit Iyyer;Mohit Iyyer;Mark Yatskar

  • WinoGrande: an adversarial winograd schema challenge at scale

    Keisuke Sakaguchi;Ronan Le Bras;Chandra Bhagavatula;Yejin Choi

  • From Recognition to Cognition: Visual Commonsense Reasoning

    Rowan Zellers;Yonatan Bisk;Ali Farhadi;Yejin Choi

  • The Risk of Racial Bias in Hate Speech Detection.

    Maarten Sap;Dallas Card;Saadia Gabriel;Yejin Choi

  • OpinionFinder: A System for Subjectivity Analysis

    Theresa Wilson;Paul Hoffmann;Swapna Somasundaran;Jason Kessler

  • ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning

    Maarten Sap;Ronan Le Bras;Emily Allaway;Chandra Bhagavatula

  • Baby talk: Understanding and generating simple image descriptions

    Girish Kulkarni;Visruth Premraj;Sagnik Dhar;Siming Li

  • HellaSwag: Can a Machine Really Finish Your Sentence?

    Rowan Zellers;Ari Holtzman;Yonatan Bisk;Ali Farhadi

  • Syntactic Stylometry for Deception Detection

    Song Feng;Ritwik Banerjee;Yejin Choi

  • Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns

    Yejin Choi;Claire Cardie;Ellen Riloff;Siddharth Patwardhan

  • PIQA: Reasoning about Physical Commonsense in Natural Language

    Yonatan Bisk;Rowan Zellers;Ronan Le bras;Jianfeng Gao

  • Defending Against Neural Fake News

    Rowan Zellers;Ari Holtzman;Hannah Rashkin;Yonatan Bisk

Frequent Co-Authors

Maarten Sap
Maarten Sap Carnegie Mellon University
Noah A. Smith
Noah A. Smith University of Washington
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
Claire Cardie
Claire Cardie Cornell University
Asli Celikyilmaz
Asli Celikyilmaz Facebook (United States)
Ali Farhadi
Ali Farhadi University of Washington
Luke Zettlemoyer
Luke Zettlemoyer University of Washington
Tamara L. Berg
Tamara L. Berg University of North Carolina at Chapel Hill
Hannaneh Hajishirzi
Hannaneh Hajishirzi University of Washington
Alexander C. Berg
Alexander C. Berg University of North Carolina at Chapel Hill

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