Yejin Choi

ORCID

Publication Activity (10 Years)

Years Active: 2022-2024
Publications (10 Years): 130

Top Venues

Publications

Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin
Agent Lumos: Unified and Modular Training for Open-Source Language Agents. ACL (1) (2024)
Bill Yuchen Lin, Yuntian Deng, Khyathi Raghavi Chandu, Faeze Brahman, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, Yejin Choi
WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. CoRR (2024)
Yujie Lu, Dongfu Jiang, Wenhu Chen, William Yang Wang, Yejin Choi, Bill Yuchen Lin
WildVision: Evaluating Vision-Language Models in the Wild with Human Preferences. CoRR (2024)
Khyathi Raghavi Chandu, Linjie Li, Anas Awadalla, Ximing Lu, Jae Sung Park, Jack Hessel, Lijuan Wang, Yejin Choi
Certainly Uncertain: A Benchmark and Metric for Multimodal Epistemic and Aleatoric Awareness. CoRR (2024)
Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L. Griffiths, Faeze Brahman
MacGyver: Are Large Language Models Creative Problem Solvers? NAACL-HLT (2024)
Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Kumar Guha, Matt Jordan, Sheng Shen, Mohamed Awadalla, Silvio Savarese, Caiming Xiong, Ran Xu, Yejin Choi, Ludwig Schmidt
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens. CoRR (2024)
Yu Ying Chiu, Liwei Jiang, Maria Antoniak, Chan Young Park, Shuyue Stella Li, Mehar Bhatia, Sahithya Ravi, Yulia Tsvetkov, Vered Shwartz, Yejin Choi
CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs' (Lack of) Multicultural Knowledge. CoRR (2024)
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
The Generative AI Paradox: "What It Can Create, It May Not Understand". ICLR (2024)
Liwei Jiang, Kavel Rao, Seungju Han, Allyson Ettinger, Faeze Brahman, Sachin Kumar, Niloofar Mireshghallah, Ximing Lu, Maarten Sap, Yejin Choi, Nouha Dziri
WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models. CoRR (2024)
Seungone Kim, Juyoung Suk, Ji Yong Cho, Shayne Longpre, Chaeeun Kim, Dongkeun Yoon, Guijin Son, Yejin Choi, Sheikh Shafayat, Jinheon Baek, Sue Hyun Park, Hyeonbin Hwang, Jinkyung Jo, Hyowon Cho, Haebin Shin, Seongyun Lee, Hanseok Oh, Noah Lee, Namgyu Ho, Se June Joo, Miyoung Ko, Yoonjoo Lee, Hyungjoo Chae, Jamin Shin, Joel Jang, Seonghyeon Ye, Bill Yuchen Lin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, Minjoon Seo
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models. CoRR (2024)
Alisa Liu, Xiaochuang Han, Yizhong Wang, Yulia Tsvetkov, Yejin Choi, Noah A. Smith
Tuning Language Models by Proxy. CoRR (2024)
Siyuan Wang, Zhongyu Wei, Yejin Choi, Xiang Ren
Can LLMs Reason with Rules? Logic Scaffolding for Stress-Testing and Improving LLMs. ACL (1) (2024)
Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell L. Gordon, Niloofar Mireshghallah, Christopher Michael Rytting, Andre Ye, Liwei Jiang, Ximing Lu, Nouha Dziri, Tim Althoff, Yejin Choi
A Roadmap to Pluralistic Alignment. CoRR (2024)
Nathan Lambert, Valentina Pyatkin, Jacob Morrison, LJ Miranda, Bill Yuchen Lin, Khyathi Raghavi Chandu, Nouha Dziri, Sachin Kumar, Tom Zick, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi
RewardBench: Evaluating Reward Models for Language Modeling. CoRR (2024)
Taylor Sorensen, Liwei Jiang, Jena D. Hwang, Sydney Levine, Valentina Pyatkin, Peter West, Nouha Dziri, Ximing Lu, Kavel Rao, Chandra Bhagavatula, Maarten Sap, John Tasioulas, Yejin Choi
Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties. AAAI (2024)
Jiacheng Liu, Sewon Min, Luke Zettlemoyer, Yejin Choi, Hannaneh Hajishirzi
Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens. CoRR (2024)
Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, Pradeep Dasigi, Valentina Pyatkin, Abhilasha Ravichander, Sarah Wiegreffe, Nouha Dziri, Khyathi Raghavi Chandu, Jack Hessel, Yulia Tsvetkov, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
The Art of Saying No: Contextual Noncompliance in Language Models. CoRR (2024)
Wenting Zhao, Justin T. Chiu, Jena D. Hwang, Faeze Brahman, Jack Hessel, Sanjiban Choudhury, Yejin Choi, Xiang Li, Alane Suhr
UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations. NAACL-HLT (2024)
Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min, Weijia Shi, Luke Zettlemoyer, Yulia Tsvetkov, Yejin Choi, David Evans, Hannaneh Hajishirzi
Do Membership Inference Attacks Work on Large Language Models? CoRR (2024)
Chani Jung, Dongkwan Kim, Jiho Jin, Jiseon Kim, Yeon Seonwoo, Yejin Choi, Alice Oh, Hyunwoo Kim
Perceptions to Beliefs: Exploring Precursory Inferences for Theory of Mind in Large Language Models. CoRR (2024)
Jaehun Jung, Peter West, Liwei Jiang, Faeze Brahman, Ximing Lu, Jillian Fisher, Taylor Sorensen, Yejin Choi
Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model. NAACL-HLT (2024)
Tejas Srinivasan, Jack Hessel, Tanmay Gupta, Bill Yuchen Lin, Yejin Choi, Jesse Thomason, Khyathi Raghavi Chandu
Selective "Selective Prediction": Reducing Unnecessary Abstention in Vision-Language Reasoning. CoRR (2024)
Natalie Shapira, Mosh Levy, Seyed Hossein Alavi, Xuhui Zhou, Yejin Choi, Yoav Goldberg, Maarten Sap, Vered Shwartz
Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models. EACL (1) (2024)
Jillian Fisher, Ximing Lu, Jaehun Jung, Liwei Jiang, Zaïd Harchaoui, Yejin Choi
JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. NAACL-HLT (2024)
Jimin Mun, Liwei Jiang, Jenny T. Liang, Inyoung Cheong, Nicole DeCario, Yejin Choi, Tadayoshi Kohno, Maarten Sap
Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits. CoRR (2024)
Yutaro Yamada, Khyathi Chandu, Bill Yuchen Lin, Jack Hessel, Ilker Yildirim, Yejin Choi
L3GO: Language Agents with Chain-of-3D-Thoughts for Generating Unconventional Objects. CoRR (2024)
Aly M. Kassem, Omar Mahmoud, Niloofar Mireshghallah, Hyunwoo Kim, Yulia Tsvetkov, Yejin Choi, Sherif Saad, Santu Rana
Alpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs. CoRR (2024)
Wenting Zhao, Tanya Goyal, Yu Ying Chiu, Liwei Jiang, Benjamin Newman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Ronan Le Bras, Claire Cardie, Yuntian Deng, Yejin Choi
WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries. CoRR (2024)
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin Choi
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning. ICLR (2024)
Jungo Kasai, Keisuke Sakaguchi, Ronan Le Bras, Dragomir Radev, Yejin Choi, Noah A. Smith
A Call for Clarity in Beam Search: How It Works and When It Stops. LREC/COLING (2024)
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, Yuntian Deng
WildChat: 1M ChatGPT Interaction Logs in the Wild. CoRR (2024)
Jillian Fisher, Ximing Lu, Jaehun Jung, Liwei Jiang, Zaïd Harchaoui, Yejin Choi
JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models. CoRR (2024)
Tong Chen, Akari Asai, Niloofar Mireshghallah, Sewon Min, James Grimmelmann, Yejin Choi, Hannaneh Hajishirzi, Luke Zettlemoyer, Pang Wei Koh
CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation. CoRR (2024)
Seungone Kim, Jamin Shin, Yejin Choi, Joel Jang, Shayne Longpre, Hwaran Lee, Sangdoo Yun, Seongjin Shin, Sungdong Kim, James Thorne, Minjoon Seo
Prometheus: Inducing Fine-Grained Evaluation Capability in Language Models. ICLR (2024)
Jaeyoung Lee, Ximing Lu, Jack Hessel, Faeze Brahman, Youngjae Yu, Yonatan Bisk, Yejin Choi, Saadia Gabriel
How to Train Your Fact Verifier: Knowledge Transfer with Multimodal Open Models. CoRR (2024)
Siyuan Wang, Zhongyu Wei, Yejin Choi, Xiang Ren
Can LLMs Reason with Rules? Logic Scaffolding for Stress-Testing and Improving LLMs. CoRR (2024)
Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Harold Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang Ren
Tailoring Self-Rationalizers with Multi-Reward Distillation. ICLR (2024)
Linlu Qiu, Liwei Jiang, Ximing Lu, Melanie Sclar, Valentina Pyatkin, Chandra Bhagavatula, Bailin Wang, Yoon Kim, Yejin Choi, Nouha Dziri, Xiang Ren
Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement. ICLR (2024)
Niloofar Mireshghallah, Maria Antoniak, Yash More, Yejin Choi, Golnoosh Farnadi
Trust No Bot: Discovering Personal Disclosures in Human-LLM Conversations in the Wild. CoRR (2024)
Zane Durante, Qiuyuan Huang, Naoki Wake, Ran Gong, Jae Sung Park, Bidipta Sarkar, Rohan Taori, Yusuke Noda, Demetri Terzopoulos, Yejin Choi, Katsushi Ikeuchi, Hoi Vo, Li Fei-Fei, Jianfeng Gao
Agent AI: Surveying the Horizons of Multimodal Interaction. CoRR (2024)
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, Jena D. Hwang, Xiang Lorraine Li, Hirona Jacqueline Arai, Soumya Sanyal, Keisuke Sakaguchi, Xiang Ren, Yejin Choi
PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning. ICLR (2024)
Hamish Ivison, Yizhong Wang, Jiacheng Liu, Zeqiu Wu, Valentina Pyatkin, Nathan Lambert, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback. CoRR (2024)
Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin, Nathan Lambert, Yejin Choi, Nouha Dziri
WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs. CoRR (2024)
Yuntian Deng, Yejin Choi, Stuart M. Shieber
From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step. CoRR (2024)
Tejas Srinivasan, Jack Hessel, Tanmay Gupta, Bill Yuchen Lin, Yejin Choi, Jesse Thomason, Khyathi Raghavi Chandu
Selective "Selective Prediction": Reducing Unnecessary Abstention in Vision-Language Reasoning. ACL (Findings) (2024)
Melanie Sclar, Yejin Choi, Yulia Tsvetkov, Alane Suhr
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting. ICLR (2024)
Jaehun Jung, Ximing Lu, Liwei Jiang, Faeze Brahman, Peter West, Pang Wei Koh, Yejin Choi
Information-Theoretic Distillation for Reference-less Summarization. CoRR (2024)
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, Yuntian Deng
WildChat: 1M ChatGPT Interaction Logs in the Wild. ICLR (2024)
Jonathan Hayase, Alisa Liu, Yejin Choi, Sewoong Oh, Noah A. Smith
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data? CoRR (2024)
Zhangchen Xu, Fengqing Jiang, Luyao Niu, Yuntian Deng, Radha Poovendran, Yejin Choi, Bill Yuchen Lin
Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing. CoRR (2024)
Shangbin Feng, Taylor Sorensen, Yuhan Liu, Jillian Fisher, Chan Young Park, Yejin Choi, Yulia Tsvetkov
Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration. CoRR (2024)
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory. ICLR (2024)
Huihan Li, Liwei Jiang, Jena D. Huang, Hyunwoo Kim, Sebastin Santy, Taylor Sorensen, Bill Yuchen Lin, Nouha Dziri, Xiang Ren, Yejin Choi
CULTURE-GEN: Revealing Global Cultural Perception in Language Models through Natural Language Prompting. CoRR (2024)
Jaehun Jung, Faeze Brahman, Yejin Choi
Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement. CoRR (2024)
Hanjie Chen, Faeze Brahman, Xiang Ren, Yangfeng Ji, Yejin Choi, Swabha Swayamdipta
REV: Information-Theoretic Evaluation of Free-Text Rationales. ACL (1) (2023)
Alisa Liu, Zhaofeng Wu, Julian Michael, Alane Suhr, Peter West, Alexander Koller, Swabha Swayamdipta, Noah A. Smith, Yejin Choi
We're Afraid Language Models Aren't Modeling Ambiguity. EMNLP (2023)
Jiacheng Liu, Ramakanth Pasunuru, Hannaneh Hajishirzi, Yejin Choi, Asli Celikyilmaz
Crystal: Introspective Reasoners Reinforced with Self-Feedback. CoRR (2023)
Liunian Harold Li, Jack Hessel, Youngjae Yu, Xiang Ren, Kai-Wei Chang, Yejin Choi
Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step. CoRR (2023)
Da Yin, Faeze Brahman, Abhilasha Ravichander, Khyathi Chandu, Kai-Wei Chang, Yejin Choi, Bill Yuchen Lin
Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs. CoRR (2023)
Yujie Lu, Xiujun Li, William Yang Wang, Yejin Choi
VIM: Probing Multimodal Large Language Models for Visual Embedded Instruction Following. CoRR (2023)
Wenting Zhao, Justin T. Chiu, Jena D. Hwang, Faeze Brahman, Jack Hessel, Sanjiban Choudhury, Yejin Choi, Xiang Lorraine Li, Alane Suhr
UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations. CoRR (2023)
Jae Sung Park, Jack Hessel, Khyathi Raghavi Chandu, Paul Pu Liang, Ximing Lu, Peter West, Youngjae Yu, Qiuyuan Huang, Jianfeng Gao, Ali Farhadi, Yejin Choi
Localized Symbolic Knowledge Distillation for Visual Commonsense Models. CoRR (2023)
Phillip Howard, Junlin Wang, Vasudev Lal, Gadi Singer, Yejin Choi, Swabha Swayamdipta
NeuroComparatives: Neuro-Symbolic Distillation of Comparative Knowledge. CoRR (2023)
Julia Mendelsohn, Ronan Le Bras, Yejin Choi, Maarten Sap
From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Models. CoRR (2023)
Seungju Han, Jack Hessel, Nouha Dziri, Yejin Choi, Youngjae Yu
Champagne: Learning Real-world Conversation from Large-Scale Web Videos. ICCV (2023)
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, Yejin Choi
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory. CoRR (2023)
Wangchunshu Zhou, Ronan Le Bras, Yejin Choi
Commonsense Knowledge Transfer for Pre-trained Language Models. CoRR (2023)
Brihi Joshi, Ziyi Liu, Sahana Ramnath, Aaron Chan, Zhewei Tong, Shaoliang Nie, Qifan Wang, Yejin Choi, Xiang Ren
Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-text Rationales. ACL (1) (2023)
Skyler Hallinan, Faeze Brahman, Ximing Lu, Jaehun Jung, Sean Welleck, Yejin Choi
STEER: Unified Style Transfer with Expert Reinforcement. CoRR (2023)
Seungju Han, Junhyeok Kim, Jack Hessel, Liwei Jiang, Jiwan Chung, Yejin Son, Yejin Choi, Youngjae Yu
Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms. CoRR (2023)
Taylor Sorensen, Liwei Jiang, Jena D. Hwang, Sydney Levine, Valentina Pyatkin, Peter West, Nouha Dziri, Ximing Lu, Kavel Rao, Chandra Bhagavatula, Maarten Sap, John Tasioulas, Yejin Choi
Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties. CoRR (2023)
Tianxiao Shen, Hao Peng, Ruoqi Shen, Yao Fu, Zaïd Harchaoui, Yejin Choi
FiLM: Fill-in Language Models for Any-Order Generation. CoRR (2023)
Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, 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
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. CoRR (2023)
Hyunwoo Kim, Jack Hessel, Liwei Jiang, Peter West, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap, Yejin Choi
SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. EMNLP (2023)
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Sean Welleck, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Xiang Ren, Allyson Ettinger, Zaïd Harchaoui, Yejin Choi
Faith and Fate: Limits of Transformers on Compositionality. NeurIPS (2023)
Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley, Jack Hessel, Rafet Sifa, Christian Bauckhage, Hannaneh Hajishirzi, Yejin Choi
Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization. ICLR (2023)
Melanie Sclar, Yejin Choi, Yulia Tsvetkov, Alane Suhr
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting. CoRR (2023)
Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, Yejin Choi
Generating Sequences by Learning to Self-Correct. ICLR (2023)
Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, Ronan Le Bras, Akari Asai, Xinyan Yu, Dragomir Radev, Noah A. Smith, Yejin Choi, Kentaro Inui
RealTime QA: What's the Answer Right Now? NeurIPS (2023)
Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Harold Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang Ren
Tailoring Self-Rationalizers with Multi-Reward Distillation. CoRR (2023)
Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Chandu, Abhilasha Ravichander, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Lin, Skyler Hallinan, Lianhui Qin, Xiang Ren, Sean Welleck, Yejin Choi
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. EMNLP (2023)
Melanie Sclar, Sachin Kumar, Peter West, Alane Suhr, Yejin Choi, Yulia Tsvetkov
Minding Language Models' (Lack of) Theory of Mind: A Plug-and-Play Multi-Character Belief Tracker. CoRR (2023)
Wangchunshu Zhou, Ronan Le Bras, Yejin Choi
Modular Transformers: Compressing Transformers into Modularized Layers for Flexible Efficient Inference. ACL (Findings) (2023)
Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hannaneh Hajishirzi, Sameer Singh, Roy Fox
Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling. ICML (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
Fusing Pre-Trained Language Models with Multimodal Prompts through Reinforcement Learning. CVPR (2023)
Wanrong Zhu, Jack Hessel, Anas Awadalla, Samir Yitzhak Gadre, Jesse Dodge, Alex Fang, Youngjae Yu, Ludwig Schmidt, William Yang Wang, Yejin Choi
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text. NeurIPS (2023)
Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, Jena D. Hwang, Xiang Lorraine Li, Hirona J. Arai, Soumya Sanyal, Keisuke Sakaguchi, Xiang Ren, Yejin Choi
PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning. CoRR (2023)
Hyunwoo Kim, Melanie Sclar, Xuhui Zhou, Ronan Le Bras, Gunhee Kim, Yejin Choi, Maarten Sap
FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactions. EMNLP (2023)
Jack Hessel, Ana Marasovic, Jena D. Hwang, Lillian Lee, Jeff Da, Rowan Zellers, Robert Mankoff, Yejin Choi
Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contest. ACL (1) (2023)
Kavel Rao, Liwei Jiang, Valentina Pyatkin, Yuling Gu, Niket Tandon, Nouha Dziri, Faeze Brahman, Yejin Choi
What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations. CoRR (2023)
Pei Zhou, Andrew Zhu, Jennifer Hu, Jay Pujara, Xiang Ren, Chris Callison-Burch, Yejin Choi, Prithviraj Ammanabrolu
I Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons. ACL (1) (2023)
Wangchunshu Zhou, Ronan Le Bras, Yejin Choi
Modular Transformers: Compressing Transformers into Modularized Layers for Flexible Efficient Inference. CoRR (2023)
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, Zaïd Harchaoui, Yejin Choi
Faith and Fate: Limits of Transformers on Compositionality. CoRR (2023)
Linlu Qiu, Liwei Jiang, Ximing Lu, Melanie Sclar, Valentina Pyatkin, Chandra Bhagavatula, Bailin Wang, Yoon Kim, Yejin Choi, Nouha Dziri, Xiang Ren
Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement. CoRR (2023)
Wangchunshu Zhou, Ronan Le Bras, Yejin Choi
Commonsense Knowledge Transfer for Pre-trained Language Models. ACL (Findings) (2023)
Kavel Rao, Liwei Jiang, Valentina Pyatkin, Yuling Gu, Niket Tandon, Nouha Dziri, Faeze Brahman, Yejin Choi
What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations. EMNLP (Findings) (2023)
Jiacheng Liu, Ramakanth Pasunuru, Hannaneh Hajishirzi, Yejin Choi, Asli Celikyilmaz
Crystal: Introspective Reasoners Reinforced with Self-Feedback. EMNLP (2023)
Liunian Harold Li, Jack Hessel, Youngjae Yu, Xiang Ren, Kai-Wei Chang, Yejin Choi
Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step. ACL (1) (2023)
Julia Mendelsohn, Ronan Le Bras, Yejin Choi, Maarten Sap
From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Models. ACL (1) (2023)
Zhaoxuan Tan, Shangbin Feng, Melanie Sclar, Herun Wan, Minnan Luo, Yejin Choi, Yulia Tsvetkov
BotPercent: Estimating Bot Populations in Twitter Communities. EMNLP (Findings) (2023)

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Publication Activity (10 Years)

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Yejin Choi