Richard Yuanzhe Pang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 38

Top Topics

Document Summarization

Structured Prediction

Item Response Theory

Top Venues

Publications

Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
Leveraging Implicit Feedback from Deployment Data in Dialogue. EACL (2) (2024)
Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, Jason Weston
Iterative Reasoning Preference Optimization. CoRR (2024)
Florian Bordes, Richard Yuanzhe Pang, Anurag Ajay, Alexander C. Li, Adrien Bardes, Suzanne Petryk, Oscar Mañas, Zhiqiu Lin, Anas Mahmoud, Bargav Jayaraman, Mark Ibrahim, Melissa Hall, Yunyang Xiong, Jonathan Lebensold, Candace Ross, Srihari Jayakumar, Chuan Guo, Diane Bouchacourt, Haider Al-Tahan, Karthik Padthe, Vasu Sharma, Hu Xu, Xiaoqing Ellen Tan, Megan Richards, Samuel Lavoie, Pietro Astolfi, Reyhane Askari Hemmat, Jun Chen, Kushal Tirumala, Rim Assouel, Mazda Moayeri, Arjang Talattof, Kamalika Chaudhuri, Zechun Liu, Xilun Chen, Quentin Garrido, Karen Ullrich, Aishwarya Agrawal, Kate Saenko, Asli Celikyilmaz, Vikas Chandra
An Introduction to Vision-Language Modeling. CoRR (2024)
Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Sainbayar Sukhbaatar, Jing Xu, Jason Weston
Self-Rewarding Language Models. CoRR (2024)
Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Seyed Mehran Kazemi, Najoung Kim, He He
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. CoRR (2023)
Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
Leveraging Implicit Feedback from Deployment Data in Dialogue. CoRR (2023)
Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. ACL (1) (2023)
Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
Extrapolative Controlled Sequence Generation via Iterative Refinement. CoRR (2023)
Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
Reward Gaming in Conditional Text Generation. ACL (1) (2023)
Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
Extrapolative Controlled Sequence Generation via Iterative Refinement. ICML (2023)
Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Mehran Kazemi, Najoung Kim, He He
Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. NeurIPS (2023)
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, Samuel R. Bowman
GPQA: A Graduate-Level Google-Proof Q&A Benchmark. CoRR (2023)
Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
Token Dropping for Efficient BERT Pretraining. ACL (1) (2022)
Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman
What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. CoRR (2022)
Alex Wang, Richard Yuanzhe Pang, Angelica Chen, Jason Phang, Samuel R. Bowman
SQuALITY: Building a Long-Document Summarization Dataset the Hard Way. CoRR (2022)
Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
Token Dropping for Efficient BERT Pretraining. CoRR (2022)
Alex Wang, Richard Yuanzhe Pang, Angelica Chen, Jason Phang, Samuel R. Bowman
SQuALITY: Building a Long-Document Summarization Dataset the Hard Way. EMNLP (2022)
Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
Reward Gaming in Conditional Text Generation. CoRR (2022)
Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
QuALITY: Question Answering with Long Input Texts, Yes! NAACL-HLT (2022)
Richard Yuanzhe Pang, Ádám D. Lelkes, Vinh Q. Tran, Cong Yu
AgreeSum: Agreement-Oriented Multi-Document Summarization. CoRR (2021)
Richard Yuanzhe Pang, Ádám Dániel Lelkes, Vinh Q. Tran, Cong Yu
AgreeSum: Agreement-Oriented Multi-Document Summarization. ACL/IJCNLP (Findings) (2021)
Clara Vania, Phu Mon Htut, William Huang, Dhara A. Mungra, Richard Yuanzhe Pang, Jason Phang, Haokun Liu, Kyunghyun Cho, Samuel R. Bowman
Comparing Test Sets with Item Response Theory. CoRR (2021)
Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
QuALITY: Question Answering with Long Input Texts, Yes! CoRR (2021)
Richard Yuanzhe Pang, He He
Text Generation by Learning from Demonstrations. ICLR (2021)
Clara Vania, Phu Mon Htut, William Huang, Dhara A. Mungra, Richard Yuanzhe Pang, Jason Phang, Haokun Liu, Kyunghyun Cho, Samuel R. Bowman
Comparing Test Sets with Item Response Theory. ACL/IJCNLP (1) (2021)
Richard Yuanzhe Pang, He He, Kyunghyun Cho
Amortized Noisy Channel Neural Machine Translation. CoRR (2021)
Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. CoRR (2020)
Lifu Tu, Richard Yuanzhe Pang, Kevin Gimpel
Improving Joint Training of Inference Networks and Structured Prediction Energy Networks. SPNLP@EMNLP (2020)
Yada Pruksachatkun, Jason Phang, Haokun Liu, Phu Mon Htut, Xiaoyi Zhang, Richard Yuanzhe Pang, Clara Vania, Katharina Kann, Samuel R. Bowman
Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work? ACL (2020)
Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman, Kevin Gimpel
ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation. CoRR (2020)
Richard Yuanzhe Pang, He He
Text Generation by Learning from Off-Policy Demonstrations. CoRR (2020)
Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman, Kevin Gimpel
ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation. ACL (2020)
Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. EMNLP (1) (2020)
Yada Pruksachatkun, Jason Phang, Haokun Liu, Phu Mon Htut, Xiaoyi Zhang, Richard Yuanzhe Pang, Clara Vania, Katharina Kann, Samuel R. Bowman
Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work? CoRR (2020)
Lifu Tu, Richard Yuanzhe Pang, Kevin Gimpel
Improving Joint Training of Inference Networks and Structured Prediction Energy Networks. CoRR (2019)
Richard Yuanzhe Pang, Kevin Gimpel
Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer. NGT@EMNLP-IJCNLP (2019)
Richard Yuanzhe Pang
Towards Actual (Not Operational) Textual Style Transfer Auto-Evaluation. W-NUT@EMNLP (2019)
Richard Yuanzhe Pang
The Daunting Task of Real-World Textual Style Transfer Auto-Evaluation. CoRR (2019)