Richard Yuanzhe Pang

51 papers A* 10Journal 28Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following. CoRR Yun He, Wenzhe Li, Hejia Zhang, Songlin Li, Karishma Mandyam, Sopan Khosla, Yuanhao Xiong, Nanshu Wang, Xiaoliang Peng, Beibin Li, Shengjie Bi, Shishir G. Patil, Qi Qi, Shengyu Feng, Julian Katz-Samuels, Richard Yuanzhe Pang, Sujan Gonugondla, Hunter Lang, Yue Yu, Yundi Qian, Maryam Fazel-Zarandi, Licheng Yu, Amine Benhalloum, Hany Awadalla, Manaal Faruqui
2025	J	`jnl`	Prompt Curriculum Learning for Efficient LLM Post-Training. CoRR Zhaolin Gao, Joongwon Kim, Wen Sun, Thorsten Joachims, Sid Wang, Richard Yuanzhe Pang, Liang Tan
2025	A*	`conf`	Self-Consistency Preference Optimization. ICML Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang, Jing Xu, Maryam Fazel-Zarandi, Mohit Bansal, Sainbayar Sukhbaatar, Jason E. Weston, Jane Yu
2025	—	`conf`	Self-Generated Critiques Boost Reward Modeling for Language Models. NAACL (Long Papers) Yue Yu, Zhengxing Chen, Aston Zhang, Liang Tan, Chenguang Zhu, Richard Yuanzhe Pang, Yundi Qian, Xuewei Wang, Suchin Gururangan, Chao Zhang, Melanie Kambadur, Dhruv Mahajan, Rui Hou
2025	A*	`conf`	Transformers Struggle to Learn to Search. ICLR Abulhair Saparov, Srushti Ajay Pawar, Shreyas Pimpalgaonkar, Nitish Joshi, Richard Yuanzhe Pang, Vishakh Padmakumar, Mehran Kazemi, Najoung Kim, He He
2024	J	`jnl`	An Introduction to Vision-Language Modeling. CoRR 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
2024	A*	`conf`	Iterative Reasoning Preference Optimization. NeurIPS Richard Yuanzhe Pang, Weizhe Yuan, He He, Kyunghyun Cho, Sainbayar Sukhbaatar, Jason Weston
2024	J	`jnl`	Iterative Reasoning Preference Optimization. CoRR Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, Jason Weston
2024	—	`—`	Learning from Rewards in Text Generation Richard Yuanzhe Pang
2024	—	`conf`	Leveraging Implicit Feedback from Deployment Data in Dialogue. EACL (2) Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
2024	J	`jnl`	Self-Consistency Preference Optimization. CoRR Archiki Prasad, Weizhe Yuan, Richard Yuanzhe Pang, Jing Xu, Maryam Fazel-Zarandi, Mohit Bansal, Sainbayar Sukhbaatar, Jason Weston, Jane A. Yu
2024	J	`jnl`	Self-Generated Critiques Boost Reward Modeling for Language Models. CoRR Yue Yu, Zhengxing Chen, Aston Zhang, Liang Tan, Chenguang Zhu, Richard Yuanzhe Pang, Yundi Qian, Xuewei Wang, Suchin Gururangan, Chao Zhang, Melanie Kambadur, Dhruv Mahajan, Rui Hou
2024	A*	`conf`	Self-Rewarding Language Models. ICML Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Xian Li, Sainbayar Sukhbaatar, Jing Xu, Jason Weston
2024	J	`jnl`	Self-Rewarding Language Models. CoRR Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Sainbayar Sukhbaatar, Jing Xu, Jason Weston
2024	J	`jnl`	Self-Taught Evaluators. CoRR Tianlu Wang, Ilia Kulikov, Olga Golovneva, Ping Yu, Weizhe Yuan, Jane Dwivedi-Yu, Richard Yuanzhe Pang, Maryam Fazel-Zarandi, Jason Weston, Xian Li
2024	J	`jnl`	Transformers Struggle to Learn to Search. CoRR Abulhair Saparov, Srushti Pawar, Shreyas Pimpalgaonkar, Nitish Joshi, Richard Yuanzhe Pang, Vishakh Padmakumar, Seyed Mehran Kazemi, Najoung Kim, He He
2023	A*	`conf`	Extrapolative Controlled Sequence Generation via Iterative Refinement. ICML Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
2023	J	`jnl`	Extrapolative Controlled Sequence Generation via Iterative Refinement. CoRR Vishakh Padmakumar, Richard Yuanzhe Pang, He He, Ankur P. Parikh
2023	J	`jnl`	GPQA: A Graduate-Level Google-Proof Q&A Benchmark. CoRR David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, Samuel R. Bowman
2023	J	`jnl`	Leveraging Implicit Feedback from Deployment Data in Dialogue. CoRR Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston
2023	—	`conf`	Reward Gaming in Conditional Text Generation. ACL (1) Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
2023	A*	`conf`	Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. NeurIPS Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Mehran Kazemi, Najoung Kim, He He
2023	J	`jnl`	Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. CoRR Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, Nitish Joshi, Seyed Mehran Kazemi, Najoung Kim, He He
2023	—	`conf`	What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. ACL (1) Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman
2022	—	`conf`	QuALITY: Question Answering with Long Input Texts, Yes! NAACL-HLT Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
2022	J	`jnl`	Reward Gaming in Conditional Text Generation. CoRR Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam, Ankur P. Parikh, He He
2022	A*	`conf`	SQuALITY: Building a Long-Document Summarization Dataset the Hard Way. EMNLP Alex Wang, Richard Yuanzhe Pang, Angelica Chen, Jason Phang, Samuel R. Bowman
2022	J	`jnl`	SQuALITY: Building a Long-Document Summarization Dataset the Hard Way. CoRR Alex Wang, Richard Yuanzhe Pang, Angelica Chen, Jason Phang, Samuel R. Bowman
2022	—	`conf`	Token Dropping for Efficient BERT Pretraining. ACL (1) Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
2022	J	`jnl`	Token Dropping for Efficient BERT Pretraining. CoRR Le Hou, Richard Yuanzhe Pang, Tianyi Zhou, Yuexin Wu, Xinying Song, Xiaodan Song, Denny Zhou
2022	J	`jnl`	What Do NLP Researchers Believe? Results of the NLP Community Metasurvey. CoRR Julian Michael, Ari Holtzman, Alicia Parrish, Aaron Mueller, Alex Wang, Angelica Chen, Divyam Madaan, Nikita Nangia, Richard Yuanzhe Pang, Jason Phang, Samuel R. Bowman
2021	—	`conf`	AgreeSum: Agreement-Oriented Multi-Document Summarization. ACL/IJCNLP (Findings) Richard Yuanzhe Pang, Ádám Dániel Lelkes, Vinh Q. Tran, Cong Yu
2021	J	`jnl`	AgreeSum: Agreement-Oriented Multi-Document Summarization. CoRR Richard Yuanzhe Pang, Ádám D. Lelkes, Vinh Q. Tran, Cong Yu
2021	J	`jnl`	Amortized Noisy Channel Neural Machine Translation. CoRR Richard Yuanzhe Pang, He He, Kyunghyun Cho
2021	—	`conf`	Comparing Test Sets with Item Response Theory. ACL/IJCNLP (1) Clara Vania, Phu Mon Htut, William Huang, Dhara A. Mungra, Richard Yuanzhe Pang, Jason Phang, Haokun Liu, Kyunghyun Cho, Samuel R. Bowman
2021	J	`jnl`	Comparing Test Sets with Item Response Theory. CoRR Clara Vania, Phu Mon Htut, William Huang, Dhara A. Mungra, Richard Yuanzhe Pang, Jason Phang, Haokun Liu, Kyunghyun Cho, Samuel R. Bowman
2021	J	`jnl`	QuALITY: Question Answering with Long Input Texts, Yes! CoRR Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, Nikita Nangia, Jason Phang, Angelica Chen, Vishakh Padmakumar, Johnny Ma, Jana Thompson, He He, Samuel R. Bowman
2021	A*	`conf`	Text Generation by Learning from Demonstrations. ICLR Richard Yuanzhe Pang, He He
2020	—	`conf`	Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. EMNLP (1) Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho
2020	J	`jnl`	Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. CoRR Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho
2020	A*	`conf`	ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation. ACL Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman, Kevin Gimpel
2020	J	`jnl`	ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation. CoRR Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman, Kevin Gimpel
2020	—	`conf`	Improving Joint Training of Inference Networks and Structured Prediction Energy Networks. SPNLP@EMNLP Lifu Tu, Richard Yuanzhe Pang, Kevin Gimpel
2020	A*	`conf`	Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work? ACL Yada Pruksachatkun, Jason Phang, Haokun Liu, Phu Mon Htut, Xiaoyi Zhang, Richard Yuanzhe Pang, Clara Vania, Katharina Kann, Samuel R. Bowman
2020	J	`jnl`	Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work? CoRR Yada Pruksachatkun, Jason Phang, Haokun Liu, Phu Mon Htut, Xiaoyi Zhang, Richard Yuanzhe Pang, Clara Vania, Katharina Kann, Samuel R. Bowman
2020	J	`jnl`	Text Generation by Learning from Off-Policy Demonstrations. CoRR Richard Yuanzhe Pang, He He
2019	J	`jnl`	Improving Joint Training of Inference Networks and Structured Prediction Energy Networks. CoRR Lifu Tu, Richard Yuanzhe Pang, Kevin Gimpel
2019	J	`jnl`	The Daunting Task of Real-World Textual Style Transfer Auto-Evaluation. CoRR Richard Yuanzhe Pang
2019	—	`conf`	Towards Actual (Not Operational) Textual Style Transfer Auto-Evaluation. W-NUT@EMNLP Richard Yuanzhe Pang
2019	—	`conf`	Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer. NGT@EMNLP-IJCNLP Richard Yuanzhe Pang, Kevin Gimpel
2018	J	`jnl`	Learning Criteria and Evaluation Metrics for Textual Transfer between Non-Parallel Corpora. CoRR Richard Yuanzhe Pang, Kevin Gimpel