Weizhe Yuan
ML/NLP, Painting
bellyapplerian@gmail.com

About

Currently, I am a third-year Ph.D. student at New York University advised by Prof. Kyunghyun Cho and Prof. Jason Weston. My research experience mainly focused on text generation and evaluation for NLP tasks but I’m open to other areas as well. I currently work on self-training for large language models and alignment research in general. My long-time research goal is to develop intelligent systems for human goods.

Before now, I was a Master’s student at Carnegie Mellon University majoring computational data science. During my Master’s period, I worked closely with Dr. Pengfei Liu and Prof. Graham Neubig and developed my interest in natural language processing.

I received my Bachelor’s degree from Wuhan University in 2019, majoring civil engineering and computer science.

News

  • 2022.05.22 Received the Outstanding Demo Paper Award at ACL 2022 🏆
  • 2021.12.01 One paper accepted to AAAI 2022 🎉
  • 2021.09.29 One paper accepted to NeurIPS 2021 🎉
  • 2021.07.28 Released a survey regarding prompt-based learning
  • 2021.07.20 Received the Best Demo Paper Award at ACL 2021 🏆
  • 2021.07.12 Gave a talk on BARTScore: Evaluating Generated Text as Text Generation at Unbabel

Working Experience

  • 2023.9 - Now Visiting Researcher, Meta
  • 2023.6 - 2023.8 Intern of Technical Staff, Cohere

Selected Publications

My full list of publications can be found on Google Scholar.

Self-Rewarding Language Models
Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Xian Li, Sainbayar Sukhbaatar, Jing Xu, Jason Weston
ICML 2024paper
System-Level Natural Language Feedback
Weizhe Yuan, Kyunghyun Cho, Jason Weston
EACL 2024code paper
reStructured Pre-training
Weizhe Yuan and Pengfei Liu
ArXiv 2022code paper
DataLab: A Platform for Data Analysis and Intervention
Yang Xiao, Jinlan Fu, Weizhe Yuan, Vijay Viswanathan, Zhoumianze Liu, Yixin Liu, Graham Neubig, Pengfei Liu
ACL 2022code paper
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, Graham Neubig
ACM Computing Surveys 2023code paper
BARTScore: Evaluating Generated Text as Text Generation
Weizhe Yuan, Graham Neubig, Pengfei Liu
NeurIPS 2021code paper
ExplainaBoard: An Explainable Leaderboard for NLP
Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaicheng Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, Zi-Yi Dou, Graham Neubig
ACL 2021 Best Demo Papercode paper
Can We Automate Scientific Reviewing?
Weizhe Yuan, Pengfei Liu, Graham Neubig
JAIR 2022code paper

Education Background

  • Sep. 2022 - Now Ph.D. in Computer and Information Sciences, New York University
  • Sep. 2019 - May. 2021 Master of Computational Data Science, Carnegie Mellon University
  • Feb. 2017 - Jun. 2019 B.E. in Computer Science, Wuhan University, China
  • Sep. 2015 - Jun. 2019 B.E. in Civil Engineering, Wuhan University, China