Hi~ I am Tianyu Gao, a first-year PhD student at Princeton University, advised by Prof. Danqi Chen. Before joining Princeton, I received my bachelor degree at Tsinghua University. During my time at Tsinghua, I was a member of THUNLP and was advised by Prof. Zhiyuan Liu. Here is my CV.

Find me at twitter, google scholar, and github!

Email: tianyug@cs.princeton.edu

Research


My research interests lie within the intersection of natural language processing and machine learning. More specifically, my research interests include:

  • Training NLP models with fewer annotations. Annotations for language are expensive to gather, so it is meaningful to develop models and algorithms that learn more efficiently.
    • Human can grasp new knowledge with only a handful of examples. So can machines. Few-shot learning aims at guiding models to learn new tasks with limited data.
    • There are huge amounts of unlabeled data on the Internet and we can utilize them with unsupervised / semi-supervised training, like pretraining language models or bootstrapping from a few seeds of annotations.
    • Existing structured information can act as an external knowledge for NLP models, like knowledge graphs in distant supervision relation extraction.
    • I explore the above aspects mainly in the field of information extraction, an important area in NLP.

Highlighted Publications


Please refer to my publications for the full list.

Tianyu Gao*, Xingcheng Yao*, Danqi Chen (* indicates equal contribution)
SimCSE: Simple Contrastive Learning of Sentence Embeddings
Arxiv preprint, 2021 pdf code

Tianyu Gao*, Adam Fisch*, Danqi Chen (* indicates equal contribution)
Making Pre-trained Language Models Better Few-shot Learners
Arxiv preprint, 2021 pdf code

Hao Peng*, Tianyu Gao*, Xu Han, Yankai Lin, Peng Li, Zhiyuan Liu, Maosong Sun, Jie Zhou (* indicates equal contribution)
Learning from Context or Names? An Empirical Study on Neural Relation Extraction
Proceedings of EMNLP, 2020 pdf code

Xu Han*, Tianyu Gao*, Yankai Lin*, Hao Peng, Yaoliang Yang, Chaojun Xiao, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou (* indicates equal contribution)
More Data, More Relations, More Context and More Openness: A Review and Outlook for Relation Extraction
Proceedings of AACL, 2020 pdf

Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu, Zhiyuan Liu, Juanzi Li, Jian Tang
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Proceedings of TACL, 2020 pdf

Tianyu Gao, Xu Han, Ruobing Xie, Zhiyuan Liu, Fen Lin, Leyu Lin, Maosong Sun
Neural Snowball for Few-Shot Relation Learning
Proceedings of AAAI, 2020 pdf code

Tianyu Gao, Xu Han, Hao Zhu, Zhiyuan Liu, Peng Li, Maosong Sun, Jie Zhou
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
Proceedings of EMNLP (Short Paper), 2019 pdf code

Xu Han*, Tianyu Gao*, Yuan Yao, Deming Ye, Zhiyuan Liu, Maosong Sun (* indicates equal contribution)
OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction
Proceedings of EMNLP (Demonstration Track), 2019 pdf code

Experiences


Princeton NLP group. As PhD student. Aug. 2020 - Present

  • Advised by Prof. Danqi Chen.
  • Research on natural language processing.

Tsinghua NLP Lab. As research assistant. Nov. 2017 - May 2020

  • Advised by Prof. Zhiyuan Liu.
  • Research on natural language processing and machine learning.

Mila-Quebec AI Institute. As Research Intern. July 2019 - Sept. 2019

  • Mentor: Prof. Jian Tang.
  • Research on knowledge graph embedding and pre-training language models.

WeChat AI, Tencent. Tencent Rhino-Bird Elite Training Program. May 2019 - May 2020

  • Mentor: Dr. Peng Li.
  • Research on natural language processing and machine learning.

Momenta. As intern. May 2017 - May 2018

  • Mentor: Dr. Ji Liang.
  • Research on semantic segmentation.