Hi~ I am Tianyu Gao, a senior-year undergraduate student from the Department of Computer Science and Technology, Tsinghua University. I am a member of Tsinghua Natural Language Processing and Computational Social Science Lab (THUNLP) and advised by Professor Zhiyuan Liu.

Here is [my CV], and you can find my projects from [my github] and [THUNLP github].


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.


KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu, Zhiyuan Liu, Juanzi Li, Jian Tang.
Arxiv preprint paper

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

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

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

Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
Tianyu Gao*, Xu Han*, Zhiyuan Liu and Maosong Sun. (* indicates equal contribution)
In Proceedings of AAAI 2019 paper code


OpenNRE: An Open-Source Package for Neural Relation Extraction code

  • An open-source toolkit for relation extraction (RE), including sentence-level RE, bag-level RE (distantly-supervised RE) and few-shot RE.
  • Unified framework, modular design, easy to use and very extensible.

NREPapers: A Paper List for Neural Relation Extraction code

  • Include important papers in relation extraction and will continue to be updated.

FewRel: FewRel Dataset, Toolkits and Baseline Models code

  • FewRel is a large-scale few-shot relation extraction dataset.
  • I helped with implementing the toolkits and several baseline models. Also, I led the development of the second version of this dataset (FewRel 2.0).


Tsinghua NLP Lab. As research assistant. Nov. 2017 - Present

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

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

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

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

  • Directed by Dr. Peng Li
  • Research on natural language processing and machine learning.

Momenta. As intern. May 2017 - May 2018

  • Directed by Ji Liang
  • Research on semantic segmentation.