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Tianyu Gao

Princeton University

23 papers hereh-index 2411.8k citations27 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author7
  • middle author15
  • last author1

Across the 23 of 23 papers where every author was matched, so the position is known.

fields
  • cs.CL20
  • cs.LG2
  • cs.IR1
affiliations
  • Princeton University
Homepage
same name
  • Tianyu Gao — 6 papers, h 6
  • Tianyu Gao — 3 papers, h 0
  • Tianyu Gao — 2 papers, h 5
  • Tianyu Gao — 1 paper, h 9
  • Tianyu Gao — 1 paper, h 4
  • Tianyu Gao — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192024
most citedMaking Pre-trained Language Models Better Few-shot Learners

131 citations · 506 across the 23 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CL2019★ 80 cited

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation

Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu +4

Pre-trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, knowledge embedding (KE) methods can effectively represent the relat…

cs.CL2019★ 5 cited

FewRel 2.0: Towards More Challenging Few-Shot Relation Classification

Tianyu Gao, Xu Han, Hao Zhu +4

We present FewRel 2.0, a more challenging task to investigate two aspects of few-shot relation classification models: (1) Can they adapt to a new domain with only a handful of inst…

cs.CL2019★ 7 cited

OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction

Xu Han, Tianyu Gao, Yuan Yao +3

OpenNRE is an open-source and extensible toolkit that provides a unified framework to implement neural models for relation extraction (RE). Specifically, by implementing typical RE…

cs.CL2019★ 7 cited

Neural Snowball for Few-Shot Relation Learning

Tianyu Gao, Xu Han, Ruobing Xie +4

Knowledge graphs typically undergo open-ended growth of new relations. This cannot be well handled by relation extraction that focuses on pre-defined relations with sufficient trai…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.