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Circles are like Ellipses, or Ellipses are like Circles? Measuring the
  Degree of Asymmetry of Static and Contextual Embeddings and the Implications
  to Representation Learning

Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation Learning

3 December 2020
Wei Zhang
Murray Campbell
Yang Yu
Sadhana Kumaravel
ArXivPDFHTML

Papers citing "Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation Learning"

3 / 3 papers shown
Title
K-BERT: Enabling Language Representation with Knowledge Graph
K-BERT: Enabling Language Representation with Knowledge Graph
Weijie Liu
Peng Zhou
Zhe Zhao
Zhiruo Wang
Qi Ju
Haotang Deng
Ping Wang
231
778
0
17 Sep 2019
Language Models as Knowledge Bases?
Language Models as Knowledge Bases?
Fabio Petroni
Tim Rocktaschel
Patrick Lewis
A. Bakhtin
Yuxiang Wu
Alexander H. Miller
Sebastian Riedel
KELM
AI4MH
415
2,586
0
03 Sep 2019
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
297
6,956
0
20 Apr 2018
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