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Do NLP Models Know Numbers? Probing Numeracy in Embeddings

Do NLP Models Know Numbers? Probing Numeracy in Embeddings

17 September 2019
Eric Wallace
Yizhong Wang
Sujian Li
Sameer Singh
Matt Gardner
ArXivPDFHTML

Papers citing "Do NLP Models Know Numbers? Probing Numeracy in Embeddings"

14 / 64 papers shown
Title
Investigating the Limitations of Transformers with Simple Arithmetic
  Tasks
Investigating the Limitations of Transformers with Simple Arithmetic Tasks
Rodrigo Nogueira
Zhiying Jiang
Jimmy J. Li
LRM
24
123
0
25 Feb 2021
Data-to-text Generation with Macro Planning
Data-to-text Generation with Macro Planning
Ratish Puduppully
Mirella Lapata
63
73
0
04 Feb 2021
Seeing past words: Testing the cross-modal capabilities of pretrained
  V&L models on counting tasks
Seeing past words: Testing the cross-modal capabilities of pretrained V&L models on counting tasks
Letitia Parcalabescu
Albert Gatt
Anette Frank
Iacer Calixto
LRM
33
48
0
22 Dec 2020
Trex: Learning Execution Semantics from Micro-Traces for Binary
  Similarity
Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity
Kexin Pei
Zhou Xuan
Junfeng Yang
Suman Jana
Baishakhi Ray
27
89
0
16 Dec 2020
Infusing Finetuning with Semantic Dependencies
Infusing Finetuning with Semantic Dependencies
Zhaofeng Wu
Hao Peng
Noah A. Smith
25
37
0
10 Dec 2020
An Empirical Investigation of Contextualized Number Prediction
An Empirical Investigation of Contextualized Number Prediction
Daniel M. Spokoyny
Taylor Berg-Kirkpatrick
AI4TS
27
34
0
20 Oct 2020
Bootleg: Chasing the Tail with Self-Supervised Named Entity
  Disambiguation
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
Laurel J. Orr
Megan Leszczynski
Simran Arora
Sen Wu
Neel Guha
Xiao Ling
Christopher Ré
143
48
0
20 Oct 2020
Understanding tables with intermediate pre-training
Understanding tables with intermediate pre-training
Julian Martin Eisenschlos
Syrine Krichene
Thomas Müller
LMTD
18
119
0
01 Oct 2020
INFOTABS: Inference on Tables as Semi-structured Data
INFOTABS: Inference on Tables as Semi-structured Data
Vivek Gupta
Maitrey Mehta
Pegah Nokhiz
Vivek Srikumar
LMTD
25
100
0
13 May 2020
Natural Language Premise Selection: Finding Supporting Statements for
  Mathematical Text
Natural Language Premise Selection: Finding Supporting Statements for Mathematical Text
Deborah Ferreira
André Freitas
AIMat
17
32
0
30 Apr 2020
TAPAS: Weakly Supervised Table Parsing via Pre-training
TAPAS: Weakly Supervised Table Parsing via Pre-training
Jonathan Herzig
Pawel Krzysztof Nowak
Thomas Müller
Francesco Piccinno
Julian Martin Eisenschlos
LMTD
RALM
45
634
0
05 Apr 2020
oLMpics -- On what Language Model Pre-training Captures
oLMpics -- On what Language Model Pre-training Captures
Alon Talmor
Yanai Elazar
Yoav Goldberg
Jonathan Berant
LRM
34
300
0
31 Dec 2019
Learning Numeral Embeddings
Learning Numeral Embeddings
Chengyue Jiang
Zhonglin Nian
Kaihao Guo
Shanbo Chu
Yinggong Zhao
Libin Shen
Kewei Tu
30
20
0
28 Dec 2019
What you can cram into a single vector: Probing sentence embeddings for
  linguistic properties
What you can cram into a single vector: Probing sentence embeddings for linguistic properties
Alexis Conneau
Germán Kruszewski
Guillaume Lample
Loïc Barrault
Marco Baroni
201
883
0
03 May 2018
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