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Analyzing machine-learned representations: A natural language case study

Analyzing machine-learned representations: A natural language case study

12 September 2019
Ishita Dasgupta
Demi Guo
S. Gershman
Noah D. Goodman
    NAI
ArXiv (abs)PDFHTML

Papers citing "Analyzing machine-learned representations: A natural language case study"

7 / 7 papers shown
Title
Representation in large language models
Cameron C. Yetman
101
1
0
03 Jan 2025
Probing BERT's priors with serial reproduction chains
Probing BERT's priors with serial reproduction chains
Takateru Yamakoshi
Thomas Griffiths
Robert D. Hawkins
84
13
0
24 Feb 2022
Distinguishing rule- and exemplar-based generalization in learning
  systems
Distinguishing rule- and exemplar-based generalization in learning systems
Ishita Dasgupta
Erin Grant
Thomas Griffiths
88
16
0
08 Oct 2021
Measuring Systematic Generalization in Neural Proof Generation with
  Transformers
Measuring Systematic Generalization in Neural Proof Generation with Transformers
Nicolas Angelard-Gontier
Koustuv Sinha
Siva Reddy
C. Pal
LRM
106
64
0
30 Sep 2020
Probing Linguistic Systematicity
Probing Linguistic Systematicity
Emily Goodwin
Koustuv Sinha
Timothy J. O'Donnell
146
58
0
08 May 2020
Discovering the Compositional Structure of Vector Representations with
  Role Learning Networks
Discovering the Compositional Structure of Vector Representations with Role Learning Networks
Paul Soulos
R. Thomas McCoy
Tal Linzen
P. Smolensky
CoGe
132
44
0
21 Oct 2019
Generating Natural Adversarial Examples
Generating Natural Adversarial Examples
Zhengli Zhao
Dheeru Dua
Sameer Singh
GANAAML
203
601
0
31 Oct 2017
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