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Semantic projection: recovering human knowledge of multiple, distinct
  object features from word embeddings
v1v2 (latest)

Semantic projection: recovering human knowledge of multiple, distinct object features from word embeddings

5 February 2018
Gabriel Grand
I. Blank
Francisco Câmara Pereira
Evelina Fedorenko
ArXiv (abs)PDFHTML

Papers citing "Semantic projection: recovering human knowledge of multiple, distinct object features from word embeddings"

7 / 7 papers shown
Title
Theoretical foundations and limits of word embeddings: what types of
  meaning can they capture?
Theoretical foundations and limits of word embeddings: what types of meaning can they capture?
Alina Arseniev-Koehler
68
21
0
22 Jul 2021
Word meaning in minds and machines
Word meaning in minds and machines
Brenden M. Lake
G. Murphy
NAI
112
118
0
04 Aug 2020
Cultural Cartography with Word Embeddings
Cultural Cartography with Word Embeddings
Dustin S. Stoltz
Marshall A. Taylor
57
39
0
09 Jul 2020
Analyzing autoencoder-based acoustic word embeddings
Analyzing autoencoder-based acoustic word embeddings
Yevgen Matusevych
Herman Kamper
Sharon Goldwater
59
12
0
03 Apr 2020
Machine learning as a model for cultural learning: Teaching an algorithm
  what it means to be fat
Machine learning as a model for cultural learning: Teaching an algorithm what it means to be fat
Alina Arseniev-Koehler
J. Foster
84
49
0
24 Mar 2020
Word Embeddings Inherently Recover the Conceptual Organization of the
  Human Mind
Word Embeddings Inherently Recover the Conceptual Organization of the Human Mind
Victor Swift
21
0
0
06 Feb 2020
Context Matters: Recovering Human Semantic Structure from Machine
  Learning Analysis of Large-Scale Text Corpora
Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large-Scale Text Corpora
M. C. Iordan
Tyler Giallanza
C. Ellis
Nicole M. Beckage
Jonathan Cohen
35
10
0
15 Oct 2019
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