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Lost in Machine Translation: A Method to Reduce Meaning Loss

Lost in Machine Translation: A Method to Reduce Meaning Loss

25 February 2019
Reuben Cohn-Gordon
Noah D. Goodman
ArXivPDFHTML

Papers citing "Lost in Machine Translation: A Method to Reduce Meaning Loss"

5 / 5 papers shown
Title
Generating Pragmatic Examples to Train Neural Program Synthesizers
Generating Pragmatic Examples to Train Neural Program Synthesizers
Saujas Vaduguru
Daniel Fried
Yewen Pu
NAI
32
5
0
09 Nov 2023
Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling
  Approaches
Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches
Daniel Fried
Nicholas Tomlin
Jennifer Hu
Roma Patel
Aida Nematzadeh
29
6
0
15 Nov 2022
Perspective-taking and Pragmatics for Generating Empathetic Responses
  Focused on Emotion Causes
Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes
Hyunwoo J. Kim
Byeongchang Kim
Gunhee Kim
42
67
0
18 Sep 2021
A practical introduction to the Rational Speech Act modeling framework
A practical introduction to the Rational Speech Act modeling framework
Gregory Scontras
Michael Henry Tessler
Michael Franke
20
13
0
20 May 2021
Mutual exclusivity as a challenge for deep neural networks
Mutual exclusivity as a challenge for deep neural networks
Kanishk Gandhi
Brenden M. Lake
39
14
0
24 Jun 2019
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