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Understanding Compositional Data Augmentation in Typologically Diverse
  Morphological Inflection

Understanding Compositional Data Augmentation in Typologically Diverse Morphological Inflection

23 May 2023
Farhan Samir
Miikka Silfverberg
ArXivPDFHTML

Papers citing "Understanding Compositional Data Augmentation in Typologically Diverse Morphological Inflection"

16 / 16 papers shown
Title
Structurally Diverse Sampling for Sample-Efficient Training and
  Comprehensive Evaluation
Structurally Diverse Sampling for Sample-Efficient Training and Comprehensive Evaluation
Shivanshu Gupta
Sameer Singh
Matt Gardner
64
7
0
16 Mar 2022
Unobserved Local Structures Make Compositional Generalization Hard
Unobserved Local Structures Make Compositional Generalization Hard
Ben Bogin
Shivanshu Gupta
Jonathan Berant
CoGe
54
33
0
15 Jan 2022
Finding needles in a haystack: Sampling Structurally-diverse Training
  Sets from Synthetic Data for Compositional Generalization
Finding needles in a haystack: Sampling Structurally-diverse Training Sets from Synthetic Data for Compositional Generalization
I. Oren
Jonathan Herzig
Jonathan Berant
55
31
0
06 Sep 2021
(Un)solving Morphological Inflection: Lemma Overlap Artificially
  Inflates Models' Performance
(Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models' Performance
Omer Goldman
David Guriel
Reut Tsarfaty
109
28
0
12 Aug 2021
A Survey of Data Augmentation Approaches for NLP
A Survey of Data Augmentation Approaches for NLP
Steven Y. Feng
Varun Gangal
Jason W. Wei
Sarath Chandar
Soroush Vosoughi
Teruko Mitamura
Eduard H. Hovy
AIMat
96
821
0
07 May 2021
Sequence-Level Mixed Sample Data Augmentation
Sequence-Level Mixed Sample Data Augmentation
Demi Guo
Yoon Kim
Alexander M. Rush
58
100
0
18 Nov 2020
Cold-start Active Learning through Self-supervised Language Modeling
Cold-start Active Learning through Self-supervised Language Modeling
Michelle Yuan
Hsuan-Tien Lin
Jordan L. Boyd-Graber
171
184
0
19 Oct 2020
COGS: A Compositional Generalization Challenge Based on Semantic
  Interpretation
COGS: A Compositional Generalization Challenge Based on Semantic Interpretation
Najoung Kim
Tal Linzen
CoGe
46
279
0
12 Oct 2020
Learning to Recombine and Resample Data for Compositional Generalization
Learning to Recombine and Resample Data for Compositional Generalization
Ekin Akyürek
Afra Feyza Akyürek
Jacob Andreas
59
80
0
08 Oct 2020
Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural
  Machine Translation
Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation
Bryan Eikema
Wilker Aziz
66
135
0
20 May 2020
Applying the Transformer to Character-level Transduction
Applying the Transformer to Character-level Transduction
Shijie Wu
Ryan Cotterell
Mans Hulden
AI4CE
48
106
0
20 May 2020
Pushing the Limits of Low-Resource Morphological Inflection
Pushing the Limits of Low-Resource Morphological Inflection
Antonios Anastasopoulos
Graham Neubig
40
77
0
16 Aug 2019
Good-Enough Compositional Data Augmentation
Good-Enough Compositional Data Augmentation
Jacob Andreas
61
234
0
21 Apr 2019
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Myle Ott
Sergey Edunov
Alexei Baevski
Angela Fan
Sam Gross
Nathan Ng
David Grangier
Michael Auli
VLM
FaML
95
3,147
0
01 Apr 2019
Linguistic generalization and compositionality in modern artificial
  neural networks
Linguistic generalization and compositionality in modern artificial neural networks
Marco Baroni
AI4CE
70
149
0
30 Mar 2019
A Kernel Theory of Modern Data Augmentation
A Kernel Theory of Modern Data Augmentation
Tri Dao
Albert Gu
Alexander J. Ratner
Virginia Smith
Christopher De Sa
Christopher Ré
98
193
0
16 Mar 2018
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