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Saliency-driven Word Alignment Interpretation for Neural Machine
  Translation

Saliency-driven Word Alignment Interpretation for Neural Machine Translation

25 June 2019
Shuoyang Ding
Hainan Xu
Philipp Koehn
ArXivPDFHTML

Papers citing "Saliency-driven Word Alignment Interpretation for Neural Machine Translation"

19 / 19 papers shown
Title
End-to-End Simultaneous Speech Translation with Differentiable
  Segmentation
End-to-End Simultaneous Speech Translation with Differentiable Segmentation
Shaolei Zhang
Yang Feng
23
17
0
25 May 2023
Explaining How Transformers Use Context to Build Predictions
Explaining How Transformers Use Context to Build Predictions
Javier Ferrando
Gerard I. Gállego
Ioannis Tsiamas
Marta R. Costa-jussá
32
31
0
21 May 2023
Understanding and Detecting Hallucinations in Neural Machine Translation
  via Model Introspection
Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection
Weijia Xu
Sweta Agrawal
Eleftheria Briakou
Marianna J. Martindale
Marine Carpuat
HILM
27
46
0
18 Jan 2023
Word Alignment in the Era of Deep Learning: A Tutorial
Word Alignment in the Era of Deep Learning: A Tutorial
Bryan Li
29
5
0
30 Nov 2022
Gradient Knowledge Distillation for Pre-trained Language Models
Gradient Knowledge Distillation for Pre-trained Language Models
Lean Wang
Lei Li
Xu Sun
VLM
23
5
0
02 Nov 2022
Toxicity in Multilingual Machine Translation at Scale
Toxicity in Multilingual Machine Translation at Scale
Marta R. Costa-jussá
Eric Michael Smith
C. Ropers
Daniel Licht
Jean Maillard
Javier Ferrando
Carlos Escolano
30
25
0
06 Oct 2022
Lost in Context? On the Sense-wise Variance of Contextualized Word
  Embeddings
Lost in Context? On the Sense-wise Variance of Contextualized Word Embeddings
Yile Wang
Yue Zhang
19
4
0
20 Aug 2022
Towards Opening the Black Box of Neural Machine Translation: Source and
  Target Interpretations of the Transformer
Towards Opening the Black Box of Neural Machine Translation: Source and Target Interpretations of the Transformer
Javier Ferrando
Gerard I. Gállego
Belen Alastruey
Carlos Escolano
Marta R. Costa-jussá
30
44
0
23 May 2022
Learning to Scaffold: Optimizing Model Explanations for Teaching
Learning to Scaffold: Optimizing Model Explanations for Teaching
Patrick Fernandes
Marcos Vinícius Treviso
Danish Pruthi
André F. T. Martins
Graham Neubig
FAtt
25
22
0
22 Apr 2022
Robust Natural Language Processing: Recent Advances, Challenges, and
  Future Directions
Robust Natural Language Processing: Recent Advances, Challenges, and Future Directions
Marwan Omar
Soohyeon Choi
Daehun Nyang
David A. Mohaisen
32
57
0
03 Jan 2022
Understanding How Encoder-Decoder Architectures Attend
Understanding How Encoder-Decoder Architectures Attend
Kyle Aitken
V. Ramasesh
Yuan Cao
Niru Maheswaranathan
34
17
0
28 Oct 2021
On the Lack of Robust Interpretability of Neural Text Classifiers
On the Lack of Robust Interpretability of Neural Text Classifiers
Muhammad Bilal Zafar
Michele Donini
Dylan Slack
Cédric Archambeau
Sanjiv Ranjan Das
K. Kenthapadi
AAML
11
21
0
08 Jun 2021
The elephant in the interpretability room: Why use attention as
  explanation when we have saliency methods?
The elephant in the interpretability room: Why use attention as explanation when we have saliency methods?
Jasmijn Bastings
Katja Filippova
XAI
LRM
43
173
0
12 Oct 2020
Accurate Word Alignment Induction from Neural Machine Translation
Accurate Word Alignment Induction from Neural Machine Translation
Yun-Nung Chen
Yang Liu
Guanhua Chen
Xin Jiang
Qun Liu
34
60
0
30 Apr 2020
SimAlign: High Quality Word Alignments without Parallel Training Data
  using Static and Contextualized Embeddings
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings
Masoud Jalili Sabet
Philipp Dufter
François Yvon
Hinrich Schütze
23
226
0
18 Apr 2020
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,238
0
24 Jun 2017
Six Challenges for Neural Machine Translation
Six Challenges for Neural Machine Translation
Philipp Koehn
Rebecca Knowles
AAML
AIMat
224
1,208
0
12 Jun 2017
A Decomposable Attention Model for Natural Language Inference
A Decomposable Attention Model for Natural Language Inference
Ankur P. Parikh
Oscar Täckström
Dipanjan Das
Jakob Uszkoreit
213
1,367
0
06 Jun 2016
Effective Approaches to Attention-based Neural Machine Translation
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong
Hieu H. Pham
Christopher D. Manning
218
7,925
0
17 Aug 2015
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