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Considering Likelihood in NLP Classification Explanations with Occlusion
  and Language Modeling

Considering Likelihood in NLP Classification Explanations with Occlusion and Language Modeling

21 April 2020
David Harbecke
Christoph Alt
ArXivPDFHTML

Papers citing "Considering Likelihood in NLP Classification Explanations with Occlusion and Language Modeling"

7 / 7 papers shown
Title
Attention is not not Explanation
Attention is not not Explanation
Sarah Wiegreffe
Yuval Pinter
XAI
AAML
FAtt
24
901
0
13 Aug 2019
Attention is not Explanation
Attention is not Explanation
Sarthak Jain
Byron C. Wallace
FAtt
76
1,307
0
26 Feb 2019
Neural Network Acceptability Judgments
Neural Network Acceptability Judgments
Alex Warstadt
Amanpreet Singh
Samuel R. Bowman
128
1,390
0
31 May 2018
A Broad-Coverage Challenge Corpus for Sentence Understanding through
  Inference
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams
Nikita Nangia
Samuel R. Bowman
315
4,444
0
18 Apr 2017
Learning Important Features Through Propagating Activation Differences
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
62
3,848
0
10 Apr 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
63
5,920
0
04 Mar 2017
Not Just a Black Box: Learning Important Features Through Propagating
  Activation Differences
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Shcherbina
A. Kundaje
FAtt
36
782
0
05 May 2016
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