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Learning to Deceive with Attention-Based Explanations

Learning to Deceive with Attention-Based Explanations

17 September 2019
Danish Pruthi
Mansi Gupta
Bhuwan Dhingra
Graham Neubig
Zachary Chase Lipton
ArXivPDFHTML

Papers citing "Learning to Deceive with Attention-Based Explanations"

50 / 50 papers shown
Title
Regularization, Semi-supervision, and Supervision for a Plausible Attention-Based Explanation
Regularization, Semi-supervision, and Supervision for a Plausible Attention-Based Explanation
Duc Hau Nguyen
Cyrielle Mallart
Guillaume Gravier
Pascale Sébillot
68
0
0
22 Jan 2025
Explanation Regularisation through the Lens of Attributions
Explanation Regularisation through the Lens of Attributions
Pedro Ferreira
Wilker Aziz
Ivan Titov
51
1
0
23 Jul 2024
Why bother with geometry? On the relevance of linear decompositions of
  Transformer embeddings
Why bother with geometry? On the relevance of linear decompositions of Transformer embeddings
Timothee Mickus
Raúl Vázquez
27
2
0
10 Oct 2023
Evaluating Explanation Methods for Vision-and-Language Navigation
Evaluating Explanation Methods for Vision-and-Language Navigation
Guanqi Chen
Lei Yang
Guanhua Chen
Jia Pan
XAI
25
0
0
10 Oct 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
37
32
0
21 May 2023
Faithful Chain-of-Thought Reasoning
Faithful Chain-of-Thought Reasoning
Qing Lyu
Shreya Havaldar
Adam Stein
Li Zhang
D. Rao
Eric Wong
Marianna Apidianaki
Chris Callison-Burch
ReLM
LRM
46
209
0
31 Jan 2023
Tensions Between the Proxies of Human Values in AI
Tensions Between the Proxies of Human Values in AI
Teresa Datta
D. Nissani
Max Cembalest
Akash Khanna
Haley Massa
John P. Dickerson
39
2
0
14 Dec 2022
MEGAN: Multi-Explanation Graph Attention Network
MEGAN: Multi-Explanation Graph Attention Network
Jonas Teufel
Luca Torresi
Patrick Reiser
Pascal Friederich
28
8
0
23 Nov 2022
ViT-CX: Causal Explanation of Vision Transformers
ViT-CX: Causal Explanation of Vision Transformers
Weiyan Xie
Xiao-hui Li
Caleb Chen Cao
Nevin L.Zhang
ViT
37
17
0
06 Nov 2022
Salience Allocation as Guidance for Abstractive Summarization
Salience Allocation as Guidance for Abstractive Summarization
Fei Wang
Kaiqiang Song
Hongming Zhang
Lifeng Jin
Sangwoo Cho
Wenlin Yao
Xiaoyang Wang
Muhao Chen
Dong Yu
60
32
0
22 Oct 2022
StyLEx: Explaining Style Using Human Lexical Annotations
StyLEx: Explaining Style Using Human Lexical Annotations
Shirley Anugrah Hayati
Kyumin Park
Dheeraj Rajagopal
Lyle Ungar
Dongyeop Kang
28
3
0
14 Oct 2022
On the Explainability of Natural Language Processing Deep Models
On the Explainability of Natural Language Processing Deep Models
Julia El Zini
M. Awad
39
82
0
13 Oct 2022
Explanations, Fairness, and Appropriate Reliance in Human-AI
  Decision-Making
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making
Jakob Schoeffer
Maria De-Arteaga
Niklas Kuehl
FaML
55
46
0
23 Sep 2022
How to Dissect a Muppet: The Structure of Transformer Embedding Spaces
How to Dissect a Muppet: The Structure of Transformer Embedding Spaces
Timothee Mickus
Denis Paperno
Mathieu Constant
36
20
0
07 Jun 2022
Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps
Grad-SAM: Explaining Transformers via Gradient Self-Attention Maps
Oren Barkan
Edan Hauon
Avi Caciularu
Ori Katz
Itzik Malkiel
Omri Armstrong
Noam Koenigstein
39
37
0
23 Apr 2022
ProtoTEx: Explaining Model Decisions with Prototype Tensors
ProtoTEx: Explaining Model Decisions with Prototype Tensors
Anubrata Das
Chitrank Gupta
Venelin Kovatchev
Matthew Lease
Junjie Li
39
27
0
11 Apr 2022
Interpretation of Black Box NLP Models: A Survey
Interpretation of Black Box NLP Models: A Survey
Shivani Choudhary
N. Chatterjee
S. K. Saha
FAtt
34
10
0
31 Mar 2022
Measuring the Mixing of Contextual Information in the Transformer
Measuring the Mixing of Contextual Information in the Transformer
Javier Ferrando
Gerard I. Gállego
Marta R. Costa-jussá
36
50
0
08 Mar 2022
POTATO: exPlainable infOrmation exTrAcTion framewOrk
POTATO: exPlainable infOrmation exTrAcTion framewOrk
Adam Kovacs
Kinga Gémes
Eszter Iklódi
Gábor Recski
38
4
0
31 Jan 2022
Counterfactual Explanations for Models of Code
Counterfactual Explanations for Models of Code
Jürgen Cito
Işıl Dillig
V. Murali
S. Chandra
AAML
LRM
32
48
0
10 Nov 2021
Revisiting Methods for Finding Influential Examples
Revisiting Methods for Finding Influential Examples
Karthikeyan K
Anders Søgaard
TDI
22
30
0
08 Nov 2021
Understanding Interlocking Dynamics of Cooperative Rationalization
Understanding Interlocking Dynamics of Cooperative Rationalization
Mo Yu
Yang Zhang
Shiyu Chang
Tommi Jaakkola
29
41
0
26 Oct 2021
Interpreting Deep Learning Models in Natural Language Processing: A
  Review
Interpreting Deep Learning Models in Natural Language Processing: A Review
Xiaofei Sun
Diyi Yang
Xiaoya Li
Tianwei Zhang
Yuxian Meng
Han Qiu
Guoyin Wang
Eduard H. Hovy
Jiwei Li
24
45
0
20 Oct 2021
Evaluating the Faithfulness of Importance Measures in NLP by Recursively
  Masking Allegedly Important Tokens and Retraining
Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining
Andreas Madsen
Nicholas Meade
Vaibhav Adlakha
Siva Reddy
111
35
0
15 Oct 2021
Identifying and Mitigating Spurious Correlations for Improving
  Robustness in NLP Models
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models
Tianlu Wang
Rohit Sridhar
Diyi Yang
Xuezhi Wang
AAML
120
72
0
14 Oct 2021
Automated and Explainable Ontology Extension Based on Deep Learning: A
  Case Study in the Chemical Domain
Automated and Explainable Ontology Extension Based on Deep Learning: A Case Study in the Chemical Domain
A. Memariani
Martin Glauer
Fabian Neuhaus
Till Mossakowski
Janna Hastings
36
5
0
19 Sep 2021
Diagnostics-Guided Explanation Generation
Diagnostics-Guided Explanation Generation
Pepa Atanasova
J. Simonsen
Christina Lioma
Isabelle Augenstein
LRM
FAtt
43
6
0
08 Sep 2021
Enjoy the Salience: Towards Better Transformer-based Faithful
  Explanations with Word Salience
Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience
G. Chrysostomou
Nikolaos Aletras
37
16
0
31 Aug 2021
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation
Lijie Wang
Hao Liu
Shu-ping Peng
Hongxuan Tang
Xinyan Xiao
Ying-Cong Chen
Hua Wu
Haifeng Wang
25
5
0
30 Aug 2021
A Survey on Automated Fact-Checking
A Survey on Automated Fact-Checking
Zhijiang Guo
M. Schlichtkrull
Andreas Vlachos
31
460
0
26 Aug 2021
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks
Thorben Funke
Megha Khosla
Mandeep Rathee
Avishek Anand
FAtt
25
38
0
18 May 2021
Collaborative Graph Learning with Auxiliary Text for Temporal Event
  Prediction in Healthcare
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare
Chang Lu
Chandan K. Reddy
Prithwish Chakraborty
Samantha Kleinberg
Yue Ning
26
58
0
16 May 2021
How Reliable are Model Diagnostics?
How Reliable are Model Diagnostics?
V. Aribandi
Yi Tay
Donald Metzler
19
19
0
12 May 2021
Rationalization through Concepts
Rationalization through Concepts
Diego Antognini
Boi Faltings
FAtt
27
19
0
11 May 2021
Which transformer architecture fits my data? A vocabulary bottleneck in
  self-attention
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies
Yoav Levine
Daniel Jannai
Amnon Shashua
40
20
0
09 May 2021
Improving the Faithfulness of Attention-based Explanations with
  Task-specific Information for Text Classification
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification
G. Chrysostomou
Nikolaos Aletras
32
37
0
06 May 2021
Do Feature Attribution Methods Correctly Attribute Features?
Do Feature Attribution Methods Correctly Attribute Features?
Yilun Zhou
Serena Booth
Marco Tulio Ribeiro
J. Shah
FAtt
XAI
38
132
0
27 Apr 2021
MeSIN: Multilevel Selective and Interactive Network for Medication
  Recommendation
MeSIN: Multilevel Selective and Interactive Network for Medication Recommendation
Yang An
Liang Zhang
Mao You
Xueqing Tian
Bo Jin
Xiaopeng Wei
6
18
0
22 Apr 2021
Making Attention Mechanisms More Robust and Interpretable with Virtual
  Adversarial Training
Making Attention Mechanisms More Robust and Interpretable with Virtual Adversarial Training
Shunsuke Kitada
Hitoshi Iyatomi
AAML
30
8
0
18 Apr 2021
Of Non-Linearity and Commutativity in BERT
Of Non-Linearity and Commutativity in BERT
Sumu Zhao
Damian Pascual
Gino Brunner
Roger Wattenhofer
36
16
0
12 Jan 2021
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and
  Improving Models
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models
Tongshuang Wu
Marco Tulio Ribeiro
Jeffrey Heer
Daniel S. Weld
48
244
0
01 Jan 2021
Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment
  Analysis
Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment Analysis
Sunny Verma
Jiwei Wang
Zhefeng Ge
Rujia Shen
Fan Jin
Yang Wang
Fang Chen
Wei Liu
29
20
0
16 Oct 2020
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
64
175
0
12 Oct 2020
BERTology Meets Biology: Interpreting Attention in Protein Language
  Models
BERTology Meets Biology: Interpreting Attention in Protein Language Models
Jesse Vig
Ali Madani
Lav Varshney
Caiming Xiong
R. Socher
Nazneen Rajani
34
289
0
26 Jun 2020
The Depth-to-Width Interplay in Self-Attention
The Depth-to-Width Interplay in Self-Attention
Yoav Levine
Noam Wies
Or Sharir
Hofit Bata
Amnon Shashua
30
45
0
22 Jun 2020
Staying True to Your Word: (How) Can Attention Become Explanation?
Staying True to Your Word: (How) Can Attention Become Explanation?
Martin Tutek
Jan Snajder
16
27
0
19 May 2020
Quantifying Attention Flow in Transformers
Quantifying Attention Flow in Transformers
Samira Abnar
Willem H. Zuidema
65
779
0
02 May 2020
Sequential Interpretability: Methods, Applications, and Future Direction
  for Understanding Deep Learning Models in the Context of Sequential Data
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data
B. Shickel
Parisa Rashidi
AI4TS
33
17
0
27 Apr 2020
Towards Faithfully Interpretable NLP Systems: How should we define and
  evaluate faithfulness?
Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?
Alon Jacovi
Yoav Goldberg
XAI
48
571
0
07 Apr 2020
On Identifiability in Transformers
On Identifiability in Transformers
Gino Brunner
Yang Liu
Damian Pascual
Oliver Richter
Massimiliano Ciaramita
Roger Wattenhofer
ViT
30
187
0
12 Aug 2019
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