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On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness,
  and Semantic Evaluation

On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation

Annual Meeting of the Association for Computational Linguistics (ACL), 2021
9 June 2021
Wei Zhang
Ziming Huang
Yada Zhu
Guangnan Ye
Xiaodong Cui
Fan Zhang
ArXiv (abs)PDFHTML

Papers citing "On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation"

9 / 9 papers shown
Title
Differential Privacy, Linguistic Fairness, and Training Data Influence:
  Impossibility and Possibility Theorems for Multilingual Language Models
Differential Privacy, Linguistic Fairness, and Training Data Influence: Impossibility and Possibility Theorems for Multilingual Language ModelsInternational Conference on Machine Learning (ICML), 2023
Phillip Rust
Anders Søgaard
134
6
0
17 Aug 2023
Improved Target-specific Stance Detection on Social Media Platforms by
  Delving into Conversation Threads
Improved Target-specific Stance Detection on Social Media Platforms by Delving into Conversation ThreadsIEEE Transactions on Computational Social Systems (IEEE TCSS), 2022
Yupeng Li
Haorui He
Shaonan Wang
F. Lau
Yunya Song
149
22
0
06 Nov 2022
Influence Functions for Sequence Tagging Models
Influence Functions for Sequence Tagging ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Sarthak Jain
Varun Manjunatha
Byron C. Wallace
A. Nenkova
TDI
163
9
0
25 Oct 2022
Adapting and Evaluating Influence-Estimation Methods for
  Gradient-Boosted Decision Trees
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision TreesJournal of machine learning research (JMLR), 2022
Jonathan Brophy
Zayd Hammoudeh
Daniel Lowd
TDI
320
25
0
30 Apr 2022
Diagnosing AI Explanation Methods with Folk Concepts of Behavior
Diagnosing AI Explanation Methods with Folk Concepts of BehaviorConference on Fairness, Accountability and Transparency (FAccT), 2022
Alon Jacovi
Jasmijn Bastings
Sebastian Gehrmann
Yoav Goldberg
Katja Filippova
331
20
0
27 Jan 2022
AI Explainability 360: Impact and Design
AI Explainability 360: Impact and DesignAAAI Conference on Artificial Intelligence (AAAI), 2021
Vijay Arya
Rachel K. E. Bellamy
Pin-Yu Chen
Amit Dhurandhar
Michael Hind
...
Karthikeyan Shanmugam
Moninder Singh
Kush R. Varshney
Dennis L. Wei
Yunfeng Zhang
143
20
0
24 Sep 2021
Explaining Deep Learning Representations by Tracing the Training Process
Explaining Deep Learning Representations by Tracing the Training Process
Lukas Pfahler
K. Morik
FAtt
69
2
0
13 Sep 2021
Flexible Instance-Specific Rationalization of NLP Models
Flexible Instance-Specific Rationalization of NLP ModelsAAAI Conference on Artificial Intelligence (AAAI), 2021
G. Chrysostomou
Nikolaos Aletras
209
15
0
16 Apr 2021
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAttFaML
1.9K
19,183
0
16 Feb 2016
1