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Fine-grained Interpretation and Causation Analysis in Deep NLP Models
v1v2 (latest)

Fine-grained Interpretation and Causation Analysis in Deep NLP Models

North American Chapter of the Association for Computational Linguistics (NAACL), 2021
17 May 2021
Hassan Sajjad
Narine Kokhlikyan
Fahim Dalvi
Nadir Durrani
    MILM
ArXiv (abs)PDFHTML

Papers citing "Fine-grained Interpretation and Causation Analysis in Deep NLP Models"

5 / 5 papers shown
Computational modeling of semantic change
Computational modeling of semantic changeConference of the European Chapter of the Association for Computational Linguistics (EACL), 2023
Nina Tahmasebi
Haim Dubossarsky
351
8
0
13 Apr 2023
Analyzing Encoded Concepts in Transformer Language Models
Analyzing Encoded Concepts in Transformer Language ModelsNorth American Chapter of the Association for Computational Linguistics (NAACL), 2022
Hassan Sajjad
Nadir Durrani
Fahim Dalvi
Firoj Alam
A. Khan
Jia Xu
209
58
0
27 Jun 2022
A Multilingual Perspective Towards the Evaluation of Attribution Methods
  in Natural Language Inference
A Multilingual Perspective Towards the Evaluation of Attribution Methods in Natural Language InferenceConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Kerem Zaman
Yonatan Belinkov
258
8
0
11 Apr 2022
Measuring the Mixing of Contextual Information in the Transformer
Measuring the Mixing of Contextual Information in the TransformerConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Javier Ferrando
Gerard I. Gállego
Marta R. Costa-jussá
345
73
0
08 Mar 2022
"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
2.6K
20,717
0
16 Feb 2016
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