BERTology Meets Biology: Interpreting Attention in Protein Language
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BERTology Meets Biology: Interpreting Attention in Protein Language Models

26 June 2020

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Papers citing "BERTology Meets Biology: Interpreting Attention in Protein Language Models"

12 / 62 papers shown

Title
Pathologies of Neural Models Make Interpretations Difficult Shi Feng Eric Wallace Alvin Grissom II Mohit Iyyer Pedro Rodriguez Jordan L. Boyd-Graber AAML FAtt 79 321 0 20 Apr 2018
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 353 204 0 06 Jul 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 204 2,235 0 12 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 728 132,199 0 12 Jun 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 213 2,899 0 14 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 191 6,015 0 04 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 405 3,809 0 28 Feb 2017
Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks Yossi Adi Einat Kermany Yonatan Belinkov Ofer Lavi Yoav Goldberg 76 546 0 15 Aug 2016
Rationalizing Neural Predictions Tao Lei Regina Barzilay Tommi Jaakkola 118 812 0 13 Jun 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,706 0 10 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,027 0 16 Feb 2016
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 397 33,550 0 16 Oct 2013

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