Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability

16 September 2020

Ninghao Liu

Papers citing "Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability"

33 / 33 papers shown

Title
Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness? Alon Jacovi Yoav Goldberg XAI 119 597 0 07 Apr 2020
The POLAR Framework: Polar Opposites Enable Interpretability of Pre-Trained Word Embeddings Binny Mathew Sandipan Sikdar Florian Lemmerich M. Strohmaier 39 36 0 27 Jan 2020
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models Eric Wallace Jens Tuyls Junlin Wang Sanjay Subramanian Matt Gardner Sameer Singh MILM 63 138 0 19 Sep 2019
Attention is not not Explanation Sarah Wiegreffe Yuval Pinter XAI AAML FAtt 120 909 0 13 Aug 2019
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning Fan Yang Mengnan Du Xia Hu XAI ELM 57 67 0 16 Jul 2019
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 81 332 0 19 Jun 2019
Is Attention Interpretable? Sofia Serrano Noah A. Smith 108 684 0 09 Jun 2019
Attention is not Explanation Sarthak Jain Byron C. Wallace FAtt 145 1,324 0 26 Feb 2019
Human-Centered Artificial Intelligence and Machine Learning Mark O. Riedl SyDa 113 267 0 31 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 134 2,551 0 24 Jan 2019
Applying Deep Learning To Airbnb Search Malay Haldar Mustafa Abdool Prashant Ramanathan Tao Xu Shulin Yang ... Qing Zhang Nick Barrow-Williams B. Turnbull Brendan M. Collins Thomas Legrand DML 49 85 0 22 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 94,891 0 11 Oct 2018
Towards Explanation of DNN-based Prediction with Guided Feature Inversion Mengnan Du Ninghao Liu Qingquan Song Xia Hu FAtt 68 127 0 19 Mar 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 214 1,842 0 30 Nov 2017
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 479 20,164 0 30 Oct 2017
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 133 867 0 29 Oct 2017
Dynamic Routing Between Capsules S. Sabour Nicholas Frosst Geoffrey E. Hinton 174 4,596 0 26 Oct 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 201 2,226 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 701 131,652 0 12 Jun 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 74 1,520 0 11 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 210 2,894 0 14 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 188 5,989 0 04 Mar 2017
Understanding Neural Networks through Representation Erasure Jiwei Li Will Monroe Dan Jurafsky AAML MILM 88 565 0 24 Dec 2016
Interpretation of Prediction Models Using the Input Gradient Yotam Hechtlinger FaML AI4CE FAtt 58 85 0 23 Nov 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 303 20,023 0 07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 635 29,076 0 09 Sep 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 180 3,701 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 16,990 0 16 Feb 2016
Character-level Convolutional Networks for Text Classification Xiang Zhang Jiaqi Zhao Yann LeCun 268 6,113 0 04 Sep 2015
Extraction of Salient Sentences from Labelled Documents Misha Denil Alban Demiraj Nando de Freitas 73 137 0 21 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 558 27,311 0 01 Sep 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,295 0 20 Dec 2013