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Many Faces of Feature Importance: Comparing Built-in and Post-hoc
  Feature Importance in Text Classification

Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification

18 October 2019
Vivian Lai
Zheng Jon Cai
Chenhao Tan
    FAtt
ArXivPDFHTML

Papers citing "Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification"

17 / 17 papers shown
Title
Attention is not not Explanation
Attention is not not Explanation
Sarah Wiegreffe
Yuval Pinter
XAI
AAML
FAtt
118
909
0
13 Aug 2019
Is Attention Interpretable?
Is Attention Interpretable?
Sofia Serrano
Noah A. Smith
101
683
0
09 Jun 2019
Attention is not Explanation
Attention is not Explanation
Sarthak Jain
Byron C. Wallace
FAtt
128
1,323
0
26 Feb 2019
On Human Predictions with Explanations and Predictions of Machine
  Learning Models: A Case Study on Deception Detection
On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection
Vivian Lai
Chenhao Tan
73
377
0
19 Nov 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLM
SSL
SSeg
1.7K
94,729
0
11 Oct 2018
A Survey Of Methods For Explaining Black Box Models
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
124
3,954
0
06 Feb 2018
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
672
131,414
0
12 Jun 2017
A Unified Approach to Interpreting Model Predictions
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
1.1K
21,864
0
22 May 2017
Learning Important Features Through Propagating Activation Differences
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
192
3,869
0
10 Apr 2017
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
388
3,785
0
28 Feb 2017
The Mythos of Model Interpretability
The Mythos of Model Interpretability
Zachary Chase Lipton
FaML
176
3,690
0
10 Jun 2016
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
774
38,735
0
09 Mar 2016
"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
FAtt
FaML
1.2K
16,954
0
16 Feb 2016
Effective Approaches to Attention-based Neural Machine Translation
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong
Hieu H. Pham
Christopher D. Manning
374
7,959
0
17 Aug 2015
Visualizing and Understanding Neural Models in NLP
Visualizing and Understanding Neural Models in NLP
Jiwei Li
Xinlei Chen
Eduard H. Hovy
Dan Jurafsky
MILM
FAtt
75
706
0
02 Jun 2015
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
533
27,295
0
01 Sep 2014
Finding Deceptive Opinion Spam by Any Stretch of the Imagination
Finding Deceptive Opinion Spam by Any Stretch of the Imagination
Myle Ott
Yejin Choi
Claire Cardie
Jeffrey T. Hancock
74
1,386
0
22 Jul 2011
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