Meaningfully Debugging Model Mistakes using Conceptual Counterfactual
Explanations

Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanations

24 June 2021

Mert Yuksekgonul

Papers citing "Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanations"

16 / 16 papers shown

Title
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models G. dÉon Jason dÉon J. R. Wright Kevin Leyton-Brown 57 74 0 01 Jul 2021
Dynabench: Rethinking Benchmarking in NLP Douwe Kiela Max Bartolo Yixin Nie Divyansh Kaushik Atticus Geiger ... Pontus Stenetorp Robin Jia Joey Tianyi Zhou Christopher Potts Adina Williams 156 401 0 07 Apr 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 168 1,418 0 14 Dec 2020
A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context V. Rotemberg N. Kurtansky B. Betz‐Stablein L. Caffery E. Chousakos ... George Shih A. Stratigos P. Tschandl Jochen Weber H. Soyer 45 402 0 07 Aug 2020
Learning under Concept Drift: A Review Jie Lu Anjin Liu Fan Dong Feng Gu João Gama Guangquan Zhang AI4TS 55 1,262 0 13 Apr 2020
CheXclusion: Fairness gaps in deep chest X-ray classifiers Laleh Seyyed-Kalantari Guanxiong Liu Matthew B. A. McDermott Irene Y. Chen Marzyeh Ghassemi OOD 74 289 0 14 Feb 2020
Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study Ahmed Alqaraawi M. Schuessler Philipp Weiß Enrico Costanza N. Bianchi-Berthouze AAML FAtt XAI 59 199 0 03 Feb 2020
Counterfactual Visual Explanations Yash Goyal Ziyan Wu Jan Ernst Dhruv Batra Devi Parikh Stefan Lee CML 73 510 0 16 Apr 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison Jeremy Irvin Pranav Rajpurkar M. Ko Yifan Yu Silviana Ciurea-Ilcus ... D. Larson C. Langlotz Bhavik Patel M. Lungren A. Ng 108 2,568 0 21 Jan 2019
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 99 587 0 21 Feb 2018
Detecting and Correcting for Label Shift with Black Box Predictors Zachary Chase Lipton Yu Wang Alex Smola OOD 56 548 0 12 Feb 2018
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks Ruth C. Fong Andrea Vedaldi FAtt 60 264 0 10 Jan 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 94 2,332 0 01 Nov 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 155 2,854 0 14 Mar 2017
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size F. Iandola Song Han Matthew W. Moskewicz Khalid Ashraf W. Dally Kurt Keutzer 132 7,448 0 24 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 214 9,280 0 14 Dec 2015