Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations

10 March 2017

Finale Doshi-Velez

Papers citing "Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations"

50 / 75 papers shown

Title
Large Language Models as Attribution Regularizers for Efficient Model Training Davor Vukadin Marin Šilić Goran Delač 36 0 0 27 Feb 2025
Diagnosing COVID-19 Severity from Chest X-Ray Images Using ViT and CNN Architectures Luis Lara Lucia Eve Berger Rajesh Raju ViT 30 0 0 23 Feb 2025
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable Shreyash Arya Sukrut Rao Moritz Bohle Bernt Schiele 68 2 0 28 Jan 2025
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers Lam Nguyen Tung Steven Cho Xiaoning Du Neelofar Neelofar Valerio Terragni Stefano Ruberto Aldeida Aleti 71 2 0 30 Oct 2024
Problem Solving Through Human-AI Preference-Based Cooperation Subhabrata Dutta Timo Kaufmann Goran Glavas Ivan Habernal Kristian Kersting Frauke Kreuter Mira Mezini Iryna Gurevych Eyke Hüllermeier Hinrich Schuetze 82 1 0 14 Aug 2024
Language-guided Detection and Mitigation of Unknown Dataset Bias Zaiying Zhao Soichiro Kumano Toshihiko Yamasaki 34 2 0 05 Jun 2024
AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems Clara Punzi Roberto Pellungrini Mattia Setzu F. Giannotti D. Pedreschi 15 5 0 09 Feb 2024
Identifying Spurious Correlations using Counterfactual Alignment Joseph Paul Cohen Louis Blankemeier Akshay S. Chaudhari CML 49 1 0 01 Dec 2023
Improving Interpretation Faithfulness for Vision Transformers Lijie Hu Yixin Liu Ninghao Liu Mengdi Huai Lichao Sun Di Wang 15 5 0 29 Nov 2023
Explaining high-dimensional text classifiers Odelia Melamed Rich Caruana 6 0 0 22 Nov 2023
SCAAT: Improving Neural Network Interpretability via Saliency Constrained Adaptive Adversarial Training Rui Xu Wenkang Qin Peixiang Huang Hao Wang Lin Luo FAtt AAML 14 2 0 09 Nov 2023
Interpretability-Aware Vision Transformer Yao Qiang Chengyin Li Prashant Khanduri D. Zhu ViT 77 7 0 14 Sep 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods Robin Hesse Simone Schaub-Meyer Stefan Roth AAML 27 32 0 11 Aug 2023
Unlearning Spurious Correlations in Chest X-ray Classification Misgina Tsighe Hagos Kathleen M. Curran Brian Mac Namee CML OOD 10 0 0 02 Aug 2023
Mitigating Bias: Enhancing Image Classification by Improving Model Explanations Raha Ahmadi Mohammad Javad Rajabi Mohammad Khalooiem Mohammad Sabokrou 19 0 0 04 Jul 2023
Learning Differentiable Logic Programs for Abstract Visual Reasoning Hikaru Shindo Viktor Pfanschilling D. Dhami Kristian Kersting NAI 19 6 0 03 Jul 2023
One Explanation Does Not Fit XIL Felix Friedrich David Steinmann Kristian Kersting LRM 32 2 0 14 Apr 2023
Are Data-driven Explanations Robust against Out-of-distribution Data? Tang Li Fengchun Qiao Mengmeng Ma Xiangkai Peng OODD OOD 28 10 0 29 Mar 2023
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 19 6 0 25 Mar 2023
Towards Learning and Explaining Indirect Causal Effects in Neural Networks Abbaavaram Gowtham Reddy Saketh Bachu Harsh Nilesh Pathak Ben Godfrey V. Balasubramanian V. Varshaneya Satya Narayanan Kar CML 26 0 0 24 Mar 2023
Towards Explaining Subjective Ground of Individuals on Social Media Younghun Lee Dan Goldwasser 12 1 0 18 Nov 2022
XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models Dong-Ho Lee Akshen Kadakia Brihi Joshi Aaron Chan Ziyi Liu ... Takashi Shibuya Ryosuke Mitani Toshiyuki Sekiya Jay Pujara Xiang Ren LRM 22 9 0 30 Oct 2022
Revision Transformers: Instructing Language Models to Change their Values Felix Friedrich Wolfgang Stammer P. Schramowski Kristian Kersting KELM 14 6 0 19 Oct 2022
Equivariant and Invariant Grounding for Video Question Answering Yicong Li Xiang Wang Junbin Xiao Tat-Seng Chua 14 25 0 26 Jul 2022
RES: A Robust Framework for Guiding Visual Explanation Yuyang Gao Tong Sun Guangji Bai Siyi Gu S. Hong Liang Zhao FAtt AAML XAI 16 31 0 27 Jun 2022
The Importance of Background Information for Out of Distribution Generalization Jupinder Parmar Khaled Kamal Saab Brian Pogatchnik D. Rubin Christopher Ré OOD 11 0 0 17 Jun 2022
Optimizing Relevance Maps of Vision Transformers Improves Robustness Hila Chefer Idan Schwartz Lior Wolf ViT 14 37 0 02 Jun 2022
Learning to Ignore Adversarial Attacks Yiming Zhang Yan Zhou Samuel Carton Chenhao Tan 41 2 0 23 May 2022
Perspectives on Incorporating Expert Feedback into Model Updates Valerie Chen Umang Bhatt Hoda Heidari Adrian Weller Ameet Talwalkar 30 11 0 13 May 2022
Dynamically Refined Regularization for Improving Cross-corpora Hate Speech Detection Tulika Bose Nikolaos Aletras Irina Illina Dominique Fohr 40 5 0 23 Mar 2022
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment Yuyang Gao Tong Sun Liang Zhao Sungsoo Ray Hong HAI 13 37 0 06 Feb 2022
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement Xiaoting Shao Karl Stelzner Kristian Kersting CML DRL 22 3 0 01 Feb 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 6 1 0 30 Jan 2022
Making a (Counterfactual) Difference One Rationale at a Time Michael J. Plyler Michal Green Min Chi 16 10 0 13 Jan 2022
Towards Relatable Explainable AI with the Perceptual Process Wencan Zhang Brian Y. Lim AAML XAI 9 61 0 28 Dec 2021
What to Learn, and How: Toward Effective Learning from Rationales Samuel Carton Surya Kanoria Chenhao Tan 10 22 0 30 Nov 2021
Improving Deep Learning Interpretability by Saliency Guided Training Aya Abdelsalam Ismail H. C. Bravo S. Feizi FAtt 16 78 0 29 Nov 2021
Matching Learned Causal Effects of Neural Networks with Domain Priors Sai Srinivas Kancheti Abbavaram Gowtham Reddy V. Balasubramanian Amit Sharma CML 6 11 0 24 Nov 2021
Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features Haohan Wang Zeyi Huang Hanlin Zhang Yong Jae Lee Eric P. Xing OOD 122 16 0 05 Nov 2021
Modeling Techniques for Machine Learning Fairness: A Survey Mingyang Wan Daochen Zha Ninghao Liu Na Zou SyDa FaML 17 36 0 04 Nov 2021
Equality of opportunity in travel behavior prediction with deep neural networks and discrete choice models Yunhan Zheng Shenhao Wang Jinhuan Zhao HAI 9 26 0 25 Sep 2021
Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience G. Chrysostomou Nikolaos Aletras 13 16 0 31 Aug 2021
Improving the trustworthiness of image classification models by utilizing bounding-box annotations K. Dharma Chicheng Zhang 17 5 0 15 Aug 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey A. Hengel 17 86 0 12 May 2021
Shapley Explanation Networks Rui Wang Xiaoqian Wang David I. Inouye TDI FAtt 9 44 0 06 Apr 2021
Efficient Explanations from Empirical Explainers Robert Schwarzenberg Nils Feldhus Sebastian Möller FAtt 15 9 0 29 Mar 2021
Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Do P. Schramowski Cigdem Turan Nico Andersen Constantin Rothkopf Kristian Kersting 17 280 0 08 Mar 2021
EnD: Entangling and Disentangling deep representations for bias correction Enzo Tartaglione C. Barbano Marco Grangetto 11 124 0 02 Mar 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 17 94 0 02 Mar 2021
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays Joseph Paul Cohen Rupert Brooks Sovann En Evan Zucker Anuj Pareek M. Lungren Akshay S. Chaudhari FAtt MedIm 15 4 0 18 Feb 2021