"Why Should I Trust You?": Explaining the Predictions of Any Classifier

16 February 2016

Papers citing ""Why Should I Trust You?": Explaining the Predictions of Any Classifier"

50 / 4,255 papers shown

Title
A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability Pouria Fatemi Ehsan Sharifian Mohammad Hossein Yassaee 43 0 0 05 May 2025
Explainable Face Recognition via Improved Localization Rashik Shadman Daqing Hou Faraz Hussain M. G. Sarwar Murshed CVBM FAtt 31 0 0 04 May 2025
PointExplainer: Towards Transparent Parkinson's Disease Diagnosis Xuechao Wang S. Nõmm Junqing Huang Kadri Medijainen A. Toomela Michael Ruzhansky AAML FAtt 26 0 0 04 May 2025
ABE: A Unified Framework for Robust and Faithful Attribution-Based Explainability Zhiyu Zhu Jiayu Zhang Zhibo Jin Fang Chen Jianlong Zhou FAtt 24 0 0 03 May 2025
Exploring the Impact of Explainable AI and Cognitive Capabilities on Users' Decisions Federico Maria Cau Lucio Davide Spano 31 0 0 02 May 2025
Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methods Mahdi Dhaini Ege Erdogan Nils Feldhus Gjergji Kasneci 51 0 0 02 May 2025
Thinking Outside the Template with Modular GP-GOMEA Joe Harrison Peter A. N. Bosman Tanja Alderliesten 41 0 0 02 May 2025
Explainable AI Based Diagnosis of Poisoning Attacks in Evolutionary Swarms Mehrdad Asadi Roxana Rădulescu Ann Nowé AAML 32 0 0 02 May 2025
Explainable Machine Learning for Cyberattack Identification from Traffic Flows Yujing Zhou Marc L. Jacquet Robel Dawit Skyler Fabre Dev Sarawat ... Yongxin Liu Dahai Liu Hongyun Chen Jian Wang Huihui Wang AAML 24 0 0 02 May 2025
Machine Learning for Cyber-Attack Identification from Traffic Flows Yujing Zhou Marc L. Jacquet Robel Dawit Skyler Fabre Dev Sarawat ... Yongxin Liu Dahai Liu Hongyun Chen Jian Wang Huihui Wang 26 0 0 02 May 2025
Overview and practical recommendations on using Shapley Values for identifying predictive biomarkers via CATE modeling David Svensson Erik Hermansson N. Nikolaou Konstantinos Sechidis Ilya Lipkovich CML 61 0 0 02 May 2025
Computational Identification of Regulatory Statements in EU Legislation Gijs Jan Brandsma Jens Blom-Hansen Christiaan Meijer Kody Moodley AILaw 63 0 0 01 May 2025
Combining LLMs with Logic-Based Framework to Explain MCTS Ziyan An Xia Wang Hendrik Baier Zirong Chen A. Dubey Taylor T. Johnson Jonathan Sprinkle Ayan Mukhopadhyay Meiyi Ma 34 1 0 01 May 2025
Self-Ablating Transformers: More Interpretability, Less Sparsity Jeremias Ferrao Luhan Mikaelson Keenan Pepper Natalia Perez-Campanero Antolin MILM 26 0 0 01 May 2025
CognitionNet: A Collaborative Neural Network for Play Style Discovery in Online Skill Gaming Platform Rukma Talwadker Surajit Chakrabarty Aditya Pareek Tridib Mukherjee Deepak Saini 51 6 0 01 May 2025
IP-CRR: Information Pursuit for Interpretable Classification of Chest Radiology Reports Yuyan Ge Kwan Ho Ryan Chan Pablo Messina René Vidal 43 0 0 30 Apr 2025
RuleKit 2: Faster and simpler rule learning Adam Gudyś Cezary Maszczyk Joanna Badura Adam Grzelak Marek Sikora Łukasz Wróbel AI4TS 19 0 0 29 Apr 2025
Explanations Go Linear: Interpretable and Individual Latent Encoding for Post-hoc Explainability Simone Piaggesi Riccardo Guidotti F. Giannotti D. Pedreschi FAtt LRM 214 0 0 29 Apr 2025
In defence of post-hoc explanations in medical AI Joshua Hatherley Lauritz Munch Jens Christian Bjerring 32 0 0 29 Apr 2025
A Domain-Agnostic Scalable AI Safety Ensuring Framework Beomjun Kim Kangyeon Kim Sunwoo Kim Heejin Ahn 57 0 0 29 Apr 2025
Unsupervised Surrogate Anomaly Detection Simon Klüttermann Tim Katzke Emmanuel Müller 34 0 0 29 Apr 2025
GiBy: A Giant-Step Baby-Step Classifier For Anomaly Detection In Industrial Control Systems Sarad Venugopalan Sridhar Adepu 32 0 0 29 Apr 2025
GMAR: Gradient-Driven Multi-Head Attention Rollout for Vision Transformer Interpretability Sehyeong Jo Gangjae Jang Haesol Park 32 0 0 28 Apr 2025
ODExAI: A Comprehensive Object Detection Explainable AI Evaluation Loc Phuc Truong Nguyen Hung Nguyen Hung Cao 71 0 0 27 Apr 2025
SSA-UNet: Advanced Precipitation Nowcasting via Channel Shuffling Marco Turzi Siamak Mehrkanoon AI4TS 57 0 0 25 Apr 2025
Avoiding Leakage Poisoning: Concept Interventions Under Distribution Shifts M. Zarlenga Gabriele Dominici Pietro Barbiero Z. Shams M. Jamnik KELM 233 0 0 24 Apr 2025
What Makes for a Good Saliency Map? Comparing Strategies for Evaluating Saliency Maps in Explainable AI (XAI) Felix Kares Timo Speith Hanwei Zhang Markus Langer FAtt XAI 38 0 0 23 Apr 2025
Learning Explainable Dense Reward Shapes via Bayesian Optimization Ryan Koo Ian Yang Vipul Raheja Mingyi Hong Kwang-Sung Jun Dongyeop Kang 31 0 0 22 Apr 2025
Intrinsic Barriers to Explaining Deep Foundation Models Zhen Tan Huan Liu AI4CE 22 0 0 21 Apr 2025
Surrogate Fitness Metrics for Interpretable Reinforcement Learning Philipp Altmann Céline Davignon Maximilian Zorn Fabian Ritz Claudia Linnhoff-Popien Thomas Gabor 29 0 0 20 Apr 2025
Walk the Talk? Measuring the Faithfulness of Large Language Model Explanations Katie Matton Robert Osazuwa Ness John Guttag Emre Kıcıman 29 2 0 19 Apr 2025
Mathematical Programming Models for Exact and Interpretable Formulation of Neural Networks Masoud Ataei Edrin Hasaj Jacob Gipp Sepideh Forouzi 22 0 0 19 Apr 2025
Enhancing Multilingual Sentiment Analysis with Explainability for Sinhala, English, and Code-Mixed Content Azmarah Rizvi Navojith Thamindu A.M.N.H. Adhikari W.P.U. Senevirathna Dharshana Kasthurirathna Lakmini Abeywardhana 26 0 0 18 Apr 2025
Probabilistic Stability Guarantees for Feature Attributions Helen Jin Anton Xue Weiqiu You Surbhi Goel Eric Wong 27 0 0 18 Apr 2025
Transformation of audio embeddings into interpretable, concept-based representations Alice Zhang Edison Thomaz Lie Lu 29 0 0 18 Apr 2025
Long-context Non-factoid Question Answering in Indic Languages Ritwik Mishra R. Shah Ponnurangam Kumaraguru 33 0 0 18 Apr 2025
Decoding Vision Transformers: the Diffusion Steering Lens Ryota Takatsuki Sonia Joseph Ippei Fujisawa Ryota Kanai DiffM 30 0 0 18 Apr 2025
Leakage and Interpretability in Concept-Based Models Enrico Parisini Tapabrata Chakraborti Chris Harbron Ben D. MacArthur Christopher R. S. Banerji 40 0 0 18 Apr 2025
Learning to Attribute with Attention Benjamin Cohen-Wang Yung-Sung Chuang Aleksander Madry 30 0 0 18 Apr 2025
PCBEAR: Pose Concept Bottleneck for Explainable Action Recognition Jongseo Lee Wooil Lee Gyeong-Moon Park Seong Tae Kim Jinwoo Choi 35 0 0 17 Apr 2025
Readable Twins of Unreadable Models Krzysztof Pancerz Piotr Kulicki Michał Kalisz Andrzej Burda Maciej Stanisławski Jaromir Sarzyński SyDa 60 0 0 17 Apr 2025
Representation Learning for Tabular Data: A Comprehensive Survey Jun-Peng Jiang Si-Yang Liu Hao-Run Cai Qile Zhou Han-Jia Ye LMTD 53 1 0 17 Apr 2025
Why and How LLMs Hallucinate: Connecting the Dots with Subsequence Associations Yiyou Sun Y. Gai Lijie Chen Abhilasha Ravichander Yejin Choi D. Song HILM 57 0 0 17 Apr 2025
Towards Spatially-Aware and Optimally Faithful Concept-Based Explanations Shubham Kumar Dwip Dalal Narendra Ahuja 26 0 0 15 Apr 2025
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations Indu Panigrahi Sunnie S. Y. Kim Amna Liaqat Rohan Jinturkar Olga Russakovsky Ruth C. Fong Parastoo Abtahi FAtt HAI 59 0 0 14 Apr 2025
GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals Asiful Arefeen Saman Khamesian Maria Adela Grando Bithika Thompson Hassan Ghasemzadeh 46 0 0 14 Apr 2025
Challenges in interpretability of additive models Xinyu Zhang Julien Martinelli S. T. John AAML AI4CE 32 1 0 14 Apr 2025
Explainable Artificial Intelligence techniques for interpretation of food datasets: a review Leonardo Arrighi Ingrid Alves de Moraes Marco Zullich Michele Simonato Douglas Fernandes Barbin Sylvio Barbon Junior 36 0 0 12 Apr 2025
Are We Merely Justifying Results ex Post Facto? Quantifying Explanatory Inversion in Post-Hoc Model Explanations Zhen Tan Song Wang Yifan Li Yu Kong Jundong Li Tianlong Chen Huan Liu FAtt 48 0 0 11 Apr 2025
Beyond Black-Box Predictions: Identifying Marginal Feature Effects in Tabular Transformer Networks Anton Thielmann Arik Reuter Benjamin Saefken LMTD 75 0 0 11 Apr 2025