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Faith-Shap: The Faithful Shapley Interaction Index

2 March 2022

Che-Ping Tsai

Papers citing "Faith-Shap: The Faithful Shapley Interaction Index"

34 / 34 papers shown

Title
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs Landon Butler Abhineet Agarwal Justin Singh Kang Yigit Efe Erginbas Bin Yu Kannan Ramchandran 141 0 0 23 May 2025
SPEX: Scaling Feature Interaction Explanations for LLMs Justin Singh Kang Landon Butler Abhineet Agarwal Yigit Efe Erginbas Ramtin Pedarsani Kannan Ramchandran Bin Yu VLM LRM 162 2 0 20 Feb 2025
Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection Maximilian Spliethover Tim Knebler Fabian Fumagalli Maximilian Muschalik Barbara Hammer Eyke Hüllermeier Henning Wachsmuth 188 1 0 10 Feb 2025
Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory Fabian Fumagalli Maximilian Muschalik Eyke Hüllermeier Barbara Hammer J. Herbinger FAtt 199 4 0 22 Dec 2024
Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey Yunkai Dang Kaichen Huang Jiahao Huo Yibo Yan Shijie Huang ... Kun Wang Yong Liu Jing Shao Hui Xiong Xuming Hu LRM 170 22 0 03 Dec 2024
A Bayesian explanation of machine learning models based on modes and functional ANOVA Quan Long 29 1 0 05 Nov 2024
Why pre-training is beneficial for downstream classification tasks? Xin Jiang Xu Cheng Zechao Li 70 0 0 11 Oct 2024
SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference Yuan Zhang Chun-Kai Fan Junpeng Ma Wenzhao Zheng Tao Huang ... Denis A. Gudovskiy Tomoyuki Okuno Yohei Nakata Kurt Keutzer Shanghang Zhang VLM 68 59 0 06 Oct 2024
shapiq: Shapley Interactions for Machine Learning Maximilian Muschalik Hubert Baniecki Fabian Fumagalli Patrick Kolpaczki Barbara Hammer Eyke Hüllermeier TDI 66 13 0 02 Oct 2024
META-ANOVA: Screening interactions for interpretable machine learning Daniel A. Serino Marc L. Klasky Chanmoo Park Dongha Kim Yongdai Kim 72 0 0 02 Aug 2024
nn2poly: An R Package for Converting Neural Networks into Interpretable Polynomials Pablo Morala Jenny Alexandra Cifuentes R. Lillo Iñaki Ucar 121 0 0 03 Jun 2024
Explaining Graph Neural Networks via Structure-aware Interaction Index Ngoc H. Bui Hieu Trung Nguyen Viet Anh Nguyen Rex Ying FAtt 76 4 0 23 May 2024
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions Fabian Fumagalli Maximilian Muschalik Patrick Kolpaczki Eyke Hüllermeier Barbara Hammer 103 7 0 17 May 2024
Using Shapley interactions to understand how models use structure Divyansh Singhvi Andrej Erkelens Raghav Jain Diganta Misra Isabel Papadimitriou Naomi Saphra 52 0 0 19 Mar 2024
Interpretable Machine Learning for Survival Analysis Sophie Hanna Langbein Mateusz Krzyzinski Mikolaj Spytek Hubert Baniecki P. Biecek Marvin N. Wright 85 2 0 15 Mar 2024
Succinct Interaction-Aware Explanations Sascha Xu Joscha Cuppers Jilles Vreeken FAtt 75 0 0 08 Feb 2024
Learning to Understand: Identifying Interactions via the Möbius Transform Justin Singh Kang Yigit Efe Erginbas Landon Butler Ramtin Pedarsani Kannan Ramchandran 92 4 0 04 Feb 2024
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles Maximilian Muschalik Fabian Fumagalli Barbara Hammer Eyke Hüllermeier TDI 107 18 0 22 Jan 2024
Sample based Explanations via Generalized Representers Che-Ping Tsai Chih-Kuan Yeh Pradeep Ravikumar FAtt 93 9 0 27 Oct 2023
Bayesian Regression Markets Thomas Falconer J. Kazempour Pierre Pinson 145 3 0 23 Oct 2023
Explaining Interactions Between Text Spans Sagnik Ray Choudhury Pepa Atanasova Isabelle Augenstein 56 2 0 20 Oct 2023
Conditional expectation network for SHAP Ronald Richman M. Wüthrich FAtt BDL 47 3 0 20 Jul 2023
Four Axiomatic Characterizations of the Integrated Gradients Attribution Method Daniel Lundstrom Meisam Razaviyayn FAtt 38 3 0 23 Jun 2023
Distributing Synergy Functions: Unifying Game-Theoretic Interaction Methods for Machine-Learning Explainability Daniel Lundstrom Meisam Razaviyayn FAtt 57 1 0 04 May 2023
Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models Qihan Ren Maximilian Brunner Wen Shen S. Mintchev 91 12 0 03 May 2023
Technical Note: Defining and Quantifying AND-OR Interactions for Faithful and Concise Explanation of DNNs Mingjie Li Quanshi Zhang 69 11 0 26 Apr 2023
SHAP-IQ: Unified Approximation of any-order Shapley Interactions Fabian Fumagalli Maximilian Muschalik Patrick Kolpaczki Eyke Hüllermeier Barbara Hammer 127 30 0 02 Mar 2023
Does a Neural Network Really Encode Symbolic Concepts? Mingjie Li Quanshi Zhang 98 31 0 25 Feb 2023
Approximating the Shapley Value without Marginal Contributions Patrick Kolpaczki Viktor Bengs Maximilian Muschalik Eyke Hüllermeier FAtt TDI 156 26 0 01 Feb 2023
Training Data Influence Analysis and Estimation: A Survey Zayd Hammoudeh Daniel Lowd TDI 117 101 0 09 Dec 2022
From Shapley Values to Generalized Additive Models and back Sebastian Bordt U. V. Luxburg FAtt TDI 168 43 0 08 Sep 2022
Unifying local and global model explanations by functional decomposition of low dimensional structures M. Hiabu Josephine T. Meyer Marvin N. Wright FAtt 82 21 0 12 Aug 2022
Defining and Quantifying the Emergence of Sparse Concepts in DNNs Jie Ren Mingjie Li Qirui Chen Huiqi Deng Quanshi Zhang 120 33 0 11 Nov 2021
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.3K 17,197 0 16 Feb 2016