{"total":146,"rows":[{"id":"2110.14049","title":"Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning","created":"2021-10-26","cited_by_count":165,"area":null},{"id":"2107.07436","title":"FastSHAP: Real-Time Shapley Value Estimation","created":"2021-07-15","cited_by_count":125,"area":null},{"id":"2207.07605","title":"Algorithms to estimate Shapley value feature attributions","created":"2022-07-15","cited_by_count":115,"area":null},{"id":"2202.05594","title":"The Shapley Value in Machine Learning","created":"2022-02-11","cited_by_count":98,"area":null},{"id":"2203.00870","title":"Faith-Shap: The Faithful Shapley Interaction Index","created":"2022-03-02","cited_by_count":69,"area":null},{"id":"2202.01875","title":"Rethinking Explainability as a Dialogue: A Practitioner's Perspective","created":"2022-02-03","cited_by_count":52,"area":null},{"id":"2303.01179","title":"SHAP-IQ: Unified Approximation of any-order Shapley Interactions","created":"2023-03-02","cited_by_count":51,"area":null},{"id":"2206.10013","title":"Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments","created":"2022-06-20","cited_by_count":50,"area":null},{"id":"2206.05282","title":"Learning to Estimate Shapley Values with Vision Transformers","created":"2022-06-10","cited_by_count":45,"area":null},{"id":"2402.05406","title":"Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes","created":"2024-02-08","cited_by_count":43,"area":null},{"id":"2410.01649","title":"shapiq: Shapley Interactions for Machine Learning","created":"2024-10-02","cited_by_count":43,"area":null},{"id":"2105.00108","title":"Explaining a Series of Models by Propagating Shapley Values","created":"2021-04-30","cited_by_count":37,"area":null},{"id":"2305.10289","title":"Explain Any Concept: Segment Anything Meets Concept-Based Explanation","created":"2023-05-17","cited_by_count":37,"area":null},{"id":"2111.06206","title":"Defining and Quantifying the Emergence of Sparse Concepts in DNNs","created":"2021-11-11","cited_by_count":36,"area":null},{"id":"2209.13429","title":"WeightedSHAP: analyzing and improving Shapley based feature attributions","created":"2022-09-27","cited_by_count":36,"area":null},{"id":"2306.05724","title":"Explaining Predictive Uncertainty with Information Theoretic Shapley Values","created":"2023-06-09","cited_by_count":36,"area":null},{"id":"2302.00736","title":"Approximating the Shapley Value without Marginal Contributions","created":"2023-02-01","cited_by_count":34,"area":null},{"id":"2104.08015","title":"On the Complexity of SHAP-Score-Based Explanations: Tractability via Knowledge Compilation and Non-Approximability Results","created":"2021-04-16","cited_by_count":32,"area":null},{"id":"2302.08160","title":"The Inadequacy of Shapley Values for Explainability","created":"2023-02-16","cited_by_count":31,"area":null},{"id":"2401.12069","title":"Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles","created":"2024-01-22","cited_by_count":31,"area":null},{"id":"2110.09167","title":"RKHS-SHAP: Shapley Values for Kernel Methods","created":"2021-10-18","cited_by_count":30,"area":null},{"id":"2106.14648","title":"On Locality of Local Explanation Models","created":"2021-06-24","cited_by_count":25,"area":null},{"id":"2101.02153","title":"The Shapley Value of Classifiers in Ensemble Games","created":"2021-01-06","cited_by_count":23,"area":null},{"id":"2410.01917","title":"Provably Accurate Shapley Value Estimation via Leverage Score Sampling","created":"2024-10-02","cited_by_count":23,"area":null},{"id":"2105.11724","title":"SHAFF: Fast and consistent SHApley eFfect estimates via random Forests","created":"2021-05-25","cited_by_count":22,"area":null},{"id":"2405.10852","title":"KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions","created":"2024-05-17","cited_by_count":22,"area":null},{"id":"2106.12228","title":"groupShapley: Efficient prediction explanation with Shapley values for feature groups","created":"2021-06-23","cited_by_count":21,"area":null},{"id":"2401.15866","title":"Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution","created":"2024-01-29","cited_by_count":21,"area":null},{"id":"2303.02794","title":"CoRTX: Contrastive Framework for Real-time Explanation","created":"2023-03-05","cited_by_count":20,"area":null},{"id":"2305.15167","title":"Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models","created":"2023-05-24","cited_by_count":19,"area":null},{"id":"2506.11849","title":"Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values","created":"2025-06-13","cited_by_count":19,"area":null},{"id":"2304.01811","title":"HarsanyiNet: Computing Accurate Shapley Values in a Single Forward Propagation","created":"2023-04-04","cited_by_count":17,"area":null},{"id":"2302.03225","title":"Efficient XAI Techniques: A Taxonomic Survey","created":"2023-02-07","cited_by_count":14,"area":null},{"id":"2111.10853","title":"Decorrelated Variable Importance","created":"2021-11-21","cited_by_count":13,"area":null},{"id":"2206.08529","title":"Accelerating Shapley Explanation via Contributive Cooperator Selection","created":"2022-06-17","cited_by_count":13,"area":null},{"id":"2501.16944","title":"Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks","created":"2025-01-28","cited_by_count":13,"area":null},{"id":"2208.09970","title":"Statistical Aspects of SHAP: Functional ANOVA for Model Interpretation","created":"2022-08-21","cited_by_count":12,"area":null},{"id":"2201.11701","title":"Model Agnostic Interpretability for Multiple Instance Learning","created":"2022-01-27","cited_by_count":10,"area":null},{"id":"2103.15429","title":"Efficient Explanations from Empirical Explainers","created":"2021-03-29","cited_by_count":9,"area":null},{"id":"2106.03820","title":"Accurate Shapley Values for explaining tree-based models","created":"2021-06-07","cited_by_count":9,"area":null},{"id":"2209.01939","title":"Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams","created":"2022-09-05","cited_by_count":9,"area":null},{"id":"2310.07672","title":"Stabilizing Estimates of Shapley Values with Control Variates","created":"2023-10-11","cited_by_count":9,"area":null},{"id":"2407.11359","title":"Feature Inference Attack on Shapley Values","created":"2024-07-16","cited_by_count":9,"area":null},{"id":"2410.23808","title":"One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently","created":"2024-10-31","cited_by_count":9,"area":null},{"id":"2206.00511","title":"Differentially Private Shapley Values for Data Evaluation","created":"2022-06-01","cited_by_count":8,"area":null},{"id":"2410.06300","title":"SHAP values via sparse Fourier representation","created":"2024-10-08","cited_by_count":8,"area":null},{"id":"2510.21599","title":"SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism","created":"2025-10-24","cited_by_count":8,"area":null},{"id":"2110.02484","title":"Shapley variable importance clouds for interpretable machine learning","created":"2021-10-06","cited_by_count":7,"area":null},{"id":"2401.15800","title":"Statistical Significance of Feature Importance Rankings","created":"2024-01-28","cited_by_count":7,"area":null},{"id":"2601.18608","title":"PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression","created":"2026-01-26","cited_by_count":7,"area":null},{"id":"2210.02419","title":"Boundary-Aware Uncertainty for Feature Attribution Explainers","created":"2022-10-05","cited_by_count":6,"area":null},{"id":"2210.17426","title":"Trade-off Between Efficiency and Consistency for Removal-based Explanations","created":"2022-10-31","cited_by_count":6,"area":null},{"id":"2212.00630","title":"Probably Approximate Shapley Fairness with Applications in Machine Learning","created":"2022-12-01","cited_by_count":6,"area":null},{"id":"2508.14499","title":"Exact Shapley Attributions in Quadratic-time for FANOVA Gaussian Processes","created":"2025-08-20","cited_by_count":6,"area":null},{"id":"2307.04850","title":"SHAP@k:Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features","created":"2023-07-10","cited_by_count":5,"area":null},{"id":"2308.08945","title":"Interpretable Graph Neural Networks for Tabular Data","created":"2023-08-17","cited_by_count":5,"area":null},{"id":"2312.03675","title":"GeoShapley: A Game Theory Approach to Measuring Spatial Effects in Machine Learning Models","created":"2023-12-06","cited_by_count":5,"area":null},{"id":"2410.04883","title":"Improving the Weighting Strategy in KernelSHAP","created":"2024-10-07","cited_by_count":5,"area":null},{"id":"2501.15070","title":"Unifying Prediction and Explanation in Time-Series Transformers via Shapley-based Pretraining","created":"2025-01-25","cited_by_count":5,"area":null},{"id":"2504.01842","title":"shapr: Explaining Machine Learning Models with Conditional Shapley Values in R and Python","created":"2025-04-02","cited_by_count":5,"area":null},{"id":"2505.16516","title":"Amortized Linear-time Exact Shapley Value for Product-Kernel Methods","created":"2025-05-22","cited_by_count":5,"area":null},{"id":"2602.01399","title":"An Odd Estimator for Shapley Values","created":"2026-02-01","cited_by_count":5,"area":null},{"id":"2304.03113","title":"Efficient SAGE Estimation via Causal Structure Learning","created":"2023-04-06","cited_by_count":4,"area":null},{"id":"2305.19998","title":"Efficient Shapley Values Estimation by Amortization for Text Classification","created":"2023-05-31","cited_by_count":4,"area":null},{"id":"2309.03041","title":"A Refutation of Shapley Values for Explainability","created":"2023-09-06","cited_by_count":4,"area":null},{"id":"2309.08799","title":"SHAPNN: Shapley Value Regularized Tabular Neural Network","created":"2023-09-15","cited_by_count":4,"area":null},{"id":"2310.07882","title":"The Thousand Faces of Explainable AI Along the Machine Learning Life Cycle: Industrial Reality and Current State of Research","created":"2023-10-11","cited_by_count":4,"area":null},{"id":"2405.03735","title":"Select to Perfect: Imitating desired behavior from large multi-agent data","created":"2024-05-06","cited_by_count":4,"area":null},{"id":"2405.17489","title":"On the Inflation of KNN-Shapley Value","created":"2024-05-25","cited_by_count":4,"area":null},{"id":"2406.18334","title":"Efficient and Accurate Explanation Estimation with Distribution Compression","created":"2024-06-26","cited_by_count":4,"area":null},{"id":"2407.13841","title":"Many Perception Tasks are Highly Redundant Functions of their Input Data","created":"2024-07-18","cited_by_count":4,"area":null},{"id":"2408.06509","title":"Fooling SHAP with Output Shuffling Attacks","created":"2024-08-12","cited_by_count":4,"area":null},{"id":"2409.11992","title":"Additive-feature-attribution methods: a review on explainable artificial intelligence for fluid dynamics and heat transfer","created":"2024-09-18","cited_by_count":4,"area":null},{"id":"2410.19236","title":"SHAP zero Explains Biological Sequence Models with Near-zero Marginal Cost for Future Queries","created":"2024-10-25","cited_by_count":4,"area":null},{"id":"2503.19496","title":"SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration","created":"2025-03-25","cited_by_count":4,"area":null},{"id":"2506.05216","title":"A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values","created":"2025-06-05","cited_by_count":4,"area":null},{"id":"2602.11623","title":"TreeGrad-Ranker: Feature Ranking via $O(L)$-Time Gradients for Decision Trees","created":"2026-02-12","cited_by_count":4,"area":null},{"id":"2201.03291","title":"A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study","created":"2022-01-10","cited_by_count":3,"area":null},{"id":"2312.11818","title":"Root Cause Explanation of Outliers under Noisy Mechanisms","created":"2023-12-19","cited_by_count":3,"area":null},{"id":"2402.09947","title":"Explaining Probabilistic Models with Distributional Values","created":"2024-02-15","cited_by_count":3,"area":null},{"id":"2410.17269","title":"FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction","created":"2024-10-07","cited_by_count":3,"area":null},{"id":"2505.04775","title":"Prediction via Shapley Value Regression","created":"2025-05-07","cited_by_count":3,"area":null},{"id":"2506.05647","title":"Learning to Weight Parameters for Training Data Attribution","created":"2025-06-06","cited_by_count":3,"area":null},{"id":"2602.07203","title":"Exactly Computing do-Shapley Values","created":"2026-02-06","cited_by_count":3,"area":null},{"id":"2112.12444","title":"More Than Words: Towards Better Quality Interpretations of Text Classifiers","created":"2021-12-23","cited_by_count":2,"area":null},{"id":"2211.13289","title":"Shapley Curves: A Smoothing Perspective","created":"2022-11-23","cited_by_count":2,"area":null},{"id":"2311.01010","title":"Fast Shapley Value Estimation: A Unified Approach","created":"2023-11-02","cited_by_count":2,"area":null},{"id":"2402.09288","title":"EcoVal: An Efficient Data Valuation Framework for Machine Learning","created":"2024-02-14","cited_by_count":2,"area":null},{"id":"2405.19562","title":"Selective Explanations","created":"2024-05-29","cited_by_count":2,"area":null},{"id":"2410.08336","title":"Kernel Banzhaf: A Fast and Robust Estimator for Banzhaf Values","created":"2024-10-10","cited_by_count":2,"area":null},{"id":"2411.13052","title":"On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective","created":"2024-11-20","cited_by_count":2,"area":null},{"id":"2412.01460","title":"A Comprehensive Study of Shapley Value in Data Analytics","created":"2024-12-02","cited_by_count":2,"area":null},{"id":"2502.04763","title":"Shapley Value Approximation Based on k-Additive Games","created":"2025-02-07","cited_by_count":2,"area":null},{"id":"2503.06602","title":"FW-Shapley: Real-time Estimation of Weighted Shapley Values","created":"2025-03-09","cited_by_count":2,"area":null},{"id":"2505.19013","title":"Faithful Group Shapley Value","created":"2025-05-25","cited_by_count":2,"area":null},{"id":"2506.05281","title":"Fast-DataShapley: Neural Modeling for Training Data Valuation","created":"2025-06-05","cited_by_count":2,"area":null},{"id":"2508.12947","title":"Shapley Values: Paired-Sampling Approximations","created":"2025-08-18","cited_by_count":2,"area":null},{"id":"2510.01663","title":"Shift-Invariant Attribute Scoring for Kolmogorov-Arnold Networks via Shapley Value","created":"2025-10-02","cited_by_count":2,"area":null},{"id":"2512.14354","title":"Enhancing Interpretability for Vision Models via Shapley Value Optimization","created":"2025-12-16","cited_by_count":2,"area":null},{"id":"2602.09326","title":"Priority-Aware Shapley Value","created":"2026-02-10","cited_by_count":2,"area":null}],"next_cursor":"100"}