AAAI 2024 "explainable ai" Papers

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Accelerating the Global Aggregation of Local Explanations

Alon Mor, Yonatan Belinkov, Benny Kimelfeld

AAAI 2024paperarXiv:2312.07991
6
citations

Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles

Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer et al.

AAAI 2024paperarXiv:2401.12069
29
citations

CGS-Mask: Making Time Series Predictions Intuitive for All

Feng Lu, Wei Li, Yifei Sun et al.

AAAI 2024paperarXiv:2312.09513
1
citations

Enhance Sketch Recognition’s Explainability via Semantic Component-Level Parsing

Guangming Zhu, Siyuan Wang, Tianci Wu et al.

AAAI 2024paperarXiv:2312.07875
2
citations

Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals

Patrick Altmeyer, Mojtaba Farmanbar, Arie Van Deursen et al.

AAAI 2024paperarXiv:2312.10648

Gaussian Process Neural Additive Models

Wei Zhang, Brian Barr, John Paisley

AAAI 2024paperarXiv:2402.12518
11
citations

Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning

Tom Nuno Wolf, Fabian Bongratz, Anne-Marie Rickmann et al.

AAAI 2024paperarXiv:2312.09783
8
citations

Learning Performance Maximizing Ensembles with Explainability Guarantees

Vincent Pisztora, Jia Li

AAAI 2024paperarXiv:2312.12715

Towards More Faithful Natural Language Explanation Using Multi-Level Contrastive Learning in VQA

Chengen Lai, Shengli Song, Shiqi Meng et al.

AAAI 2024paperarXiv:2312.13594
9
citations

Using Stratified Sampling to Improve LIME Image Explanations

Muhammad Rashid, Elvio G. Amparore, Enrico Ferrari et al.

AAAI 2024paperarXiv:2403.17742
7
citations