Xuanxiang Huang

According to our database, Xuanxiang Huang authored at least 32 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Feature Necessity and Relevancy in Machine Learning Explanations.

Xuanxiang Huang, Martin C. Cooper, António Morgado, Jordi Planes, João Marques-Silva

J. Autom. Reason., June, 2026

Towards Rigorous Explainability by Feature Attribution.

Olivier Létoffé, Xuanxiang Huang, João Marques-Silva

CoRR, April, 2026

A Parallel Approach to Counting Exact Covers Based on Decomposability Property.

Liangda Fang, Yaohui Luo, Delong Li, Xuanxiang Huang, Quanlong Guan

CoRR, April, 2026

Rigorous Explanations for Tree Ensembles.

Yacine Izza, Alexey Ignatiev, Xuanxiang Huang, Peter J. Stuckey, João Marques-Silva

CoRR, March, 2026

Unifying Formal Explanations: A Complexity-Theoretic Perspective.

Shahaf Bassan, Xuanxiang Huang, Guy Katz

CoRR, February, 2026

2025

Uncovering Bugs in Formal Explainers: A Case Study with PyXAI.

Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, João Marques-Silva

CoRR, November, 2025

Rigorous Feature Importance Scores based on Shapley Value and Banzhaf Index.

Xuanxiang Huang, Olivier Létoffé, João Marques-Silva

CoRR, August, 2025

The Explanation Game - Rekindled (Extended Version).

João Marques-Silva, Xuanxiang Huang, Olivier Letoffe

CoRR, January, 2025

Towards Trustable SHAP Scores.

Olivier Létoffé, Xuanxiang Huang, João Marques-Silva

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Explainability Is <i>Not</i> a Game.

João Marques-Silva, Xuanxiang Huang

Commun. ACM, July, 2024

On the failings of Shapley values for explainability.

Xuanxiang Huang, João Marques-Silva

Int. J. Approx. Reason., 2024

SHAP scores fail pervasively even when Lipschitz succeeds.

Olivier Letoffe, Xuanxiang Huang, João Marques-Silva

CoRR, 2024

From SHAP Scores to Feature Importance Scores.

Olivier Letoffe, Xuanxiang Huang, Nicholas Asher, João Marques-Silva

CoRR, 2024

On Correcting SHAP Scores.

Olivier Letoffe, Xuanxiang Huang, João Marques-Silva

CoRR, 2024

Distance-Restricted Explanations: Theoretical Underpinnings & Efficient Implementation.

Yacine Izza, Xuanxiang Huang, António Morgado, Jordi Planes, Alexey Ignatiev, João Marques-Silva

Proceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning, 2024

Updates on the Complexity of SHAP Scores.

Xuanxiang Huang, João Marques-Silva

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023

On computing probabilistic abductive explanations.

Yacine Izza, Xuanxiang Huang, Alexey Ignatiev, Nina Narodytska, Martin C. Cooper, João Marques-Silva

Int. J. Approx. Reason., August, 2023

Recent advances in formal explainability. (Progrès récents en matière d'explicabilité formelle).

Xuanxiang Huang

PhD thesis, 2023

Refutation of Shapley Values for XAI - Additional Evidence.

Xuanxiang Huang, João Marques-Silva

CoRR, 2023

A Refutation of Shapley Values for Explainability.

Xuanxiang Huang, João Marques-Silva

CoRR, 2023

Explainability is NOT a Game.

João Marques-Silva, Xuanxiang Huang

CoRR, 2023

From Robustness to Explainability and Back Again.

Xuanxiang Huang, João Marques-Silva

CoRR, 2023

The Inadequacy of Shapley Values for Explainability.

Xuanxiang Huang, João Marques-Silva

CoRR, 2023

Feature Necessity & Relevancy in ML Classifier Explanations.

Xuanxiang Huang, Martin C. Cooper, António Morgado, Jordi Planes, João Marques-Silva

Proceedings of the Tools and Algorithms for the Construction and Analysis of Systems, 2023

From Decision Trees to Explained Decision Sets.

Xuanxiang Huang, João Marques-Silva

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Solving Explainability Queries with Quantification: The Case of Feature Relevancy.

Xuanxiang Huang, Yacine Izza, João Marques-Silva

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

On Deciding Feature Membership in Explanations of SDD & Related Classifiers.

Xuanxiang Huang, João Marques-Silva

CoRR, 2022

Tractable Explanations for d-DNNF Classifiers.

Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, Martin C. Cooper, Nicholas Asher, João Marques-Silva

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Efficient Explanations for Knowledge Compilation Languages.

Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, Martin C. Cooper, Nicholas Asher, João Marques-Silva

CoRR, 2021

On Efficiently Explaining Graph-Based Classifiers.

Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, João Marques-Silva

Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning, 2021

2020

Dynamic Minimization of Bi-Kronecker Functional Decision Diagrams.

Xuanxiang Huang, Haipeng Che, Liangda Fang, Qingliang Chen, Quanlong Guan, Yuhui Deng, Kaile Su

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

2019

Bi-Kronecker Functional Decision Diagrams: A Novel Canonical Representation of Boolean Functions.

Xuanxiang Huang, Kehang Fang, Liangda Fang, Qingliang Chen, Zhao-Rong Lai, Linfeng Wei

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019