Technical Note: Game-Theoretic Interactions of Different Orders
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Abstract (arXiv)
In this study, we define interaction components of different orders between two input variables based on game theory. We further prove that interaction components of different orders satisfy several desirable properties.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Oct 2020.
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Citing papers per year: 2021: 5; 2022: 1; 2023: 1; 2024: 2; 2025: 2.
11 papers.
- 2021A Unified Game-Theoretic Interpretation of Adversarial Robustnesscited by 17
- 2021Interpreting Attributions and Interactions of Adversarial Attackscited by 13
- 2021Interpreting Representation Quality of DNNs for 3D Point Cloud Processingcited by 12
- 2022Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferabilitycited by 12
- 2025INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Samplingcited by 10
- 2024Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic Viewcited by 7
- 2024Navigating Beyond Dropout: An Intriguing Solution Towards Generalizable Image Super Resolutioncited by 3
- 2023Distributing Synergy Functions: Unifying Game-Theoretic Interaction Methods for Machine-Learning Explainabilitycited by 2
- 2021Interpreting and improving deep-learning models with reality checkscited by 1
- 2025The Interaction Bottleneck of Deep Neural Networks: Discovery, Proof, and Modulationcited by 1
- 2021A Unified Game-Theoretic Interpretation of Adversarial Robustnesscited by 0
- 2025The Interaction Bottleneck of Deep Neural Networks: Discovery, Proof, and Modulation21 Dec 2025
- 2025INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling7 Jul 2025
- 2024Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View27 May 2024
- 2024Navigating Beyond Dropout: An Intriguing Solution Towards Generalizable Image Super Resolution29 Feb 2024
- 2023Distributing Synergy Functions: Unifying Game-Theoretic Interaction Methods for Machine-Learning Explainability4 May 2023
- 2022Proving Common Mechanisms Shared by Twelve Methods of Boosting Adversarial Transferability24 Jul 2022
- 2021Interpreting Representation Quality of DNNs for 3D Point Cloud Processing5 Nov 2021
- 2021A Unified Game-Theoretic Interpretation of Adversarial Robustness5 Nov 2021
- 2021Interpreting Attributions and Interactions of Adversarial Attacks16 Aug 2021
- 2021Interpreting and improving deep-learning models with reality checks16 Aug 2021
- 2021A Unified Game-Theoretic Interpretation of Adversarial Robustness12 Mar 2021