The Metagame of Interpretability and Meta-Attributions
How can an arbitrary attribution method be generalized from first principles to capture interactions? We answer this with the metagame, a conceptual framework for quantifying second-order interaction effects of model explanations. We cast the attribution value $φ_i$ of feature $i$ as a cooperative game among the other features and compute its Shapley value, which measures how much feature $j$ influences the attribution of $i$, yielding the directional meta-attribution $\varphi_{j \to i}$. By decomposing attribution itself rather than the model directly, meta-attributions extend any gradient- or attention-based method to interactions, uniting removal-based perturbations with model internal...
| Authors | Hubert Baniecki, Przemyslaw Biecek, Fabian Fumagalli |
|---|---|
| Primary category | cs.LG |
| Published | 7 May 2026 |
| Last updated at source | 6 October 2026 |
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