mlsanityData to 7 Oct 2026

Shapley Revisited: Tractable Responsibility Measures for Query Answers

arXiv 2503.22358 ↗First posted 28 Mar 2025cs.DB cs.AIcited by 4

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Abstract (arXiv)

The Shapley value, originating from cooperative game theory, has been employed to define responsibility measures that quantify the contributions of database facts to obtaining a given query answer. For non-numeric queries, this is done by considering a cooperative game whose players are the facts and whose wealth function assigns 1 or 0 to each subset of the database, depending on whether the query answer holds in the given subset. While conceptually simple, this approach suffers from a notable drawback: the problem of computing such Shapley values is #P-hard in data complexity, even for simple conjunctive queries. This motivates us to revisit the question of what constitutes a reasonable responsibility measure and to introduce a new family of responsibility measures -- weighted sums of minimal supports (WSMS) -- which satisfy intuitive properties. Interestingly, while the definition of WSMSs is simple and bears no obvious resemblance to the Shapley value formula, we prove that every WSMS measure can be equivalently seen as the Shapley value of a suitably defined cooperative game. Moreover, WSMS measures enjoy tractable data complexity for a large class of queries, including all unions of conjunctive queries. We further explore the combined complexity of WSMS computation and establish (in)tractability results for various subclasses of conjunctive queries.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 14 of its 51 references that are in the map. First posted on arXiv 28 Mar 2025.

Builds on

14 of 51 references.

References · 14

  1. 2017A Unified Approach to Interpreting Model Predictionscited by 6,488
  2. 2019The Shapley Value of Tuples in Query Answeringcited by 23
  3. 2023Explainability is NOT a Gamecited by 23
  4. 2022Feature Necessity & Relevancy in ML Classifier Explanationscited by 22
  5. 2021Computing the Shapley Value of Facts in Query Answeringcited by 11
  6. 2016Quantifying Causal Effects on Query Answering in Databasescited by 10
  7. 2020The Shapley Value of Inconsistency Measures for Functional Dependenciescited by 8
  8. 2023When is Shapley Value Computation a Matter of Counting?cited by 8
  9. 2023From Shapley Value to Model Counting and Backcited by 7
  10. 2019The Impact of Negation on the Complexity of the Shapley Value in Conjunctive Queriescited by 6
  11. 2023Banzhaf Values for Facts in Query Answeringcited by 6
  12. 2024Expected Shapley-Like Scores of Boolean Functions: Complexity and Applications to Probabilistic Databasescited by 6
2 more
  1. 2022The Complexity of the Shapley Value for Regular Path Queriescited by 5
  2. 2024Shapley Value Computation in Ontology-Mediated Query Answeringcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.