Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:32:56.074741Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2506.13900.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:32:56.074741Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T19:07:32.564519Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T19:13:52.682699Z
27 of 27 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 937e7622-39fc-4f4c-8f8c-3c90c1f8857b · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Amoukou, Tangi Sala ¨un, and Nicolas Brunel
Reference 1
Source-reported events for the cited work
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Observation d569a06a-7712-4362-846f-34deda9c9719 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Harsanyi
Reference 5
Source-reported events for the cited work
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Observation f1b7d34f-991a-4214-b1bf-c9b64204ef80 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models On the coalitional decomposition of parameters of interest
Reference 8
Source-reported events for the cited work
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Observation d75aa3e7-a864-4eaf-9d4a-d7b4c34e7a30 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models A unified approach to interpreting model predictions
Reference 12
Source-reported events for the cited work
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Observation be172711-3b0a-43d6-a0d4-16469d07f146 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Unresolved cited work
Reference 18
Source-reported events for the cited work
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Observation 885bfafc-1912-49da-aee1-30926bf305e1 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models [Vasil’ev and van der Laan, 2001] Valeri Vasil’ev and Ger- ard van der Laan
Reference 22
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0537c462-7663-4aec-ab56-216289247cb7 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models [Watson et al., 2023] David Watson, Joshua O’Hara, Niek Tax, Richard Mudd, and Ido Guy
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 98bac4f5-28f0-4d72-bb3e-731150c07928 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Probabilistic values for games, page 101–120
Reference 25
Source-reported events for the cited work
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Observation a7675f1c-fc10-49f2-98ff-4beb1e4e0abd · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots
Reference 27
Source-reported events for the cited work
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Observation 56517360-b475-4282-b616-5c9acae9890e · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Nelson, and Jeremy Staum
Reference 1951
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 955152a3-bf9d-4847-9c22-7c70bd1201b6 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Haufe, R
Reference 1963
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d9af3cdf-4f91-431f-a15e-425fd9836bfa · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Why don’t xai techniques agree? characterizing the dis- agreements between post-hoc explanations of defect pre- dictions
Reference 1964
Source-reported events for the cited work
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Observation c8fb755c-e9c0-4f0f-a779-1072b8d09fb7 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Unresolved cited work
Reference 1988
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 74420c0a-e2c8-4479-8dfe-3a7fd1ef0b29 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Unresolved cited work
Reference 1994
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f75c693b-9a01-4c45-9fda-62067ba1ef5a · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Osborne and Ariel Rubinstein
Reference 2000
Source-reported events for the cited work
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Observation 7d8ff54e-bd5e-4dbd-8486-82f26bdc1bb2 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Verdinelli and L
Reference 2001
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3cf2d883-022c-44ef-87d6-b132b254ef69 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models The Many Shapley Values for Model Ex- planation
Reference 2010
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b77ffa90-521b-4a60-b70b-624b51922ddf · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models On the foundations of combi- natorial theory I
Reference 2014
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1e86a9a8-3841-46a4-b2be-bc96e2998d8e · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models An efficient explanation of individual classi- fications using game theory
Reference 2016
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0ed676f2-581d-47ba-84dd-57ea2451c23f · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Michael Ortmann
Reference 2017
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 724c5f00-9e0f-448f-9bfb-7402fa9b1e7d · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Achieving interpretable machine learn- ing by functional decomposition of black-box models into explainable predictor effects,
Reference 2019
Source-reported events for the cited work
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Observation c5593712-0bab-4faa-8c7e-10da16ffdbb1 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Kernel-based anova decomposition and shapley effects – application to global sensitivity analysis,
Reference 2020
Source-reported events for the cited work
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Observation 9da96e4e-85d8-4812-b6e8-15feb5e4c461 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Asymmetric shapley values: incorporating causal knowledge into model-agnostic explainability
Reference 2021
Source-reported events for the cited work
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Observation 8230a418-fee3-460c-89e1-21357b9f67cc · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
Reference 2022
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation da9d6e59-a6f1-45f0-9225-523d07743950 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Hoeffding decomposition of functions of ran- dom dependent variables
Reference 2023
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c421ff0b-19c1-427f-befb-b90552828da1 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Explainable AI needs formalization
Reference 2024
Source-reported events for the cited work
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Observation 60045d6c-85be-4b16-8386-520c67ff0889 · outbound
Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models Shapley Effects For Sensitivity Analysis With Cor- related Inputs: Comparisons With Sobol’ Indices, Numer- ical Estimation And Applications
Reference 2025
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 1e09a978-f2c5-4efb-82c2-bc9a0f9ecb05 · inbound
Coalition Free Energy and Adaptive Precision in Multi-Agent Cooperation Beyond Shapley Values: Cooperative Games for the Interpretation of Machine Learning Models
Reference 25
Source-reported events for the cited work
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