Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T07:35:25.604743Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 1 inbound Pith citation observation for arXiv:2601.20086.
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 2026-08-03T07:35:25.604743Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-10T14:59:12.966608Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T11:21:04.851795Z
66 of 66 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 23ffc90e-ec3b-4dc2-9583-7f76788eeee2 · outbound
Evaluating Actionability in Explainable AI ICO & Turing Institute (2022), https://ico.org.uk/for-organisations/guide-to-data-protection/key-dp- themes/explaining-decisions-made-with-artificial-intelligence/ 20 G
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Evaluating Actionability in Explainable AI Hum.-Comput
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Evaluating Actionability in Explainable AI Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
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Evaluating Actionability in Explainable AI One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
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Evaluating Actionability in Explainable AI (ed.): Scenario-based design: envisioning work and technology in sys- tem development
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Evaluating Actionability in Explainable AI In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
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Evaluating Actionability in Explainable AI In: 2018 IEEE 20th Interna- tional Conference on e-Health Networking, Applications and Services (Healthcom)
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Evaluating Actionability in Explainable AI In: Proceedings of the 42nd In- ternational ACM SIGIR Conference on Research and Development in Infor- mation Retrieval
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Evaluating Actionability in Explainable AI In: Guarda, T., Portela, F., Augusto, M.F
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Evaluating Actionability in Explainable AI it is a moving process
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Evaluating Actionability in Explainable AI In: Dohn, N.B., Jandrić, P., Ryberg, T., de Laat, M
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Evaluating Actionability in Explainable AI Towards A Rigorous Science of Interpretable Machine Learning
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Evaluating Actionability in Explainable AI https://doi.org/10.2139/ssrn.2972855, https://papers.ssrn.com/abstract=2972855
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Evaluating Actionability in Explainable AI In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
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Observation 1fafdaae-6352-4b18-9f35-68c8c98c37c5 · outbound
Evaluating Actionability in Explainable AI In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining
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Evaluating Actionability in Explainable AI https://doi.org/10.1007/s00146-022-01454-7, https://doi.org/10.1007/s00146- 022-01454-7
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Evaluating Actionability in Explainable AI Learning Actionable Representations with Goal-Conditioned Policies
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Observation d59ed3fb-aa9b-43ef-9936-742fa21ca724 · outbound
Evaluating Actionability in Explainable AI Human-Machine Communication2, 153–171 (01 2021)
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Observation da61f0f7-c2d6-4c8c-9e7d-93b3447c9009 · outbound
Evaluating Actionability in Explainable AI Academy of Management An- nals14(2), 627–660 (2020)
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Observation 2b36ec69-850f-426e-8ebc-8ae81fc2c4a3 · outbound
Evaluating Actionability in Explainable AI ACM Computing Surveys (CSUR)51, 1 – 42 (2018)
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Evaluating Actionability in Explainable AI Unresolved cited work
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Observation fd3317c9-ba40-4054-b90c-0581b97eb0e4 · outbound
Evaluating Actionability in Explainable AI AAAI Spring Symposium (2009)
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Observation 43fb845f-e635-4c85-b397-ff170d1e3337 · outbound
Evaluating Actionability in Explainable AI Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems
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Observation 6942256c-a22f-443c-a377-5479fd9c0b8e · outbound
Evaluating Actionability in Explainable AI Unresolved cited work
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Evaluating Actionability in Explainable AI Unresolved cited work
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Observation 7c3ba3a1-80c6-4a50-9a0d-848566f914a5 · outbound
Evaluating Actionability in Explainable AI In: Trattner, C., Parra, D., Riche, N
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Observation 4e8df79a-6345-45e9-bfc8-275902a5dff1 · outbound
Evaluating Actionability in Explainable AI Communications of the ACM 61, 36 – 43 (2018)
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Observation dfd7c5f1-297a-48bc-b173-afb40b2b952a · outbound
Evaluating Actionability in Explainable AI Unresolved cited work
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Observation 560914c8-6b51-4a84-bbe4-84c08ac6e3db · outbound
Evaluating Actionability in Explainable AI Journal of Computer-Mediated Com- munication26(6), 384–402 (09 2021)
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Observation 7043880f-163e-4bea-a23b-a8662ed8f3eb · outbound
Evaluating Actionability in Explainable AI In: Nørskov, M., Seibt, J., Quick, O
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Observation 46f3a5a6-c7bb-4f77-b870-663d525fafa6 · outbound
Evaluating Actionability in Explainable AI Extracting Actionability from Machine Learning Models by Sub-optimal Deterministic Planning
Reference 45
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Observation b2d300de-5fd2-4e33-8e18-e0332393f28f · outbound
Evaluating Actionability in Explainable AI A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
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Observation 26ee1d46-23f0-4847-91bb-014d22e28653 · outbound
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Evaluating Actionability in Explainable AI In: Lim, C.T., Leo, H.L., Yeow, R
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Evaluating Actionability in Explainable AI Computers and Education: Artificial Intelligence2, 100020 (2021)
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Observation c3db8462-1209-4f89-8c18-f4ce1ecbe900 · outbound
Evaluating Actionability in Explainable AI American Medical Informatics Association Annual Symposium2012, 779–88 (2012)
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Observation 9fc02097-d7d9-4e97-8216-065046f5e32b · outbound
Evaluating Actionability in Explainable AI British Journal of Educational Technology50(6), 2943–2958 (2019)
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Evaluating Actionability in Explainable AI Directive Explanations for Actionable Explainability in Machine Learning Applications
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Observation 2e38d349-31e4-434a-8ccf-0c700bbcac3b · outbound
Evaluating Actionability in Explainable AI Extended Analysis of "How Child Welfare Workers Reduce Racial Disparities in Algorithmic Decisions"
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Evaluating Actionability in Explainable AI (eds.) The Mind-Technology Problem : Investigating Minds, Selves and 21st Century Artefacts, pp
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Evaluating Actionability in Explainable AI Defining and Conceptualizing Actionable Insight: A Conceptual Framework for Decision-centric Analytics
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Observation 3263fcd6-0758-4528-be5c-69b2f92f5d5e · outbound
Evaluating Actionability in Explainable AI Explanatory Pluralism in Explainable AI
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From Attribution to Action: A Human-Centered Application of Activation Steering Evaluating Actionability in Explainable AI
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