Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T15:37:19.094296Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2503.13463.
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 2026-08-08T15:37:19.094296Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
25 of 25 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation da26ed95-af26-4401-b606-b3fe98759130 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation In: 2021 IEEE International Conference on Smart Data Services (SMDS)
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 444f4c2a-d316-4ae4-bb66-6c73a280b75b · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation FactSheets: Increasing Trust in AI Services through Supplier's Declarations of Conformity
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3305dd30-c3d1-4c1d-87a7-15a1b8ea5794 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Transactions of the Association for Computational Linguistics 6, 587–604 (2018)
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation cdb6a5a4-0d1d-4f52-a147-a0eef932ee20 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Unresolved cited work
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation de3583ed-9bdb-4fab-9624-77bb09f5619b · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Proceedings of the ACM on Human-Computer Interaction 5(CSCW2), 438:1–438:27 (Oct 2021)
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8bcb1f8d-8b63-4910-a8ed-fe926f6c194c · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b2d32d24-fafa-4aed-9cc0-b4a2871ffbdf · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Unresolved cited work
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f381163f-8d83-484c-97fe-bf4a56ba9c2e · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Datasheets for Datasets
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 576009b4-e1f9-4c18-ac16-8d3ed74d7cb2 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation The Dataset Nutrition Label: A Framework To Drive Higher Data Quality Standards
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2bf06ab7-e34c-4c4f-a582-c0b17ae978aa · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 771eec66-099a-4b86-bc8a-fcec71430dfa · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Proceedings of the 2020 Conference on Fairness, Ac- countability, and Transparency pp
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a8d5b7b8-ff29-408c-b7c8-10ce0d4fb827 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Reduced, Reused and Recycled: The Life of a Dataset in Machine Learning Research
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fc4d55a-1640-4161-9273-90be90e05c1a · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Digital Policy, Regulation and Governance 23(5), 475–488 (Jan 2021)
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 846090d5-c28c-427e-a9e2-5849ec462994 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Proceedings of the Conference on Fairness, Accountability, and Transparency pp
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da2f533f-a151-4a8d-a0e3-554fe5a542c9 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Mitigating Dataset Harms Requires Stewardship: Lessons from 1000 Papers
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f5a4603-333c-4861-89cb-4260c95ad7fd · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Journal of Statistical Software 90, 1–38 (Jul 2019)
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 877b8091-b56f-4846-b035-9c3eaf01f9b6 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation A Methodology for Creating AI FactSheets
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9ba32b69-65a9-47d2-a340-4b3001b6bf88 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Everyone wants to do the model work, not the data work
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 98e99221-d636-4ec1-b1a9-4c883ed19973 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Proceedings of the ACM on Human-Computer Interaction 5(CSCW2), 1–37 (Oct 2021)
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f4db3860-b61c-4d57-b254-f8f0f90f28ea · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 043a6c78-15ed-4062-8764-0df04e9c7e70 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation In: Proceedings of the 28th ACM International Conference on Information and Knowledge Manage- ment
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 65912f49-2f89-4762-ad8a-ee4fa11d5387 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Media, Culture & Society p
Reference 23
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5bcec523-b667-457a-870c-520f383ba898 · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Proceedings of the 2018 International Conference on Management of Data pp
Reference 24
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6f7e6946-d8b5-4d46-851c-6e13fb6bbceb · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation Fairness in Ranking: A Survey
Reference 25
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3070b6c1-278c-4adc-8465-640bf32df06e · outbound
Completeness of Datasets Documentation on ML/AI repositories: an Empirical Investigation https://doi.org/10.1145/3442188.3445918
Reference 575
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.