Paper Citation Record · LEDGER

Mapping the Regulatory Learning Space for the EU AI Act

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.05787.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2503.05787 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T12:08:29.224058Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-21T18:55:29.862775Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 716f8d7a-2700-42f5-837f-4f838dddf74c · inbound

Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid cites this paper.

Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid Mapping the Regulatory Learning Space for the EU AI Act

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:35:32.833958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 52542fa4-b9d5-49f3-875f-e1dafb7e1081 · inbound

Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid cites this paper.

Quantifying the Climate Risk of Generative AI: Region-Aware Carbon Accounting with G-TRACE and the AI Sustainability Pyramid Mapping the Regulatory Learning Space for the EU AI Act

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:55:29.866576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ab0da4e8-57b1-4099-b102-b7b26306980b · inbound

Assessing High-Risk AI Systems under the EU AI Act: From Legal Requirements to Technical Verification cites this paper.

Assessing High-Risk AI Systems under the EU AI Act: From Legal Requirements to Technical Verification Mapping the Regulatory Learning Space for the EU AI Act

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:38:34.367233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1f1a8ba5-1709-4ddf-bf28-7424cf88e80f · inbound

Bathtubs, Boundaries, and Sandboxes: AI Regulatory Learning under Legal Uncertainty cites this paper.

Bathtubs, Boundaries, and Sandboxes: AI Regulatory Learning under Legal Uncertainty Mapping the Regulatory Learning Space for the EU AI Act

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T12:08:29.224058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.