Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Position: Measure Dataset Diversity, Don't Just Claim It
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.08188.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:34:06.207187Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T19:47:50.105582Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- 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 bcae24da-4436-4c06-992d-d6b5f7c12403 · inbound
Image Generation Diversity Issues and How to Tame Them cites this paper.
Image Generation Diversity Issues and How to Tame Them Position: Measure Dataset Diversity, Don't Just Claim It
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T13:34:06.207187Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 177f72cc-7719-4287-8697-736e8d02fb5d · inbound
A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts cites this paper.
A Shared Standard for Valid Measurement of Generative AI Systems' Capabilities, Risks, and Impacts Position: Measure Dataset Diversity, Don't Just Claim It
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T00:07:18.921234Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23d0066d-d61f-4963-816d-561dad040ee0 · inbound
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models cites this paper.
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models Position: Measure Dataset Diversity, Don't Just Claim It
Reference 239
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:57:02.170118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 002a391c-296a-4350-83e4-a0b42f749512 · inbound
Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems cites this paper.
Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems Position: Measure Dataset Diversity, Don't Just Claim It
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T10:45:03.096719Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8b973ad6-b883-47bf-a536-559b06e27047 · inbound
Toward Valid Measurement Of (Un)fairness For Generative AI: A Proposal For Systematization Through The Lens Of Fair Equality of Chances cites this paper.
Toward Valid Measurement Of (Un)fairness For Generative AI: A Proposal For Systematization Through The Lens Of Fair Equality of Chances Position: Measure Dataset Diversity, Don't Just Claim It
Reference 94
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T19:47:50.177138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.