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Paper Citation Record · LEDGER

DQI: Measuring Data Quality in NLP

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2005.00816.

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

pith.paper-citation-record.v1
2005.00816 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:54:50.806461Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:35:53.496072Z

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 805fea4b-e9e7-4120-a3af-3544770927cb · inbound

Measuring Diversity in Synthetic Datasets cites this paper.

Measuring Diversity in Synthetic Datasets DQI: Measuring Data Quality in NLP

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T04:54:50.806461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T04:54:50.806461Z digest=sha256:0766e17f93af135a0c416a07219ff7ebaa2ac0cb9af7358a4df7bbecfe7884d3

Observation f852dc58-eb7a-447b-8707-50a7b4d93cae · inbound

Towards Better Instruction Following Retrieval Models cites this paper.

Towards Better Instruction Following Retrieval Models DQI: Measuring Data Quality in NLP

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:35:53.562588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:35:49.159046Z digest=sha256:ed79ef6b06142093c14f14c45d9de33ed8b20a4d1c8ac0efce8b7ecf6a55b035