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Paper Citation Record · LEDGER

Knowledge Discovery in Optical Music Recognition: Enhancing Information Retrieval with Instance Segmentation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.15002.

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

pith.paper-citation-record.v1
2408.15002 v2

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:57:04.402673Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-09T23:04:17.588702Z

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 bf1091cd-1469-437c-9c43-c6694acdb18c · inbound

MusiXQA: Advancing Visual Music Understanding in Multimodal Large Language Models cites this paper.

MusiXQA: Advancing Visual Music Understanding in Multimodal Large Language Models Knowledge Discovery in Optical Music Recognition: Enhancing Information Retrieval with Instance Segmentation

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T21:57:04.402673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:57:04.402673Z digest=sha256:f9c7d8fbce8d40c406baa20158b4395aee7ec0d7a1fed7481ea2831654ac1e69

Observation ca01f2dc-ab79-49d7-89e0-43abd94698aa · inbound

ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence cites this paper.

ONOTE: Benchmarking Omnimodal Notation Processing for Expert-level Music Intelligence Knowledge Discovery in Optical Music Recognition: Enhancing Information Retrieval with Instance Segmentation

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-09T23:04:17.590323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-09T23:03:01.356594Z digest=sha256:597d1b94b488d62098927f4b685de67de61cc0053956901af25db4970e5da6a9