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Paper Citation Record · LEDGER

A Comprehensive Survey for Evaluation Methodologies of AI-Generated Music

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.13736.

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

pith.paper-citation-record.v1
2308.13736 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 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T00:35:42.697038Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T00:45:12.348646Z

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 6b68b129-e91d-448f-9282-f7233acd1893 · inbound

APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music cites this paper.

APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music A Comprehensive Survey for Evaluation Methodologies of AI-Generated Music

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:56:29.727988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-07T13:27:41.439049Z digest=sha256:1b35a552b80e96bb445b3cda20359ef50fb884680d88f635a2deaa31047ff1b5

Observation 593e7019-97a1-4f0c-a4b4-56dfd7385c60 · inbound

APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music cites this paper.

APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music A Comprehensive Survey for Evaluation Methodologies of AI-Generated Music

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-01T00:45:12.350450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-07-01T00:35:42.697038Z digest=sha256:21facff85da6f85fac10d5368b08ea48908734b7632e9f72f0c410ce003482b2