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Paper Citation Record · LEDGER

SCNet: Sparse Compression Network for Music Source Separation

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.13276.

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

pith.paper-citation-record.v1
2401.13276 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:48:42.768530Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 1d6f7cbb-1f10-4a73-9c3b-6c7e6c9392a9 · inbound

StemFX: Learning Mixing Style Representations via Autoregressive FX Chain Prediction on Source-Separated Stems cites this paper.

StemFX: Learning Mixing Style Representations via Autoregressive FX Chain Prediction on Source-Separated Stems SCNet: Sparse Compression Network for Music Source Separation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-01T22:48:42.768530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:48:42.768530Z digest=sha256:6ba1d6481090141be464e125d6d36d95fda59664ccc43bbfa6bea3bb9389974a

Observation 74edd24a-03cf-47e8-9130-93d68532d3ec · inbound

Music-Source-Separation-Training (MSST): A Unified Framework for Training and Evaluating Music Demixing Models cites this paper.

Music-Source-Separation-Training (MSST): A Unified Framework for Training and Evaluating Music Demixing Models SCNet: Sparse Compression Network for Music Source Separation

Reference 48

Resolution
unresolved
no resolver link, observed 2026-07-30T23:23:05.705659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T23:23:05.705659Z digest=sha256:03766824f2895d719fee4623ab172aea3373481b629ce38b48daa7521f05eb18