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Paper Citation Record · LEDGER

Rethinking CNN Models for Audio Classification

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2007.11154.

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

pith.paper-citation-record.v1
2007.11154 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:11:30.466495Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.507304Z

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 7f32bd6d-a652-4f8e-ad30-cee216639371 · inbound

LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment cites this paper.

LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment Rethinking CNN Models for Audio Classification

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-17T03:27:59.042443Z

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=arxiv_source observed=2026-05-17T03:27:58.952076Z digest=sha256:7ade339532e5e16fe0edba809e06ceb87c7cb72091406a5ba248bbd6a5d0c394

Observation ba4b7444-69cb-4830-b93b-ef560406aadb · inbound

15,500 Seconds: Lean UAV Classification Using EfficientNet and Lightweight Fine-Tuning cites this paper.

15,500 Seconds: Lean UAV Classification Using EfficientNet and Lightweight Fine-Tuning Rethinking CNN Models for Audio Classification

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T15:11:30.466495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:11:30.466495Z digest=sha256:7e2e18469277c6780273c9151def951c7a5f3578addc7f51292b97ba90a7828d

Observation b90c8b98-a3a0-43cf-86ed-8e479b2a4bb1 · inbound

Charting 15 years of progress in deep learning for speech emotion recognition: A replication study cites this paper.

Charting 15 years of progress in deep learning for speech emotion recognition: A replication study Rethinking CNN Models for Audio Classification

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T05:03:20.280689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:03:20.280689Z digest=sha256:6bc0b4a5609790e3e6f6a124003fa5651e2d9cfa155cd5b681a266b54582e489

Observation 5d758765-0317-4234-962e-c2f3b1f49df1 · inbound

Label Smoothing++: Enhanced Label Regularization for Training Neural Networks cites this paper.

Label Smoothing++: Enhanced Label Regularization for Training Neural Networks Rethinking CNN Models for Audio Classification

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T17:14:23.933814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:14:23.933814Z digest=sha256:2a920478fd5b597c78ba27f943fc7e1f93dfea303d7d562f4edf5fe482dd1d48

Observation bfac8267-5cda-43a2-b1a7-154465cb974b · inbound

InterCMDM: Block-Causal Diffusion for Autoregressive Human Interaction Generation cites this paper.

InterCMDM: Block-Causal Diffusion for Autoregressive Human Interaction Generation Rethinking CNN Models for Audio Classification

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:48:39.508702Z

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=arxiv_source observed=2026-07-03T16:42:32.300986Z digest=sha256:c36a4dffe3d9fed983419b54775d169e266e96aaaa0c8baec3dfb565ba8599c1