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Paper Citation Record · LEDGER

Enhancing Automatic Modulation Recognition through Robust Global Feature Extraction

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.01056.

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

pith.paper-citation-record.v1
2401.01056 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:51:25.761624Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T02:27:34.586302Z

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 2de0401b-fa47-4680-9338-90c7807655e2 · inbound

AI/ML-Based Automatic Modulation Recognition: Recent Trends and Future Possibilities cites this paper.

AI/ML-Based Automatic Modulation Recognition: Recent Trends and Future Possibilities Enhancing Automatic Modulation Recognition through Robust Global Feature Extraction

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T19:51:25.761624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:51:25.761624Z digest=sha256:bde4425898e56f28955e85f4b1bc205a4773aab0d24d46633312576eec22cf0f

Observation 6523e93f-361d-4147-86bb-75309789e1ea · inbound

Mixture-of-Experts Transformer for Automatic Modulation Recognition cites this paper.

Mixture-of-Experts Transformer for Automatic Modulation Recognition Enhancing Automatic Modulation Recognition through Robust Global Feature Extraction

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-07-03T02:27:34.587757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T15:57:35.464420Z digest=sha256:a835f4f71dfa027ca6ad3134f67f954d41f726ec2610a2af74d7cb0971021d27

Observation 4fa19d4e-9af3-4d1b-93fc-cc0bd8e185c2 · inbound

An Uncertainty-Driven Hybrid Deep Learning Approach for Broad-Coverage RF Modulation Recognition cites this paper.

An Uncertainty-Driven Hybrid Deep Learning Approach for Broad-Coverage RF Modulation Recognition Enhancing Automatic Modulation Recognition through Robust Global Feature Extraction

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T00:15:37.665891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T00:15:37.665891Z digest=sha256:671634a24ec3d0f61251a4810a47245b5e43fbce9c894484ff78ec3d20a1ddbf