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Paper Citation Record · LEDGER

Scaling Up Resonate-and-Fire Networks for Fast Deep Learning

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2504.00719.

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

pith.paper-citation-record.v1
2504.00719 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:29:09.663223Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T11:07:15.279207Z

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 c97e3444-4948-481d-8b8b-d3bbd9e2a004 · inbound

SiLIF: Structured State Space Model Dynamics and Parametrization for Spiking Neural Networks cites this paper.

SiLIF: Structured State Space Model Dynamics and Parametrization for Spiking Neural Networks Scaling Up Resonate-and-Fire Networks for Fast Deep Learning

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:07:15.280718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-19T11:05:05.783726Z digest=sha256:a87e872424e8950af68ebc75fb37b159a3ec1def35a0f0c377bb3d92517d2ba9

Observation c0da5b9f-4f8e-453c-a529-78a5492265ab · inbound

Phase State Space Models: Parallel, Surrogate-Free Training of Spiking Networks cites this paper.

Phase State Space Models: Parallel, Surrogate-Free Training of Spiking Networks Scaling Up Resonate-and-Fire Networks for Fast Deep Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T00:29:09.663223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:29:09.663223Z digest=sha256:418df69c0d0dfb106d9eb28bd2718bd70700a2e4c59d6b73227d0179dc4fa84c