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Paper Citation Record · LEDGER

SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.14302.

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

pith.paper-citation-record.v1
2403.14302 v2

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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:12:23.926171Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T08:19:52.499326Z

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 86e46bda-6390-4e00-a688-00a6e866b4c3 · inbound

Quantized Spike-driven Transformer cites this paper.

Quantized Spike-driven Transformer SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T16:12:23.926171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:12:23.926171Z digest=sha256:5989e19431aefdb4ca75c6b6aaac08667398971ca37699c48cef179b652d1a91

Observation af065ea8-5d25-4964-b502-7bc8b43de4cb · inbound

Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers cites this paper.

Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:19:52.501185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-21T08:17:45.899981Z digest=sha256:bb244513859d6f30a7324b6d019a88d7d2f471f0cd0987b037a627c00eebeba3