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Paper Citation Record · LEDGER

AT-SNN: Adaptive Tokens for Vision Transformer on Spiking Neural Network

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2408.12293.

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

pith.paper-citation-record.v1
2408.12293 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T04:31:33.656789Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T06:11:24.222272Z

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 45ca4f1e-d512-4239-8c0c-be030f8a1ff8 · inbound

Uncertainty-Aware Token Importance Estimation in Spiking Transformers cites this paper.

Uncertainty-Aware Token Importance Estimation in Spiking Transformers AT-SNN: Adaptive Tokens for Vision Transformer on Spiking Neural Network

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:11:24.237346Z

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=2026-05-12T04:31:33.656789Z digest=sha256:490ea8ec6f5034524ad2738a3d23f10ec99eb098837579ea303743a0c2245af0