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Paper Citation Record · LEDGER

Spiking Neural Networks for event-based action recognition: A new task to understand their advantage

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.14915.

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

pith.paper-citation-record.v1
2209.14915 v3

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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:52:49.613140Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:43:03.931481Z

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 6cf73d44-7218-45cb-afc9-f37d22ffa3da · inbound

Making Every Event Count: Balancing Data Efficiency and Accuracy in Event Camera Subsampling cites this paper.

Making Every Event Count: Balancing Data Efficiency and Accuracy in Event Camera Subsampling Spiking Neural Networks for event-based action recognition: A new task to understand their advantage

Reference 46

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T13:43:04.074010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-07T13:43:02.747761Z digest=sha256:9b44b7b513d2cbf96519dc3c255241d019c6f0ac115b18eb1764bfbe6ff79901

Observation 2c55b330-91a6-426e-8df3-eea3cb029442 · inbound

Static in Frames, Dynamic in Events: Rethinking Features in Event Cameras as Motion Cues cites this paper.

Static in Frames, Dynamic in Events: Rethinking Features in Event Cameras as Motion Cues Spiking Neural Networks for event-based action recognition: A new task to understand their advantage

Reference 202

Resolution
unresolved
no resolver link, observed 2026-08-12T10:52:49.613140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T10:52:49.613140Z digest=sha256:68a78ef4fbc7aa429cccd8be8ccfdc304ade01009b753dc7a5c2c922e81dcd80