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Paper Citation Record · LEDGER

SynA-ResNet: Spike-driven ResNet Achieved through OR Residual Connection

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.06570.

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

pith.paper-citation-record.v1
2311.06570 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T19:48:29.933520Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T19:55:01.652205Z

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 000995cd-f84d-41ff-b4d1-c5fdeaf98080 · inbound

Quantization of Spiking Neural Networks Beyond Accuracy cites this paper.

Quantization of Spiking Neural Networks Beyond Accuracy SynA-ResNet: Spike-driven ResNet Achieved through OR Residual Connection

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-10T12:50:25.045434Z

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=2026-05-10T12:48:10.403053Z digest=sha256:591ab17e35f77025db7ba6b5dbabde9cd58959b1101d6d8b83bae1ffb26c3cc4

Observation cccc9c4c-670a-483d-9974-bac67ee6e65e · inbound

XOResNet: Exclusive-OR Meta-Residuals Facilitate Deep Spiking Neural Networks Learning cites this paper.

XOResNet: Exclusive-OR Meta-Residuals Facilitate Deep Spiking Neural Networks Learning SynA-ResNet: Spike-driven ResNet Achieved through OR Residual Connection

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-06-30T19:55:01.653743Z

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=2026-06-30T19:48:29.933520Z digest=sha256:0b006ea7d925481a8b15200ac19f9385061a18b9de9a0f0acfe44f6bb1bc8436