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Paper Citation Record · LEDGER

Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2409.02111.

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

pith.paper-citation-record.v1
2409.02111 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:31:33.262953Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 79fc2d84-4104-41c8-b0b6-8937c4d899d1 · inbound

Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment cites this paper.

Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T13:57:21.302891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:57:21.302891Z digest=sha256:aa5b35a172becfeb284579426ae1fad52f27ce3c4763e9bda6803cc26c8d42bf

Observation 4b4522b0-a4ae-4cd0-a50e-bde1aad2c0e3 · inbound

Spiking Neural Networks for Temporal Processing: Status Quo and Future Prospects cites this paper.

Spiking Neural Networks for Temporal Processing: Status Quo and Future Prospects Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T21:29:16.115490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:29:16.115490Z digest=sha256:a4a6cfa20e6a0fab27f1325f9997fb1d0b6ae63cf5099b93f510aad5d21ad239

Observation f9899c2d-d053-4259-9442-db1820cb1600 · inbound

Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks cites this paper.

Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-22T16:01:46.015034Z

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=2026-05-22T15:58:41.801748Z digest=sha256:d56daab039620b3d2bf1024554203b0b6f11806a9da70838324b0b9b746b3713

Observation 17591edc-afa2-4f76-b545-765abb84ba16 · inbound

Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems cites this paper.

Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-19T04:42:04.852843Z

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=2026-05-19T04:37:33.928616Z digest=sha256:d125ef474cefecad0bca5ddaa3ac947ae1503b90ac69f33a782b662580cd4857

Observation 0b0d1e80-4c44-4a00-8fc0-ef95787bd2bf · inbound

A Multiplication-Free Spike-Time Learning Algorithm and its Efficient FPGA Implementation for On-Chip SNN Training cites this paper.

A Multiplication-Free Spike-Time Learning Algorithm and its Efficient FPGA Implementation for On-Chip SNN Training Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T21:06:11.618825Z

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=2026-05-08T07:04:10.712160Z digest=sha256:d36135ec85917245f22caf4421beea666bce47838582e6b6be1d121dc7dd203f

Observation ec142599-9991-44a7-82c5-f8ac9dbd0ca9 · inbound

NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework cites this paper.

NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-15T03:14:51.575153Z

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=2026-05-15T03:10:19.726961Z digest=sha256:00b5578923ec73a173487361e5121bdf6d78d93c8e0c1c5718371b911758b6bb

Observation 1507b536-5b74-40c0-b1dd-033c0e1f0013 · inbound

LongSpike: Fractional Order Spiking State Space Models for Efficient Long Sequence Learning cites this paper.

LongSpike: Fractional Order Spiking State Space Models for Efficient Long Sequence Learning Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:48:21.537910Z

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=2026-06-27T07:26:58.608421Z digest=sha256:8c0d1929419a3aaccd3b8d5ed829fcfa6ebd72f3441a99d00da460d0d65ee8ba

Observation 530494e3-6ba0-41d7-a144-cac623d5d985 · inbound

Lapis: Laplacian Spiking Attention via First-Spike Timing and Membrane Leakage cites this paper.

Lapis: Laplacian Spiking Attention via First-Spike Timing and Membrane Leakage Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T00:31:33.262953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:31:33.262953Z digest=sha256:2e329f3097c7ef809bca024674f109b149a92fb8af04e0d259ff3cd34d6a8242