Paper Citation Record · LEDGER

Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2103.00476.

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

pith.paper-citation-record.v1
2103.00476 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T00:24:58.216992Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:05:45.727094Z

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 3b62ef99-be2c-4091-b034-5ab16e100854 · inbound

FAS: Fast ANN-SNN Conversion for Spiking Large Language Models cites this paper.

FAS: Fast ANN-SNN Conversion for Spiking Large Language Models Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T00:24:58.216992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29698e43-9244-46b6-b5de-2581639fbbbd · inbound

SDSNN: A Single-Timestep Spiking Neural Network with Self-Dropping Neuron and Bayesian Optimization cites this paper.

SDSNN: A Single-Timestep Spiking Neural Network with Self-Dropping Neuron and Bayesian Optimization Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:19.959442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74dfa550-e1fe-483e-aa34-93bc8e2f867b · inbound

EventTracer: Fast Path Tracing-based Event Stream Rendering cites this paper.

EventTracer: Fast Path Tracing-based Event Stream Rendering Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T16:41:01.940557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3118233f-d706-4ea6-a4f3-e2aa828a6b4b · inbound

Spiking Neural Network Architecture Search: A Survey cites this paper.

Spiking Neural Network Architecture Search: A Survey Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-18T07:01:01.383933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 00dc2972-b6b7-4db4-8213-247cd8dfc025 · inbound

Error Amplification Limits ANN-to-SNN Conversion in Continuous Control cites this paper.

Error Amplification Limits ANN-to-SNN Conversion in Continuous Control Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-03T06:57:05.563478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12d3ed40-312f-4a95-bbc1-57359fc124fe · inbound

STARS: Spike Tail-Aware Relational Synthesis for ANN-to-SNN Data-Free Knowledge Distillation cites this paper.

STARS: Spike Tail-Aware Relational Synthesis for ANN-to-SNN Data-Free Knowledge Distillation Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:45.731636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.