Pith. sign in

Paper Citation Record · LEDGER

DRiVE: Dynamic Recognition in VEhicles using snnTorch

As of 10 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2502.10421.

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

pith.paper-citation-record.v1
2502.10421 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:00:09.344019Z

measured 18 of 18 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

  • verified exact7
  • verified fuzzy2
  • unresolved8
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e698c305-e744-4e41-a686-dc6e9d8f5144 · outbound

This paper cites Spiking Neural Networks and Their Applications: A Review,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Spiking Neural Networks and Their Applications: A Review,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.290840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.290840Z digest=sha256:22413efaf7e6a05ddd974bdb72b126b8b7032da6eadbd819a7fd4661233b2f5d

Observation 703d3e8e-2d87-4ec6-998e-55bf1ad79b1c · outbound

This paper cites Training Spiking Neural Networks Using Lessons From Deep Learning,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Training Spiking Neural Networks Using Lessons From Deep Learning,

Reference 2

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T13:00:09.987636Z

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.

source=pdf_text observed=2026-08-09T13:00:09.293990Z digest=sha256:1cd88bbdda9fc63a2edd692c21c7494b67aef325d50d64a2b6115f275d97103d

Observation 278f96fe-7947-4e7f-9a7e-b12d2f3c45b5 · outbound

This paper cites A Review of Object Detection Models based on Convolutional Neural Network,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch A Review of Object Detection Models based on Convolutional Neural Network,

Reference 3

Resolution
verified exact
doi, observed 2026-08-09T13:00:09.456953Z

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.

source=pdf_text observed=2026-08-09T13:00:09.296964Z digest=sha256:5c966b355225234600faa6b87f3b62841d3d2d091a158d550e7b23eb06f176b5

Observation 75e6fb41-459d-4aad-9ef4-c5584e06fe65 · outbound

This paper cites A Review on Traditional and Deep Learning based Object Detection Methods,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch A Review on Traditional and Deep Learning based Object Detection Methods,

Reference 4

Resolution
verified exact
arxiv_id_nonexistent, observed 2026-08-09T13:00:09.653821Z

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.

source=pdf_text observed=2026-08-09T13:00:09.299466Z digest=sha256:25f78c6671e850d86b29255dfcb10c7c39a768748c13871135a5a56c072ee944

Observation ff6191ef-7869-4cf4-9724-989f87608033 · outbound

This paper cites A Comprehensive Review of Spiking Neural Networks: Interpretation, Optimization, Efficiency, and Best Practices.

DRiVE: Dynamic Recognition in VEhicles using snnTorch A Comprehensive Review of Spiking Neural Networks: Interpretation, Optimization, Efficiency, and Best Practices

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.304478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.304478Z digest=sha256:e5622ae402da9fe1f339c623630be9319c6cedda2f0592f246937ee9a3fcfa09

Observation 3e3a2d0c-62da-49eb-b692-6084b20969db · outbound

This paper cites Parallelized Multi-Agent Bayesian Optimization in Lava.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Parallelized Multi-Agent Bayesian Optimization in Lava

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-09T13:00:09.438033Z

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.

source=pdf_text observed=2026-08-09T13:00:09.307441Z digest=sha256:6536e4b000ac2dcbb710ed4a02d003610e8a980e97cd36e2eff1a8e8a5be457a

Observation 2a50a285-856c-4d4c-a8cf-7d3d796001ef · outbound

This paper cites On Neuromorphic Computing: A Case Study on Radio Resource Allocation with LAVA Software Framework,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch On Neuromorphic Computing: A Case Study on Radio Resource Allocation with LAVA Software Framework,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:00:10.005899Z

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.

source=pdf_text observed=2026-08-09T13:00:09.309945Z digest=sha256:5de629b98c345cc454330062f649f7c3820ab9c1cd7e1f9adb0ecca371abdcdd

Observation 4bc7881d-4474-4749-9332-0d6eaabe6e3d · outbound

This paper cites Recognizing Images with at most one Spike per Neuron.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Recognizing Images with at most one Spike per Neuron

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-09T13:00:09.427513Z

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.

source=pdf_text observed=2026-08-09T13:00:09.312003Z digest=sha256:f51029d91c4e222ce3c5ff4a123fc2699a8bcdb0375a467d4f18552b530ce0f1

Observation 4e63512c-c3dc-45d1-9daf-2447b2550ddd · outbound

This paper cites Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.315127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.315127Z digest=sha256:a94fa1890788f8d70275e60b5d485bd31c250b10dcf241a896907e6adeb469fb

Observation 75fac64c-2938-413b-9c98-fe82cf88a9ea · outbound

This paper cites Keys to accurate feature extraction using residual spiking neural networks,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Keys to accurate feature extraction using residual spiking neural networks,

Reference 11

Resolution
verified exact
doi, observed 2026-08-09T13:00:09.410259Z

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.

source=pdf_text observed=2026-08-09T13:00:09.319008Z digest=sha256:513dda398b1dd03cb230184335e3d788d82e269559b8bfc0a40df4e984504003

Observation 6f45d290-69be-425c-9e29-f80eff3c69ac · outbound

This paper cites Fast Convergence of Competitive Spiking Neural Networks with Sample -Based Weight Initialization,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Fast Convergence of Competitive Spiking Neural Networks with Sample -Based Weight Initialization,

Reference 12

Resolution
malformed identifier
no resolver link, observed 2026-08-09T13:00:09.321849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.321849Z digest=sha256:75067db457a6951abad8fa74cc106f16cbb6075809b8a8784cf4fbd3a8efd2e2

Observation 648bba46-8066-473b-b0b2-83eadf39aba3 · outbound

This paper cites (PDF) Research Progress of spiking neural network in image classification: a review,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch (PDF) Research Progress of spiking neural network in image classification: a review,

Reference 13

Resolution
verified exact
doi, observed 2026-08-09T13:00:09.401091Z

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.

source=pdf_text observed=2026-08-09T13:00:09.324556Z digest=sha256:7e50b7f9f833a566bbef2ce0beedddaf4caf9a7fb6e1a95a6a6a463908765ac6

Observation 342051ea-e980-403f-81ba-00dffa27fb5e · outbound

This paper cites SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks,.

DRiVE: Dynamic Recognition in VEhicles using snnTorch SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.327366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.327366Z digest=sha256:2bb2eaa492f0b12b51636f33bf1c81e7c16c4adaa0cf41b119fb34be8364ade1

Observation c3aa7508-9a9b-4639-b938-68036d802500 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Adam: A Method for Stochastic Optimization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.330779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.330779Z digest=sha256:74b092be74f798651603e6fdb65647444e88bf0a450ccb7b8c79ed4d896e9b08

Observation 64055f2c-a5b3-469e-9042-8d3355361e2e · outbound

This paper cites Decoupled Weight Decay Regularization.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Decoupled Weight Decay Regularization

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.333645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.333645Z digest=sha256:9f14bcffea008eb8f3f4005c244811c17593355ab4712da95e837cd0e8592b5f

Observation cacf87bb-8f2a-4daa-8aab-9a54561e896a · outbound

This paper cites Surrogate Gradient Learning in Spiking Neural Networks.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Surrogate Gradient Learning in Spiking Neural Networks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.336835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.336835Z digest=sha256:2d6ff86f8d907fc115623358ce25441d51240a66e74a86068402a0ae455a35c3

Observation fe46cae2-ea85-4aaf-a504-96ef6f210f0d · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T13:00:09.340324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:00:09.340324Z digest=sha256:406aa7543832360ee52e61864e379662b4018844eed2b007a18c9d570a881bec

Observation a1dd7dce-4446-437e-85ea-da247b1fc883 · outbound

This paper cites Vehicle Detection Image Set.

DRiVE: Dynamic Recognition in VEhicles using snnTorch Vehicle Detection Image Set

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:00:09.997062Z

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.

source=pdf_text observed=2026-08-09T13:00:09.344019Z digest=sha256:3df06b474587b2bc1424740769467a4898af9cfa035dd281d9cb49d22788dc92

Pith citing papers

No inbound Pith citation observations are available.