Paper Citation Record · LEDGER

Deep Reinforcement Learning with Spiking Q-learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2201.09754.

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

pith.paper-citation-record.v1
2201.09754 v3

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 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:17:01.598346Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T19:47:01.174040Z

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 a2b9c66d-94ca-49c8-9be3-ea9c89da0944 · inbound

MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents cites this paper.

MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents Deep Reinforcement Learning with Spiking Q-learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T21:17:01.598346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1046a792-804a-4f1a-abe8-a6807937f619 · inbound

SpikingSoft: A Spiking Neuron Controller for Bio-inspired Locomotion with Soft Snake Robots cites this paper.

SpikingSoft: A Spiking Neuron Controller for Bio-inspired Locomotion with Soft Snake Robots Deep Reinforcement Learning with Spiking Q-learning

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T21:31:19.936732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b91b369-00cb-40f9-90f8-0414342b57a7 · inbound

Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents cites this paper.

Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents Deep Reinforcement Learning with Spiking Q-learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-22T19:47:01.176024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8089d840-0a9e-41ee-b4e9-ae4360b30fbe · inbound

Hardware-Aware Fine-Tuning of Spiking Q-Networks on the SpiNNaker2 Neuromorphic Platform cites this paper.

Hardware-Aware Fine-Tuning of Spiking Q-Networks on the SpiNNaker2 Neuromorphic Platform Deep Reinforcement Learning with Spiking Q-learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T10:42:21.877287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bafeb540-908c-48f8-859e-f1a0209b6fc3 · inbound

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

Error Amplification Limits ANN-to-SNN Conversion in Continuous Control Deep Reinforcement Learning with Spiking Q-learning

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-03T06:57:05.558351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3cf626e-4f66-4efc-ade9-8337c72c4fc0 · 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 Deep Reinforcement Learning with Spiking Q-learning

Reference 153

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:14:53.280301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 84a97c91-3f83-413e-b634-1091882f30b5 · inbound

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation cites this paper.

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation Deep Reinforcement Learning with Spiking Q-learning

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-21T04:53:58.099273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e663f7a3-211b-4a85-a3d8-e4312e8ed75b · inbound

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation cites this paper.

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation Deep Reinforcement Learning with Spiking Q-learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T13:36:09.816511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.