Paper Citation Record · LEDGER

TS-SNN: Temporal Shift Module for Spiking Neural Networks

As of 19 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2505.04165.

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

pith.paper-citation-record.v1
2505.04165 v5

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:39:27.855020Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T03:34:36.242244Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:26:54.914004Z

Reference resolution

64 of 64 outbound references displayed

verified exact8
verified fuzzy27
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3d1493fe-6485-4cd9-9b7e-0556500c543d · outbound

This paper cites write newline.

TS-SNN: Temporal Shift Module for Spiking Neural Networks write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.583231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38704e9b-2569-48ee-bf0e-00c4d697e734 · outbound

This paper cites and Pereda, A.

TS-SNN: Temporal Shift Module for Spiking Neural Networks and Pereda, A

Reference 2

Resolution: verified exact; doi, observed 2026-08-15T23:39:27.975704Z

Source-reported events for the cited work

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Observation 97ef6aa7-dcb7-47f2-aba7-39889af0b0f3 · outbound

This paper cites and Poo, M.-m.

TS-SNN: Temporal Shift Module for Spiking Neural Networks and Poo, M.-m

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.442979Z

Source-reported events for the cited work

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Observation dc1410e6-55b4-46d4-816d-ce2662d97f9c · outbound

This paper cites A Fully Spiking Hybrid Neural Network for Energy - Efficient Object Detection.

TS-SNN: Temporal Shift Module for Spiking Neural Networks A Fully Spiking Hybrid Neural Network for Energy - Efficient Object Detection

Reference 4

Resolution: metadata mismatch; raw_fallback, observed 2026-08-15T23:39:29.094238Z

Source-reported events for the cited work

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Observation b918f195-ec94-4ea8-916c-4868be69d2a8 · outbound

This paper cites Learnable Gated Temporal Shift Module for Deep Video Inpainting.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Learnable Gated Temporal Shift Module for Deep Video Inpainting

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.604851Z

Source-reported events for the cited work

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Observation b058cbfa-d1a7-4017-b55e-eb2a4d65fdbe · outbound

This paper cites Training Full Spike Neural Networks via Auxiliary Accumulation Pathway.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Training Full Spike Neural Networks via Auxiliary Accumulation Pathway

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.609591Z

Source-reported events for the cited work

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Observation 4802b726-892a-4c8e-9639-7a51e340e783 · outbound

This paper cites All You Need Is a Few Shifts : Designing Efficient Convolutional Neural Networks for Image Classification.

TS-SNN: Temporal Shift Module for Spiking Neural Networks All You Need Is a Few Shifts : Designing Efficient Convolutional Neural Networks for Image Classification

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.431535Z

Source-reported events for the cited work

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Observation 08d53cd5-e60e-4266-b31e-afcdd103d681 · outbound

This paper cites Tensor Decomposition Based Attention Module for Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Tensor Decomposition Based Attention Module for Spiking Neural Networks

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:39:28.994783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a8b2f9d2-561e-4e13-8f3d-97d31ce19435 · outbound

This paper cites ImageNet : A large-scale hierarchical image database.

TS-SNN: Temporal Shift Module for Spiking Neural Networks ImageNet : A large-scale hierarchical image database

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39c5244e-7b67-4516-b712-3149c08b53ae · outbound

This paper cites Temporal Efficient Training of Spiking Neural Network via Gradient Re -weighting.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Temporal Efficient Training of Spiking Neural Network via Gradient Re -weighting

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.418228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 242bc098-143a-45b7-8e71-2c54eff8d6b4 · outbound

This paper cites Dynamic Image Quantization Using Leaky Integrate -and- Fire Neurons.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Dynamic Image Quantization Using Leaky Integrate -and- Fire Neurons

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.634227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bc75c41-bc2d-43a4-a33f-b6349d9ecf1a · outbound

This paper cites Temporal Effective Batch Normalization in Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Temporal Effective Batch Normalization in Spiking Neural Networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.405972Z

Source-reported events for the cited work

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Observation 914f2107-ba89-4577-bee5-5d2aba3483a7 · outbound

This paper cites Deep Residual Learning in Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Deep Residual Learning in Spiking Neural Networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.393286Z

Source-reported events for the cited work

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Observation ab9f7657-f7aa-4111-a8e0-60d300ad7f63 · outbound

This paper cites Incorporating Learnable Membrane Time Constant To Enhance Learning of Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Incorporating Learnable Membrane Time Constant To Enhance Learning of Spiking Neural Networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.381618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 22874c8c-e74f-4d21-ba7e-933d9ff43bbb · outbound

This paper cites and Zhao, J.

TS-SNN: Temporal Shift Module for Spiking Neural Networks and Zhao, J

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.369730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 419220eb-d128-405f-bd55-89af9c24b4af · outbound

This paper cites Minimal solutions for relative pose with a single affine correspondence.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Minimal solutions for relative pose with a single affine correspondence

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.355010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2dc53c23-2c42-40a8-bc9e-0551565581b1 · outbound

This paper cites Multi-dimensional pruning: A unified framework for model compression.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Multi-dimensional pruning: A unified framework for model compression

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.342713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b32e7ad8-c812-4020-9662-0b77df6d0999 · outbound

This paper cites Multidimensional pruning and its extension: A unified framework for model compression.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Multidimensional pruning and its extension: A unified framework for model compression

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.329907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7d1afced-b3c9-48b3-947a-de203136b772 · outbound

This paper cites IM - Loss : Information Maximization Loss for Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks IM - Loss : Information Maximization Loss for Spiking Neural Networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.317634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6ee845b-0020-414c-b4dc-eb22940a4a74 · outbound

This paper cites RecDis - SNN : Rectifying Membrane Potential Distribution for Directly Training Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks RecDis - SNN : Rectifying Membrane Potential Distribution for Directly Training Spiking Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.674483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 644c29a7-9d02-44b2-a128-1c2487535d29 · outbound

This paper cites Real Spike : Learning Real - Valued Spikes for Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Real Spike : Learning Real - Valued Spikes for Spiking Neural Networks

Reference 21

Resolution: verified exact; doi, observed 2026-08-15T23:39:27.963071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 97d508c4-cd3c-4e80-88bd-136217dbe7e6 · outbound

This paper cites RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:39:28.788146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 669e26d6-ab37-456b-b0e3-6b8628a6dace · outbound

This paper cites Membrane Potential Batch Normalization for Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Membrane Potential Batch Normalization for Spiking Neural Networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.305124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0f1bcf92-66bf-4791-baf0-cf8ddd93dff1 · outbound

This paper cites and Roy, K.

TS-SNN: Temporal Shift Module for Spiking Neural Networks and Roy, K

Reference 24

Resolution: verified exact; doi, observed 2026-08-15T23:39:27.951961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c14e0102-191e-4807-acf3-2ab4c0f72496 · outbound

This paper cites Deep Residual Learning for Image Recognition.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Deep Residual Learning for Image Recognition

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.293747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7e77e05b-f9d4-4433-8f9f-afea809fc65d · outbound

This paper cites an unresolved cited work.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:39:29.282036Z

Source-reported events for the cited work

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Observation 09e389f3-1855-43e2-b7f0-488df31bab51 · outbound

This paper cites 1.1 Computing 's energy problem (and what we can do about it).

TS-SNN: Temporal Shift Module for Spiking Neural Networks 1.1 Computing 's energy problem (and what we can do about it)

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.703164Z

Source-reported events for the cited work

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Observation 488573b3-d9cc-45d9-8fd2-7af2dc1f00c3 · outbound

This paper cites Advancing Spiking Neural Networks Toward Deep Residual Learning.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Advancing Spiking Neural Networks Toward Deep Residual Learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.708214Z

Source-reported events for the cited work

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Observation 944523ed-dbfb-4b33-9256-63806fa571df · outbound

This paper cites and Kim, J.

TS-SNN: Temporal Shift Module for Spiking Neural Networks and Kim, J

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.270946Z

Source-reported events for the cited work

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Observation a136c579-4db1-48fb-84d3-c85b19f4c761 · outbound

This paper cites Cifar-10 (canadian institute for advanced research).

TS-SNN: Temporal Shift Module for Spiking Neural Networks Cifar-10 (canadian institute for advanced research)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.259090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b14737f5-74b4-48b6-842c-6fc7a8085eee · outbound

This paper cites S., Panda, P., Srinivasan, G., and Roy, K.

TS-SNN: Temporal Shift Module for Spiking Neural Networks S., Panda, P., Srinivasan, G., and Roy, K

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.720431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 023e9615-3b8a-40aa-b9c2-63b1390fc083 · outbound

This paper cites C., See, S., Wang, X., Qin, H., and Li, H.

TS-SNN: Temporal Shift Module for Spiking Neural Networks C., See, S., Wang, X., Qin, H., and Li, H

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.724914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18d091f2-41e7-4a60-8ede-79e2f9eb37f6 · outbound

This paper cites Cifar10-dvs: an event-stream dataset for object classification.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Cifar10-dvs: an event-stream dataset for object classification

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.246965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b845dc6f-047e-43bd-a93f-b37ad3100f66 · outbound

This paper cites CIFAR10 - DVS : An Event - Stream Dataset for Object Classification.

TS-SNN: Temporal Shift Module for Spiking Neural Networks CIFAR10 - DVS : An Event - Stream Dataset for Object Classification

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.733016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d13e2ea-bef7-48ec-9695-ab5f19e7bbc6 · outbound

This paper cites Spikeformer: A Novel Architecture for Training High-Performance Low-Latency Spiking Neural Network.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Spikeformer: A Novel Architecture for Training High-Performance Low-Latency Spiking Neural Network

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.736965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dabd4f3c-0293-48ca-9671-de19dd23ddc3 · outbound

This paper cites Learnable Surrogate Gradient for Direct Training Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Learnable Surrogate Gradient for Direct Training Spiking Neural Networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.741596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe967635-d89a-499b-b90c-6495b9362594 · outbound

This paper cites IM - LIF : Improved Neuronal Dynamics With Attention Mechanism for Direct Training Deep Spiking Neural Network.

TS-SNN: Temporal Shift Module for Spiking Neural Networks IM - LIF : Improved Neuronal Dynamics With Attention Mechanism for Direct Training Deep Spiking Neural Network

Reference 37

Resolution: metadata mismatch; raw_fallback, observed 2026-08-15T23:39:28.427292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6a34b99-1917-4e5b-8418-8e978ed23c2e · outbound

This paper cites TSM : Temporal Shift Module for Efficient Video Understanding.

TS-SNN: Temporal Shift Module for Spiking Neural Networks TSM : Temporal Shift Module for Efficient Video Understanding

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.232035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0e72e3c2-4d25-4b68-b5b8-5a319d406276 · outbound

This paper cites Swin Transformer : Hierarchical Vision Transformer Using Shifted Windows.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Swin Transformer : Hierarchical Vision Transformer Using Shifted Windows

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.217126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a83f83f8-a7a5-475c-949f-37f9e10502d7 · outbound

This paper cites O., Mostafa, H., and Zenke, F.

TS-SNN: Temporal Shift Module for Spiking Neural Networks O., Mostafa, H., and Zenke, F

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.756902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9474843e-4ce2-4f94-bd74-4f077d89890e · outbound

This paper cites A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses.

TS-SNN: Temporal Shift Module for Spiking Neural Networks A reconfigurable on-line learning spiking neuromorphic processor comprising 256 neurons and 128K synapses

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.760751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8de31af3-5efc-4494-94ec-c6f196f977aa · outbound

This paper cites and Roy, K.

TS-SNN: Temporal Shift Module for Spiking Neural Networks and Roy, K

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.764431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0caa4a4f-d688-45aa-9963-e57aa609dfec · outbound

This paper cites P., and McGinnity, T.

TS-SNN: Temporal Shift Module for Spiking Neural Networks P., and McGinnity, T

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.767944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95966085-e6ed-47a6-b72c-de168e7ebc1b · outbound

This paper cites an unresolved cited work.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Unresolved cited work

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.771747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c038fbd5-5a80-498b-ac6d-4b57e2588736 · outbound

This paper cites A New ANN - SNN Conversion Method with High Accuracy , Low Latency and Good Robustness.

TS-SNN: Temporal Shift Module for Spiking Neural Networks A New ANN - SNN Conversion Method with High Accuracy , Low Latency and Good Robustness

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.776020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7631cd5a-7f05-4491-8c02-ac74fd734fbe · outbound

This paper cites Spatial- Temporal Self - Attention for Asynchronous Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Spatial- Temporal Self - Attention for Asynchronous Spiking Neural Networks

Reference 46

Resolution: verified exact; doi, observed 2026-08-15T23:39:27.914744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4a40072c-0902-438c-9df2-46697997772d · outbound

This paper cites ACTION - Net : Multipath Excitation for Action Recognition.

TS-SNN: Temporal Shift Module for Spiking Neural Networks ACTION - Net : Multipath Excitation for Action Recognition

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.205464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9b2c0b92-ca67-4756-8976-c531416efeb0 · outbound

This paper cites Shift: A Zero FLOP , Zero Parameter Alternative to Spatial Convolutions.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Shift: A Zero FLOP , Zero Parameter Alternative to Spatial Convolutions

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.194396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e3602299-af36-4c99-b04f-ac478a510157 · outbound

This paper cites Spatio- Temporal Backpropagation for Training High - Performance Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Spatio- Temporal Backpropagation for Training High - Performance Spiking Neural Networks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.793255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5d86a02-6c83-4626-b977-c48e7f2a8e7b · outbound

This paper cites Direct Training for Spiking Neural Networks : Faster , Larger , Better.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Direct Training for Spiking Neural Networks : Faster , Larger , Better

Reference 50

Resolution: verified exact; doi, observed 2026-08-15T23:39:27.902219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 86cb8d7d-559e-4fd8-9bda-27a0abc5a6ab · outbound

This paper cites Biologically inspired structure learning with reverse knowledge distillation for spiking neural networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Biologically inspired structure learning with reverse knowledge distillation for spiking neural networks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.800280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35f61dcd-819d-4196-8216-b0fef6ea842e · outbound

This paper cites K., Tang, H., and Pan, G.

TS-SNN: Temporal Shift Module for Spiking Neural Networks K., Tang, H., and Pan, G

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.182549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8e4e7c5a-8937-4e75-9c52-08a2c7867355 · outbound

This paper cites Rsnn: Recurrent spiking neural networks for dynamic spatial-temporal information processing.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Rsnn: Recurrent spiking neural networks for dynamic spatial-temporal information processing

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.171314Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7925abca-5ca1-4426-9996-a837e1dd7fa7 · outbound

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

TS-SNN: Temporal Shift Module for Spiking Neural Networks Spiking Neural Networks and Their Applications : A Review

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.811773Z

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Unavailable: canonical work link unavailable.

Observation 6eef8bec-20d7-4ff0-ada0-48f95d3d503f · outbound

This paper cites Attention Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Attention Spiking Neural Networks

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.816262Z

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Observation fec70969-25b2-47e2-bc00-af083983e1e9 · outbound

This paper cites GLIF : A Unified Gated Leaky Integrate -and- Fire Neuron for Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks GLIF : A Unified Gated Leaky Integrate -and- Fire Neuron for Spiking Neural Networks

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.158593Z

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Observation b87768dd-0193-4ab4-9d44-382a3f481b67 · outbound

This paper cites Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.825997Z

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Observation 106c4b9a-2746-4dd5-b984-80a929b89805 · outbound

This paper cites Fsta-snn: Frequency-based spatial-temporal attention module for spiking neural networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Fsta-snn: Frequency-based spatial-temporal attention module for spiking neural networks

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.146509Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c263d5ba-1dea-44be-ac12-c15aaba13e10 · outbound

This paper cites S2- MLP : Spatial - Shift MLP Architecture for Vision.

TS-SNN: Temporal Shift Module for Spiking Neural Networks S2- MLP : Spatial - Shift MLP Architecture for Vision

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.135192Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c2178d18-d51b-459b-8ede-6d6a4f26e44e · outbound

This paper cites Da-lif: Dual adaptive leaky integrate-and-fire model for deep spiking neural networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Da-lif: Dual adaptive leaky integrate-and-fire model for deep spiking neural networks

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.118724Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 393981ab-f6b6-4215-b70a-c9f651778493 · outbound

This paper cites STAA-SNN: Spatial-Temporal Attention Aggregator for Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks STAA-SNN: Spatial-Temporal Attention Aggregator for Spiking Neural Networks

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:39:28.051722Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dc133548-1e79-4070-ba52-4b125f6c5f21 · outbound

This paper cites Going Deeper With Directly - Trained Larger Spiking Neural Networks.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Going Deeper With Directly - Trained Larger Spiking Neural Networks

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.846885Z

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Unavailable: canonical work link unavailable.

Observation c6b7fc5f-5567-4a92-9892-1d5e5a0fa928 · outbound

This paper cites Spike- Based Motion Estimation for Object Tracking Through Bio - Inspired Unsupervised Learning.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Spike- Based Motion Estimation for Object Tracking Through Bio - Inspired Unsupervised Learning

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T23:39:27.850356Z

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Observation 2240d6be-8324-42b5-b511-86caa825ca9d · outbound

This paper cites Spikformer: When Spiking Neural Network Meets Transformer.

TS-SNN: Temporal Shift Module for Spiking Neural Networks Spikformer: When Spiking Neural Network Meets Transformer

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:39:29.106885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation f767b5c8-a1fd-4691-b50a-7bc0a5a8f068 · inbound

QDS-SNN: Energy-efficient Quantum Deeply-Supervised Spiking Neural Network Algorithm for Traffic Sign Recognition cites this paper.

QDS-SNN: Energy-efficient Quantum Deeply-Supervised Spiking Neural Network Algorithm for Traffic Sign Recognition TS-SNN: Temporal Shift Module for Spiking Neural Networks

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:26:54.915252Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.