Paper Citation Record · LEDGER

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing

As of 13 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2411.17439.

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

pith.paper-citation-record.v1
2411.17439 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:11:03.032478Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

35 of 35 outbound references displayed

verified exact0
verified fuzzy12
unresolved23
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2a970a3b-33de-4e6b-b960-89ade790a333 · outbound

This paper cites Networks of spiking neurons: the third generation of neural network models.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Networks of spiking neurons: the third generation of neural network models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.902866Z

Source-reported events for the cited work

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Observation 61ee27b6-9907-4ef1-bfdb-1a703af53017 · outbound

This paper cites Towards spike-based machine intelligence with neuromorphic computing.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Towards spike-based machine intelligence with neuromorphic computing

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.906884Z

Source-reported events for the cited work

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Observation 304d75f7-313c-4a69-8c49-83e778347aaf · outbound

This paper cites Brain-inspired computing: A systematic survey and future trends.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Brain-inspired computing: A systematic survey and future trends

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.335303Z

Source-reported events for the cited work

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Observation 2aaaa434-20ec-4e50-8562-7af21c3668bc · outbound

This paper cites Bottom-up and top-down approaches for the design of neuromorphic processing systems: tradeoffs and synergies between natural and artificial intelligence.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Bottom-up and top-down approaches for the design of neuromorphic processing systems: tradeoffs and synergies between natural and artificial intelligence

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.324065Z

Source-reported events for the cited work

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Observation 13a7a15b-0521-42a5-a1af-0a96ce737095 · outbound

This paper cites A million spiking-neuron integrated circuit with a scalable communication network and interface.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing A million spiking-neuron integrated circuit with a scalable communication network and interface

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.918678Z

Source-reported events for the cited work

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Observation be4a5c1f-5ccb-472d-99a3-9bfd3186422b · outbound

This paper cites Loihi: A neuromorphic manycore processor with on-chip learning.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Loihi: A neuromorphic manycore processor with on-chip learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.922825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67479223-1a44-48c7-92e8-78c438596f72 · outbound

This paper cites Towards artificial general intelligence with hybrid tianjic chip architecture.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Towards artificial general intelligence with hybrid tianjic chip architecture

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.926765Z

Source-reported events for the cited work

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Observation be8ed956-8e94-40a9-a7e4-0308aa02ee81 · outbound

This paper cites Backpropagation applied to handwritten zip code recognition.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Backpropagation applied to handwritten zip code recognition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.294271Z

Source-reported events for the cited work

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Observation e0a8663e-ee73-4cf3-aa19-8ebcf0999eb8 · outbound

This paper cites Progressive tandem learning for pattern recognition with deep spiking neural networks.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Progressive tandem learning for pattern recognition with deep spiking neural networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.282530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1f009c89-3c35-4d52-89df-9c15d659a005 · outbound

This paper cites Attention is all you need.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Attention is all you need

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.937377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf5ca3aa-245e-42e6-b3dd-4e839b7eb12f · outbound

This paper cites Spiking transformers for event-based single object tracking.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Spiking transformers for event-based single object tracking

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.266567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a7ba75a5-d6da-41d1-b642-a4ebaae6ff96 · outbound

This paper cites Spik- former: When spiking neural network meets transformer.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Spik- former: When spiking neural network meets transformer

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.255855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 71bc3a04-03b5-412f-aa45-81f5d9c2cf04 · outbound

This paper cites Spike-driven transformer.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Spike-driven transformer

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.244564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4fdf7221-cc14-409e-9392-9293289013c3 · outbound

This paper cites Learning representations by back-propagating errors.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Learning representations by back-propagating errors

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.951949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03c3165a-e313-4556-a366-155c661b43e4 · outbound

This paper cites Optimal conversion of conventional artificial neural networks to spiking neural networks.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Optimal conversion of conventional artificial neural networks to spiking neural networks

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.955334Z

Source-reported events for the cited work

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Observation cf42bafe-0d43-46a8-be7e-e71f5101ff2b · outbound

This paper cites Advancing spiking neural networks toward deep residual learning.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Advancing spiking neural networks toward deep residual learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.221067Z

Source-reported events for the cited work

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Observation 97fc9f95-8f1b-4c46-8a5e-5bb8d18a9bf6 · outbound

This paper cites Spatio-temporal backpropagation for training high- performance spiking neural networks.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Spatio-temporal backpropagation for training high- performance spiking neural networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.210333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d70d97f9-ac8d-495c-bdeb-54601851f85e · outbound

This paper cites Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.966352Z

Source-reported events for the cited work

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Observation add7785d-199a-4ce2-99a5-878e4d721b53 · outbound

This paper cites Deep residual learning for image recognition.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Deep residual learning for image recognition

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.969979Z

Source-reported events for the cited work

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Observation 3647fb5e-048a-441f-b436-4b58c1dbed55 · outbound

This paper cites Going deeper with directly-trained larger spiking neural networks.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Going deeper with directly-trained larger spiking neural networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.974385Z

Source-reported events for the cited work

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Observation 4b734411-e3bf-45fa-80b1-9977fa5653ab · outbound

This paper cites Deep residual learning in spiking neural networks.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Deep residual learning in spiking neural networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.179988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4f22c00a-4413-49eb-a61a-b1e8f50b82f5 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing An image is worth 16x16 words: Transformers for image recognition at scale

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.983122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5637252-c6c4-42cc-9bb4-8e7d58a98c3e · outbound

This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convolutions.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Pyramid vision transformer: A versatile backbone for dense prediction without convolutions

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.986461Z

Source-reported events for the cited work

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Observation 5030e052-6313-40f8-a179-c1d0f2a35a8d · outbound

This paper cites Mlp-mixer: An all-mlp architecture for vision.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Mlp-mixer: An all-mlp architecture for vision

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.991021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c2483b5-1259-42b3-b293-8cae05549580 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Swin transformer: Hierarchical vision transformer using shifted windows

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.994498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 749cb31e-aa6f-4c45-8d88-9150bc92c4a3 · outbound

This paper cites Twins: Revisiting the design of spatial attention in vision transformers.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Twins: Revisiting the design of spatial attention in vision transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:02.998098Z

Source-reported events for the cited work

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Observation 6ac325e8-a37c-48f2-9805-436dadf65373 · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:03.002696Z

Source-reported events for the cited work

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Observation 7b07fed9-98a5-4d1a-8e1a-a050872a3233 · outbound

This paper cites Convnext v2: Co-designing and scaling convnets with masked autoencoders.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Convnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:03.007001Z

Source-reported events for the cited work

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Observation eca53ad6-508c-473f-ae52-2fab67a5e4e1 · outbound

This paper cites Maxvit: Multi-axis vision transformer.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Maxvit: Multi-axis vision transformer

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:03.010818Z

Source-reported events for the cited work

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Observation ba9f809f-4108-4547-b287-b5105abd85e0 · outbound

This paper cites Coatnet: Marrying convolution and attention for all data sizes.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Coatnet: Marrying convolution and attention for all data sizes

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.120400Z

Source-reported events for the cited work

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Observation d5a17344-319c-41b5-84f6-dc16b33339fc · outbound

This paper cites Learning multiple layers of features from tiny images.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Learning multiple layers of features from tiny images

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:03.018543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52713ad6-54e3-49e8-ae06-64aa8f41ebae · outbound

This paper cites Decoupled Weight Decay Regularization.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Decoupled Weight Decay Regularization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:03.021914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c62426c1-3d3b-4060-9d2e-f9244854ca2a · outbound

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

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Imagenet: A large-scale hierarchical image database

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:03.025302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36a0326f-5f89-4ea9-86e1-b949d8b610ba · outbound

This paper cites How Does Mixup Help With Robustness and Generalization?.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing How Does Mixup Help With Robustness and Generalization?

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-12T12:11:03.028742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b05babcb-c47a-4fc4-bd28-df60e46c87af · outbound

This paper cites Cutmix: Regularization strategy to train strong classifiers with localizable features.

SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing Cutmix: Regularization strategy to train strong classifiers with localizable features

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T12:11:03.093680Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.