Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:17:27.106516Z
Paper Citation Record · LEDGER
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity
As of 21 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2505.10352.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
62 of 62 outbound references displayed
- verified exact0
- verified fuzzy45
- unresolved17
- parse uncertain0
- malformed identifier0
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 18b632f1-643b-40ec-8080-2090134db896 · outbound
This paper cites Vivit: A video vision transformer.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Vivit: A video vision transformer
Reference 1
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6011be24-5026-4f30-b5b6-911ac9d2f66b · outbound
This paper cites Object domain and modality in the ventral visual pathway.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Object domain and modality in the ventral visual pathway
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d081d3b2-39cf-4f67-b4ea-63c92675d294 · outbound
This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
Reference 3
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 56238fd2-1854-4e00-a256-c98f4099cd42 · outbound
This paper cites Spiking diffusion models.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Spiking diffusion models
Reference 4
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 55a7dd01-7ae8-4e5d-ae6e-b4461b8d875e · outbound
This paper cites an unresolved cited work.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Unresolved cited work
Reference 5
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b1b2f721-139b-44dd-a3ca-9d9e92e9f013 · outbound
This paper cites Xception: Deep learning with depthwise separable convolutions.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Xception: Deep learning with depthwise separable convolutions
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9925fcf9-8480-40ac-9a8f-3de36d1f2a9d · outbound
This paper cites The cityscapes dataset for semantic urban scene understanding.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity The cityscapes dataset for semantic urban scene understanding
Reference 7
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 42f5f217-266c-43e5-be54-95cac7ace82a · outbound
This paper cites an unresolved cited work.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Unresolved cited work
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 97d269b3-c2c7-4c99-ba81-186d8cc7bbb3 · outbound
This paper cites Imagenet: A large-scale hierarchical image database.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Imagenet: A large-scale hierarchical image database
Reference 9
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 85c18986-87e9-4529-bbc0-620f30f4d1fd · outbound
This paper cites Repvgg: Making vgg-style convnets great again.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Repvgg: Making vgg-style convnets great again
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 71745088-5bcb-4c7e-8977-49c57e9a0750 · outbound
This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity An image is worth 16x16 words: Transformers for image recognition at scale
Reference 11
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4d2b8db0-8bb9-4847-9a85-cd7ccfa9eb1a · outbound
This paper cites Deep residual learning in spiking neural networks.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Deep residual learning in spiking neural networks
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9fd988ba-aee2-407b-ba5b-85a68c02b320 · 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.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Bottom-up and top-down approaches for the design of neuromorphic processing systems: tradeoffs and synergies between natural and artificial intelligence
Reference 13
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation defd1206-38e5-46c6-a5c0-be098880f558 · outbound
This paper cites Deep residual learning for image recognition.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Deep residual learning for image recognition
Reference 14
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a43f5724-9a8c-4726-9f45-63592dbef5eb · outbound
This paper cites 1.1 computing's energy problem (and what we can do about it).
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity 1.1 computing's energy problem (and what we can do about it)
Reference 15
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 5e4f7806-3a2d-40d2-a0d2-3a92545a2633 · outbound
This paper cites Fast-snn: Fast spiking neural network by converting quantized ann.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Fast-snn: Fast spiking neural network by converting quantized ann
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.681734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c5714a04-1aff-4edf-ae23-6c7e48ec11e5 · outbound
This paper cites Advancing spiking neural networks toward deep residual learning.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Advancing spiking neural networks toward deep residual learning
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.667247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ff2c24c7-5ab0-4d82-a041-239b5d2b29d3 · outbound
This paper cites N., Boufounos, P.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity N., Boufounos, P
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.652283Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c1a995ab-71c5-4d23-bf46-421f18dc2872 · outbound
This paper cites Fully spiking variational autoencoder.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Fully spiking variational autoencoder
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fb723168-2445-4694-b206-e8e88e136834 · outbound
This paper cites The Kinetics Human Action Video Dataset.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity The Kinetics Human Action Video Dataset
Reference 20
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation edb00f47-c01b-490c-b8e7-2c72c4224687 · outbound
This paper cites an unresolved cited work.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Unresolved cited work
Reference 21
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0ce42c3c-9783-4edc-ab48-267218d96248 · outbound
This paper cites M., Pandit, T., Merkel, C., Kubendran, R., Aimone, J.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity M., Pandit, T., Merkel, C., Kubendran, R., Aimone, J
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6a654a39-fc8d-4ad0-a103-c96702e47fa3 · outbound
This paper cites Brain-inspired computing: A systematic survey and future trends.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Brain-inspired computing: A systematic survey and future trends
Reference 23
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aeeae0d4-28a4-4381-82a7-900ee900b7c3 · outbound
This paper cites Firefly: A high-throughput hardware accelerator for spiking neural networks with efficient dsp and memory optimization.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Firefly: A high-throughput hardware accelerator for spiking neural networks with efficient dsp and memory optimization
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.598756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation cefce266-3d55-4119-ab3a-f306c1767e25 · outbound
This paper cites SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Network.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Network
Reference 25
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e15942a-553b-456f-99dc-5ae707ed5b2b · outbound
This paper cites Video swin transformer.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Video swin transformer
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.588777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 74820912-2a1b-4d36-8700-7d8b66cf10eb · outbound
This paper cites Fully convolutional networks for semantic segmentation.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Fully convolutional networks for semantic segmentation
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.575305Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 20cad2e3-fe70-4551-8870-f03b39bbeddd · outbound
This paper cites an unresolved cited work.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Unresolved cited work
Reference 28
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 06133aae-2787-4c79-ae08-c079709fe462 · outbound
This paper cites Integer-valued training and spike-driven inference spiking neural network for high-performance and energy-efficient object detection.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Integer-valued training and spike-driven inference spiking neural network for high-performance and energy-efficient object detection
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 838a486a-5541-4475-9212-1141e10d73cd · outbound
This paper cites Networks of spiking neurons: the third generation of neural network models.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Networks of spiking neurons: the third generation of neural network models
Reference 30
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 41061b98-10d7-4833-b041-0b3991ea4438 · outbound
This paper cites Vspw: A large-scale dataset for video scene parsing in the wild.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Vspw: A large-scale dataset for video scene parsing in the wild
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.525769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 187a621f-3897-44e3-8f59-941fa25f207d · outbound
This paper cites and Torralba, A.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity and Torralba, A
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.513946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9d54f35b-9ea7-45e4-bbe8-5f1457e50752 · outbound
This paper cites Local memory attention for fast video semantic segmentation.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Local memory attention for fast video semantic segmentation
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.501409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f8522a1c-15fc-49b1-a89a-d344ff8ea3be · outbound
This paper cites The human imagination: the cognitive neuroscience of visual mental imagery.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity The human imagination: the cognitive neuroscience of visual mental imagery
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.488521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0a282a3c-9678-483e-baa7-95231a38cee8 · outbound
This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Mobilenetv2: Inverted residuals and linear bottlenecks
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.477133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 162b6393-e064-4e2d-b251-96cd7f4e058d · outbound
This paper cites Global-to-local modeling for video-based 3d human pose and shape estimation.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Global-to-local modeling for video-based 3d human pose and shape estimation
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.464748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 55a43198-9412-4383-8940-ddeabd8e3645 · outbound
This paper cites F., Klink, P.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity F., Klink, P
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.451513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation dbf70b97-21cf-40ac-a8dd-6be0738ad6c6 · outbound
This paper cites Deep directly-trained spiking neural networks for object detection.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Deep directly-trained spiking neural networks for object detection
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.438878Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2f971d2b-eaef-4297-bb70-d8f87dbe8520 · outbound
This paper cites Multi-scale full spike pattern for semantic segmentation.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Multi-scale full spike pattern for semantic segmentation
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.426942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 64e3cbdc-6016-42d5-97d6-a89f8bb45e49 · outbound
This paper cites and Egner, T.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity and Egner, T
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.414995Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f0b094eb-83aa-4cde-a28c-ac5a42dc9d6f · outbound
This paper cites Learning local and global temporal contexts for video semantic segmentation.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Learning local and global temporal contexts for video semantic segmentation
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.404760Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 94c2bdb8-9db0-4bdf-9bd5-e213f1101ad0 · outbound
This paper cites N., Kaiser, ., and Polosukhin, I.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity N., Kaiser, ., and Polosukhin, I
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:17:27.030670Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe030a3e-e50d-4c9a-ae23-71b46bac636f · outbound
This paper cites How brains beware: neural mechanisms of emotional attention.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity How brains beware: neural mechanisms of emotional attention
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.386911Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9c68b35e-9792-4974-a145-7f305240081f · outbound
This paper cites Pssd-transformer: Powerful sparse spike-driven transformer for image semantic segmentation.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Pssd-transformer: Powerful sparse spike-driven transformer for image semantic segmentation
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.375982Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c3cbe386-2d13-4d4f-b20c-9768018548a4 · outbound
This paper cites and Torresani, L.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity and Torresani, L
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.363475Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 29b8f19e-e182-4bc9-bdea-736371307d23 · outbound
This paper cites Non-local neural networks.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Non-local neural networks
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.350468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 383c398f-3d7d-4c74-8076-165ecd7a9727 · outbound
This paper cites End-to-end video instance segmentation with transformers.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity End-to-end video instance segmentation with transformers
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.339535Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 758fb100-b5d8-4d05-a28d-9109b96ed8e1 · outbound
This paper cites ResNet strikes back: An improved training procedure in timm.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity ResNet strikes back: An improved training procedure in timm
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:17:27.054676Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe8bb124-97e3-4cb3-aec8-3db78da1bc95 · outbound
This paper cites M., and Luo, P.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity M., and Luo, P
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.327743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c37f1d76-78b2-440c-8ff9-a03ed0f40e33 · outbound
This paper cites Reevaluating the sensory account of visual working memory storage.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Reevaluating the sensory account of visual working memory storage
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.316408Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 4d3d2400-b77a-4dd8-9a36-96b940d6e560 · outbound
This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:17:27.064954Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b651f8b-c702-4e1a-92d2-cfed9833bb21 · outbound
This paper cites Attention spiking neural networks.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Attention spiking neural networks
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.304635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2d563082-034f-45b2-b4bc-15ea6030ed0d · outbound
This paper cites Spike-driven transformer v2: Meta spiking neural network architecture inspiring the design of next-generation neuromorphic chips.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Spike-driven transformer v2: Meta spiking neural network architecture inspiring the design of next-generation neuromorphic chips
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.293309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c4870a7d-ee5a-44da-baf1-8580b9e204f2 · outbound
This paper cites Spike-driven transformer.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Spike-driven transformer
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.282465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d0d47d38-18fa-4994-bab0-28685ed352a4 · outbound
This paper cites an unresolved cited work.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T21:17:27.271608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d4751aec-d781-4880-bf02-fe2317cf292a · outbound
This paper cites Binary embedding: Fundamental limits and fast algorithm.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Binary embedding: Fundamental limits and fast algorithm
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.261140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9908cf2c-7474-41d6-9c6d-b42804a675db · outbound
This paper cites Metaformer is actually what you need for vision.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Metaformer is actually what you need for vision
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.249138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 42df5ac8-4da4-4a52-ad87-6362860ea216 · outbound
This paper cites Pyramid scene parsing network.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Pyramid scene parsing network
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.237813Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 33ad277f-4b50-42f3-9a83-a98808b3b26a · outbound
This paper cites Direct training high-performance deep spiking neural networks: a review of theories and methods.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Direct training high-performance deep spiking neural networks: a review of theories and methods
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.226249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2e3da7cd-7ccb-42b3-87bc-320162befce1 · outbound
This paper cites Spikformer: When spiking neural network meets transformer.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Spikformer: When spiking neural network meets transformer
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.214805Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0fb2d9c5-dd8b-49c1-83bf-9228993f07eb · outbound
This paper cites Eventhpe: Event-based 3d human pose and shape estimation.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity Eventhpe: Event-based 3d human pose and shape estimation
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:17:27.203079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 49327cc9-5601-4a7f-b452-dd8bef911dc6 · outbound
This paper cites write newline.
SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity write newline
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:17:27.106516Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.