Paper Citation Record · LEDGER

On the Relationship between Self-Attention and Convolutional Layers

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:1911.03584.

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

pith.paper-citation-record.v1
1911.03584 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:22:07.558331Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:59:20.814270Z

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Outbound references

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Pith citing papers

Observation d67f4de8-724e-42a0-8e75-9b6d073ea9b3 · inbound

DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory cites this paper.

DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory On the Relationship between Self-Attention and Convolutional Layers

Reference 163

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:03:58.158726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fab1d02a-02c6-431d-9552-5e2028a0b9d9 · inbound

Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing cites this paper.

Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing On the Relationship between Self-Attention and Convolutional Layers

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T17:35:41.962175Z

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Observation 592a97b4-2480-415d-8b9f-dd6fc0479eb1 · inbound

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey cites this paper.

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey On the Relationship between Self-Attention and Convolutional Layers

Reference 269

Resolution: unresolved; no resolver link, observed 2026-08-11T23:54:24.518120Z

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Observation cd299dc8-cab2-468d-8a2e-89aa8c45ba44 · inbound

Mixture-of-Experts Graph Transformers for Interpretable Particle Collision Detection cites this paper.

Mixture-of-Experts Graph Transformers for Interpretable Particle Collision Detection On the Relationship between Self-Attention and Convolutional Layers

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:24.769981Z

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Observation 811296c6-1c3d-4342-ba73-9e94becd0119 · inbound

Unified CNNs and transformers underlying learning mechanism reveals multi-head attention modus vivendi cites this paper.

Unified CNNs and transformers underlying learning mechanism reveals multi-head attention modus vivendi On the Relationship between Self-Attention and Convolutional Layers

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T16:44:16.486176Z

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Observation 46c93432-43c5-4786-839b-f71829323d37 · inbound

Exploring Visual Embedding Spaces Induced by Vision Transformers for Online Auto Parts Marketplaces cites this paper.

Exploring Visual Embedding Spaces Induced by Vision Transformers for Online Auto Parts Marketplaces On the Relationship between Self-Attention and Convolutional Layers

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T18:08:52.398133Z

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Observation aeefb886-3e16-46c8-8d22-34be6485a512 · inbound

Enhancing Video Understanding: Deep Neural Networks for Spatiotemporal Analysis cites this paper.

Enhancing Video Understanding: Deep Neural Networks for Spatiotemporal Analysis On the Relationship between Self-Attention and Convolutional Layers

Reference 27

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Observation ac0b69bd-302a-4dc0-a399-65df8c2bfe8f · inbound

IAFormer: Interaction-Aware Transformer network for collider data analysis cites this paper.

IAFormer: Interaction-Aware Transformer network for collider data analysis On the Relationship between Self-Attention and Convolutional Layers

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-22T17:14:59.586309Z

Source-reported events for the cited work

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Observation f943b646-7e8e-4fde-b804-fb0ce29da256 · inbound

Learning to Adapt to Position Bias in Vision Transformer Classifiers cites this paper.

Learning to Adapt to Position Bias in Vision Transformer Classifiers On the Relationship between Self-Attention and Convolutional Layers

Reference 7

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Observation 5b688fe9-a490-49ed-aad3-934d54b4aec1 · inbound

Computer Vision Models Show Human-Like Sensitivity to Geometric and Topological Concepts cites this paper.

Computer Vision Models Show Human-Like Sensitivity to Geometric and Topological Concepts On the Relationship between Self-Attention and Convolutional Layers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T20:21:48.824422Z

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Observation b859d881-c1fe-4521-a9c6-b078f1ef9c00 · inbound

Numerical Investigation of Sequence Modeling Theory using Controllable Memory Functions cites this paper.

Numerical Investigation of Sequence Modeling Theory using Controllable Memory Functions On the Relationship between Self-Attention and Convolutional Layers

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T10:22:22.158470Z

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Observation 4caa92a1-c886-42a6-8d9c-3b9712fd28f2 · inbound

Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution cites this paper.

Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution On the Relationship between Self-Attention and Convolutional Layers

Reference 32

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Observation 0fc6cdd0-6d73-4d66-a852-b0e85994817c · inbound

Low-latency vision transformers via large-scale multi-head attention cites this paper.

Low-latency vision transformers via large-scale multi-head attention On the Relationship between Self-Attention and Convolutional Layers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T21:39:34.141455Z

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Observation 9bbb0a99-a740-43d8-af83-abfb3903a314 · inbound

Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs cites this paper.

Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs On the Relationship between Self-Attention and Convolutional Layers

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T20:04:02.100755Z

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Observation 174c8a16-08bb-4748-8f16-b7f336d65cc6 · inbound

Compute Can't Handle the Truth: Why Communication Tax Prioritizes Memory and Interconnects in Modern AI Infrastructure cites this paper.

Compute Can't Handle the Truth: Why Communication Tax Prioritizes Memory and Interconnects in Modern AI Infrastructure On the Relationship between Self-Attention and Convolutional Layers

Reference 158

Resolution: unresolved; no resolver link, observed 2026-08-06T18:50:52.687932Z

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Observation aa62f6cd-dfd3-4a4e-b945-c5c66a7a4227 · inbound

GASPnet: Global Agreement to Synchronize Phases cites this paper.

GASPnet: Global Agreement to Synchronize Phases On the Relationship between Self-Attention and Convolutional Layers

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T15:09:38.488716Z

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Observation 5da29c5b-2105-47a9-a746-a793bf5ceb38 · inbound

What do language models model? Transformers, automata, and the format of thought cites this paper.

What do language models model? Transformers, automata, and the format of thought On the Relationship between Self-Attention and Convolutional Layers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T16:59:26.035340Z

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Observation e8243dd2-0513-4aee-9aa9-0748b6bfb7d6 · inbound

Long-Term Visual Localization in Dynamic Benthic Environments: A Dataset, Footprint-Based Ground Truth, and Visual Place Recognition Benchmark cites this paper.

Long-Term Visual Localization in Dynamic Benthic Environments: A Dataset, Footprint-Based Ground Truth, and Visual Place Recognition Benchmark On the Relationship between Self-Attention and Convolutional Layers

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-02T19:02:06.386909Z

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Observation 2f9ae193-2c21-4193-bc49-f806ac75c956 · inbound

From Sparsity to Simplicity: Enabling Simpler Sequential Replacements via Sparse Attention Distillation cites this paper.

From Sparsity to Simplicity: Enabling Simpler Sequential Replacements via Sparse Attention Distillation On the Relationship between Self-Attention and Convolutional Layers

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:58:58.876272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9602f92c-4912-4366-bcaf-45b692826d28 · inbound

Weierstrass Positional Encoding for Vision Transformers cites this paper.

Weierstrass Positional Encoding for Vision Transformers On the Relationship between Self-Attention and Convolutional Layers

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:50:23.757240Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 16d9f984-092d-4ae0-b59a-fc8340e41136 · inbound

SWARD: Stochastic Window-Attention-Based Relational Distillation for Cross-Architectural Semantic Segmentation cites this paper.

SWARD: Stochastic Window-Attention-Based Relational Distillation for Cross-Architectural Semantic Segmentation On the Relationship between Self-Attention and Convolutional Layers

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:56:13.946586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d83ee67-493e-4677-95ac-9c2df982570d · inbound

RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways cites this paper.

RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways On the Relationship between Self-Attention and Convolutional Layers

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:37:36.441026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f496aaba-5f4c-4d52-a914-586a87109bc6 · inbound

RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways cites this paper.

RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways On the Relationship between Self-Attention and Convolutional Layers

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-02T11:55:28.866330Z

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Observation 420f9e7a-65d2-4324-a212-c901b3bcf3da · inbound

ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence cites this paper.

ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence On the Relationship between Self-Attention and Convolutional Layers

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:59:20.817064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2f79c0d3-8a15-4535-8401-004e2262af6f · inbound

ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence cites this paper.

ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence On the Relationship between Self-Attention and Convolutional Layers

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-30T11:54:38.647194Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d19433b2-e8b4-4f27-96c0-7d74be643f2a · inbound

RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention cites this paper.

RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention On the Relationship between Self-Attention and Convolutional Layers

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T15:34:10.184742Z

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Observation acb488cc-b72b-45b9-afab-2118d0c9d4f6 · inbound

NAE: Normalizing AutoEncoder cites this paper.

NAE: Normalizing AutoEncoder On the Relationship between Self-Attention and Convolutional Layers

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-16T00:22:07.558331Z

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