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Paper Citation Record · LEDGER

On the Relationship between Self-Attention and Convolutional Layers

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 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 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:22:22.158470Z

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

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 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

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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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-20T13:03:57.828598Z digest=sha256:23730b8badf90be2ea91b19367aad997d1b1fdefa82f9e476207b464a81ec150

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T17:13:47.293753Z digest=sha256:7199f24b19f989878d0c8167d5908211a92e07a1d794003a1035626cde365ca7

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:22:22.158470Z digest=sha256:e830a8b9b3062f3be61133ceff479b83a9dce4fcefa0a5f872ccfc34aa116c99

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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unresolved
no resolver link, observed 2026-08-06T23:41:00.620976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:41:00.620976Z digest=sha256:4c8cfef5444a259ec4065c49bbb02778250486e8203f3b05a00359efd98cc329

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:39:34.141455Z digest=sha256:34d52704be6968046207a3710338bd5e7f6abf56f4f872d1cb413d5ffba74b35

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:04:02.100755Z digest=sha256:70210759fb4361071377670b0112f36896eeece025c14573b1c166f722f86786

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:50:52.687932Z digest=sha256:4165fb7b785023bf9b78b5ccdaad3726d749463e08da51baf19dfcdacf699fff

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:09:38.488716Z digest=sha256:66ae451cb621199a50320997819bca42e8c4212b49b9262eefaebcfd7c438a21

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:02:06.386909Z digest=sha256:e840ae572b63aa825aa0fa26eca961a356dd3d393784e519874a490ddfc4de00

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T19:57:16.552439Z digest=sha256:a1b9902b900fc70f7ae3f09922b79d2b628bc36f85e96566a85d840451ac98eb

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T05:48:36.533090Z digest=sha256:a87c082708860d030a655405993a3cfff707537a79ef49d5eb3dc84d2ad9c675

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T17:37:46.185060Z digest=sha256:83152bd40a388f9721202b3b1516cae12df29302c7a9195ba217f286540370f0

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T13:50:51.534798Z digest=sha256:a297e7773b1879714830e33115c64cf38ce9c61cb1100afed831e0e7fe2e0905

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:55:28.866330Z digest=sha256:c0eb714779e8ca34240595be4613c8c5265f2ed5d80ffe85def6d12049621fc1

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T20:47:03.932909Z digest=sha256:23ae7d6f8c8aeb5fc853c5ad607939b2872732ff7368de46f3dfe648c7a2b9cc

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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