Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:22:22.158470Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T00:59:20.814270Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation d67f4de8-724e-42a0-8e75-9b6d073ea9b3 · inbound
DragNUWA: Fine-grained Control in Video Generation by Integrating Text, Image, and Trajectory On the Relationship between Self-Attention and Convolutional Layers
Reference 163
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.
Observation ac0b69bd-302a-4dc0-a399-65df8c2bfe8f · inbound
IAFormer: Interaction-Aware Transformer network for collider data analysis On the Relationship between Self-Attention and Convolutional Layers
Reference 71
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.
Observation b859d881-c1fe-4521-a9c6-b078f1ef9c00 · inbound
Numerical Investigation of Sequence Modeling Theory using Controllable Memory Functions On the Relationship between Self-Attention and Convolutional Layers
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4caa92a1-c886-42a6-8d9c-3b9712fd28f2 · inbound
Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution On the Relationship between Self-Attention and Convolutional Layers
Reference 32
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0fc6cdd0-6d73-4d66-a852-b0e85994817c · inbound
Low-latency vision transformers via large-scale multi-head attention On the Relationship between Self-Attention and Convolutional Layers
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9bbb0a99-a740-43d8-af83-abfb3903a314 · inbound
Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs On the Relationship between Self-Attention and Convolutional Layers
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 174c8a16-08bb-4748-8f16-b7f336d65cc6 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aa62f6cd-dfd3-4a4e-b945-c5c66a7a4227 · inbound
GASPnet: Global Agreement to Synchronize Phases On the Relationship between Self-Attention and Convolutional Layers
Reference 2019
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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 On the Relationship between Self-Attention and Convolutional Layers
Reference 53
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f9ae193-2c21-4193-bc49-f806ac75c956 · inbound
From Sparsity to Simplicity: Enabling Simpler Sequential Replacements via Sparse Attention Distillation On the Relationship between Self-Attention and Convolutional Layers
Reference 3
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.
Observation 9602f92c-4912-4366-bcaf-45b692826d28 · inbound
Weierstrass Positional Encoding for Vision Transformers On the Relationship between Self-Attention and Convolutional Layers
Reference 12
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.
Observation 16d9f984-092d-4ae0-b59a-fc8340e41136 · inbound
SWARD: Stochastic Window-Attention-Based Relational Distillation for Cross-Architectural Semantic Segmentation On the Relationship between Self-Attention and Convolutional Layers
Reference 6
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.
Observation 8d83ee67-493e-4677-95ac-9c2df982570d · inbound
RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways On the Relationship between Self-Attention and Convolutional Layers
Reference 6
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.
Observation f496aaba-5f4c-4d52-a914-586a87109bc6 · inbound
RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways On the Relationship between Self-Attention and Convolutional Layers
Reference 2019
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 420f9e7a-65d2-4324-a212-c901b3bcf3da · inbound
ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence On the Relationship between Self-Attention and Convolutional Layers
Reference 18
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.
Observation 2f79c0d3-8a15-4535-8401-004e2262af6f · inbound
ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence On the Relationship between Self-Attention and Convolutional Layers
Reference 18
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.