Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2309.07452.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:56:34.349468Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-09T18:10:53.446663Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
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 ec449c1e-5896-44fc-b543-d93850e9f415 · inbound
Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond cites this paper.
Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
Reference 100
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:09:35.212872Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e242e4b9-764d-4f2a-a8ce-dcf71b406024 · inbound
Numerical Pruning for Efficient Autoregressive Models cites this paper.
Numerical Pruning for Efficient Autoregressive Models Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
Reference 118
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:11:27.231151Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ca7e995-6bcc-41d7-9fa6-49af139c4881 · inbound
LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers cites this paper.
LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
Reference 109
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:11:39.832086Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 352a31af-7092-41ea-acf0-61db3848f2b3 · inbound
High-Order Matching for One-Step Shortcut Diffusion Models cites this paper.
High-Order Matching for One-Step Shortcut Diffusion Models Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
Reference 50
- Resolution
- verified exact
- local_arxiv, observed 2026-08-09T18:10:53.451584Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 08739ac9-3674-4050-b177-646cda5a140d · inbound
Fast RoPE Attention: Combining the Polynomial Method and Fast Fourier Transform cites this paper.
Fast RoPE Attention: Combining the Polynomial Method and Fast Fourier Transform Is Solving Graph Neural Tangent Kernel Equivalent to Training Graph Neural Network?
Reference 139
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:56:34.349468Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.