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Paper Citation Record · LEDGER

From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.03260.

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

pith.paper-citation-record.v1
2311.03260 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T00:46:43.045052Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:19:57.659001Z

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 df6ef2ec-3b39-472e-b453-38c2ca8d41a9 · inbound

Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics cites this paper.

Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:34:02.958448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-21T07:30:07.287938Z digest=sha256:026519ba17483780cbfee45641ab3f9b761cfb8e758f678c228df2ae33f5f030

Observation bc5aeeb6-d881-4812-be1f-d86f4e9b8f3f · inbound

Swarm-Inspired Generation of Collective Behaviors in Graph Dynamical Systems cites this paper.

Swarm-Inspired Generation of Collective Behaviors in Graph Dynamical Systems From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:19:57.660286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-26T00:46:43.045052Z digest=sha256:3a6e325e1ce05a6c246a4ebd7627b981b6aa5199bb411e3ea0b3bf6f3100ddba