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Paper Citation Record · LEDGER

Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.08514.

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

pith.paper-citation-record.v1
2401.08514 v1

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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T05:19:56.528337Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:19:50.601321Z

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 341f62af-99a5-42a1-9471-677c25fdc69a · inbound

QuIC: A Training-Free Quantum Graph Embedding from Ideal Analysis to Practical Hardware Evaluation cites this paper.

QuIC: A Training-Free Quantum Graph Embedding from Ideal Analysis to Practical Hardware Evaluation Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:06:02.863362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T04:12:04.740920Z digest=sha256:d9766dbf992191a08bdddc679f4509533d64c382421859556c1babbaa806480b

Observation 45830614-ea1b-4ece-805b-d51efe4e07de · inbound

Algorithmic Foundations of Deep Learning: Complexity-Theoretic Rates and a Characterization of Universal Approximation cites this paper.

Algorithmic Foundations of Deep Learning: Complexity-Theoretic Rates and a Characterization of Universal Approximation Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness

Reference 34

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T13:19:50.603128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T05:19:56.528337Z digest=sha256:58486f4ef23ec36b618ea4a0183256a316da3b184240b44c35a17d6b5c3a81de