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Paper Citation Record · LEDGER

Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2012.03174.

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

pith.paper-citation-record.v1
2012.03174 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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:02:05.398595Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T16:39:10.739550Z

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 2c7ae1e5-c705-4eb7-a63b-792e8b8e1f2c · inbound

Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality cites this paper.

Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T22:02:05.398595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:02:05.398595Z digest=sha256:153f8ea08418c19bf516969c225b6f33b298acb15243f62ba06053136fce2852

Observation 9ac3c8a8-4078-402f-b062-5527ed38fae2 · inbound

Learning Efficient Positional Encodings with Graph Neural Networks cites this paper.

Learning Efficient Positional Encodings with Graph Neural Networks Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-09T16:39:10.745430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-09T16:39:10.656446Z digest=sha256:774d87d4a25224d515cc4d087a177e95f80fedbcd29caffe4cc6a32579a74b66