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Paper Citation Record · LEDGER

On the Computational Capability of Graph Neural Networks: A Circuit Complexity Bound Perspective

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.06444.

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

pith.paper-citation-record.v1
2501.06444 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:21:01.419305Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T19:53:23.447374Z

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 5f066297-9c76-4c6e-bd0a-aa47e1b5ac99 · inbound

How Hard Is It for Message-Passing GNNs to Simulate One Weisfeiler-Lehman Color-Refinement Step? cites this paper.

How Hard Is It for Message-Passing GNNs to Simulate One Weisfeiler-Lehman Color-Refinement Step? On the Computational Capability of Graph Neural Networks: A Circuit Complexity Bound Perspective

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-23T19:53:23.450589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T19:48:39.681300Z digest=sha256:1093147435c643bebe53e37cef91ae0f50545da8b36d0294ff5c096818e28c38

Observation 15190e46-7116-43bb-bada-dbb6eb711a62 · inbound

Minimalist Softmax Attention Provably Learns Constrained Boolean Functions cites this paper.

Minimalist Softmax Attention Provably Learns Constrained Boolean Functions On the Computational Capability of Graph Neural Networks: A Circuit Complexity Bound Perspective

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:21:01.419305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:21:01.419305Z digest=sha256:72fa5d246d02fca0abf9899fffb398bc197b28cba2606e0c07cd6a822634e4a1