Paper Citation Record · LEDGER

Rethinking Graph Neural Networks for the Graph Coloring Problem

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2208.06975.

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

pith.paper-citation-record.v1
2208.06975 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:44:32.278132Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T14:41:02.267856Z

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 c5c6c696-5e25-4d19-a742-e74954b40dfb · inbound

Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization cites this paper.

Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization Rethinking Graph Neural Networks for the Graph Coloring Problem

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T16:44:32.278132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e5e1952-dc39-4305-8f06-26feb4aab6f9 · inbound

Concept Learning in the Wild: Towards Algorithmic Understanding of Neural Networks cites this paper.

Concept Learning in the Wild: Towards Algorithmic Understanding of Neural Networks Rethinking Graph Neural Networks for the Graph Coloring Problem

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T15:17:23.208712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b0a6e2b-e4cb-453f-9986-a8021fb5b3ee · inbound

Efficient Optimization Accelerator Framework for Multistate Ising Problems cites this paper.

Efficient Optimization Accelerator Framework for Multistate Ising Problems Rethinking Graph Neural Networks for the Graph Coloring Problem

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:52.960637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10b3156d-4d31-4d5b-b1f5-73b0ffd032bc · inbound

A Low-Complexity Framework for Multi-access Coded Caching Systems with Arbitrary User-cache Access Topology cites this paper.

A Low-Complexity Framework for Multi-access Coded Caching Systems with Arbitrary User-cache Access Topology Rethinking Graph Neural Networks for the Graph Coloring Problem

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-16T14:41:02.270539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.