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Paper Citation Record · LEDGER

Chaining 2-FWL GNNs for Combinatorial Graph Alignment

As of 13 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2510.03086.

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

pith.paper-citation-record.v1
2510.03086 v2

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:39:00.860795Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

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External citation measurements

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Outbound references

Observation ac317cbb-3589-4527-b744-0aba6d89b983 · outbound

This paper cites SciPy is a set of open source (BSD licensed) scientific and numerical tools for Python.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment SciPy is a set of open source (BSD licensed) scientific and numerical tools for Python

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 80f3d2c6-5e99-44d6-ac2a-360af25f32de · outbound

This paper cites doi: https://doi.org/10.1016/0166-218X(91)90049-3.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment doi: https://doi.org/10.1016/0166-218X(91)90049-3

Reference 10

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Observation eaafbaa5-0aa5-49e9-9e0f-a78507ed1ee2 · outbound

This paper cites These instances are small (from 12 to 40 nodes) with full (integer- valued) matrices.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment These instances are small (from 12 to 40 nodes) with full (integer- valued) matrices

Reference 15

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Observation ed26dd6a-75ac-48d3-8bf0-29357bc6e575 · outbound

This paper cites These algorithms achieve partial recovery (positive accuracy) whenp noise is suffi- ciently small, though well below the information-theoretic threshold of1−d −1.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment These algorithms achieve partial recovery (positive accuracy) whenp noise is suffi- ciently small, though well below the information-theoretic threshold of1−d −1

Reference 16

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Observation c7fdc1c2-4441-4378-97b4-ba1b3470940b · outbound

This paper cites an unresolved cited work.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Unresolved cited work

Reference 17

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Observation 22f95a57-88ef-470c-b81e-f829fdc94330 · outbound

This paper cites The red curve labeled FAQ corresponds toFAQ(Dcx) and the blue curve labeled message passing are results from (Muratori & Semerjian, 2024).

Chaining 2-FWL GNNs for Combinatorial Graph Alignment The red curve labeled FAQ corresponds toFAQ(Dcx) and the blue curve labeled message passing are results from (Muratori & Semerjian, 2024)

Reference 18

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Observation 28ea8c44-e01e-4115-b94b-391fe28cf94a · outbound

This paper cites 24 Table 10: Number of common edges (nce) defined in (4) for dense Erd˝os-R´enyi graphs as a function of the noisep noise.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment 24 Table 10: Number of common edges (nce) defined in (4) for dense Erd˝os-R´enyi graphs as a function of the noisep noise

Reference 100

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Observation 68482400-8c15-4c74-a2af-d91ee30d5ed6 · outbound

This paper cites an unresolved cited work.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Unresolved cited work

Reference 500

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Observation fa4b7c39-503c-45eb-8f71-93a2b0e9178b · outbound

This paper cites URLhttps: //onlinelibrary.wiley.com/doi/abs/10.1002/nav.3800020109.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment URLhttps: //onlinelibrary.wiley.com/doi/abs/10.1002/nav.3800020109

Reference 1955

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Observation 4a00fc09-f556-4761-9d7f-522a6847764b · outbound

This paper cites Aligning random graphs with a sub-tree similarity message-passing algorithm.Journal of Statistical Mechanics: Theory and Experiment, 2022(6):063401,.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Aligning random graphs with a sub-tree similarity message-passing algorithm.Journal of Statistical Mechanics: Theory and Experiment, 2022(6):063401,

Reference 1991

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Observation 24ae998a-a03a-4c7f-a40e-74f4adb803aa · outbound

This paper cites doi: 10.1007/978-1-4613-0303-9.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment doi: 10.1007/978-1-4613-0303-9

Reference 1998

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Observation 00517d32-77a4-47c2-a74b-a5f578c324f8 · outbound

This paper cites 14 A.2 Technical details for the GNN architecture and training.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment 14 A.2 Technical details for the GNN architecture and training

Reference 2008

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Observation 1632bd53-618e-42e0-9e83-1310a26574be · outbound

This paper cites Faster algorithms for the alignment of sparse correlated Erd\"os-R\'enyi random graphs.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Faster algorithms for the alignment of sparse correlated Erd\"os-R\'enyi random graphs

Reference 2011

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Observation 7daecaa6-7a04-4e38-a4b1-afd826ad631c · outbound

This paper cites Impossibility of partial recovery in the graph alignment problem.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Impossibility of partial recovery in the graph alignment problem

Reference 2013

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Observation ec7e74d2-2e2b-4580-85cb-055eaf260547 · outbound

This paper cites an unresolved cited work.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Unresolved cited work

Reference 2015

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Observation ae3ffaa4-4c3a-49df-b260-64635d6bcf55 · outbound

This paper cites doi: 10.1145/2964791.2901460.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment doi: 10.1145/2964791.2901460

Reference 2016

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Observation aa516567-6f52-421c-98ca-9beb734d966f · outbound

This paper cites The first stage is the same as our first step but with a MPNN instead of our FGNN.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment The first stage is the same as our first step but with a MPNN instead of our FGNN

Reference 2020

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Observation 9bfb747f-f2f3-43ff-825c-a901b6d607da · outbound

This paper cites Deep graph matching via blackbox differentiation of combinatorial solvers.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Deep graph matching via blackbox differentiation of combinatorial solvers

Reference 2022

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Observation 769b6a9d-3f63-415a-805a-8466c4ee97a6 · outbound

This paper cites A polynomial-time iterative algorithm for random graph matching with non-vanishing correlation.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment A polynomial-time iterative algorithm for random graph matching with non-vanishing correlation

Reference 2023

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Observation d299227f-6166-4775-b4d0-7324cc73c121 · outbound

This paper cites Robust de-anonymization of large sparse datasets.

Chaining 2-FWL GNNs for Combinatorial Graph Alignment Robust de-anonymization of large sparse datasets

Reference 2024

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Pith citing papers

No inbound Pith citation observations are available.