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Paper Citation Record · LEDGER

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation

As of 8 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2506.22292.

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

pith.paper-citation-record.v1
2506.22292 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:15:47.004269Z

measured 27 of 27 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 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

27 of 27 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6fc385a0-aef6-4d15-a86a-b8a368bc4b50 · outbound

This paper cites Community detection and stochastic block models: recent developments.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Community detection and stochastic block models: recent developments

Reference 1

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Observation f42a1284-7b2b-4a74-a805-a0806c42c495 · outbound

This paper cites On sample eigenvalues in a generalized spiked population model.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation On sample eigenvalues in a generalized spiked population model

Reference 2

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This paper cites Emergence of scaling in random networks.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Emergence of scaling in random networks

Reference 3

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Observation 77397cab-c89b-4f65-bd81-dcbee2c269e0 · outbound

This paper cites Further results on generalized inverses of tensors via the einstein product.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Further results on generalized inverses of tensors via the einstein product

Reference 4

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Observation 187416dd-c582-49f2-b41d-d3d430bddc8a · outbound

This paper cites A tensor network low rank completion method.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation A tensor network low rank completion method

Reference 5

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Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Unresolved cited work

Reference 6

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Observation a966df42-5adb-469b-9bee-773ddbd9d679 · outbound

This paper cites Solving multilinear systems via tensor inversion.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Solving multilinear systems via tensor inversion

Reference 7

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Observation b4d1539a-bada-4b54-b60a-5585e0d79b4c · outbound

This paper cites Random matrix methods for machine learning.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Random matrix methods for machine learning

Reference 8

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This paper cites Decompositions of a higher-order tensor in block terms—part ii: Definitions and uniqueness.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Decompositions of a higher-order tensor in block terms—part ii: Definitions and uniqueness

Reference 9

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Observation e56e962e-84af-4c34-a844-47b63100c0eb · outbound

This paper cites A Fair Comparison of Graph Neural Networks for Graph Classification.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation A Fair Comparison of Graph Neural Networks for Graph Classification

Reference 10

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This paper cites Big graphs: challenges and opportunities.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Big graphs: challenges and opportunities

Reference 11

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This paper cites Optimal shrinkage of singular values.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Optimal shrinkage of singular values

Reference 12

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This paper cites Snap datasets: Stanford large network dataset collection.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Snap datasets: Stanford large network dataset collection

Reference 13

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This paper cites Stochastic blockmodels and community structure in networks.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Stochastic blockmodels and community structure in networks

Reference 14

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This paper cites Tensor decompositions and applications.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Tensor decompositions and applications

Reference 15

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This paper cites A guide to conquer the biological network era using graph theory.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation A guide to conquer the biological network era using graph theory

Reference 16

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Observation 384a7f6e-2eb3-4270-8208-624cb4e5700b · outbound

This paper cites Fundamental Tensor Operations for Large-Scale Data Analysis in Tensor Train Formats.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Fundamental Tensor Operations for Large-Scale Data Analysis in Tensor Train Formats

Reference 17

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Observation 5a569b03-558b-4c61-b33d-01cea93fb0c0 · outbound

This paper cites Kronecker graphs: an approach to modeling networks.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Kronecker graphs: an approach to modeling networks

Reference 18

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This paper cites Statistical properties of community structure in large social and information networks, in: Proceedings of the 17th international conference on World Wide Web, pp.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Statistical properties of community structure in large social and information networks, in: Proceedings of the 17th international conference on World Wide Web, pp

Reference 19

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Observation 3c3c5b34-e450-4a15-80bb-5e8186563b0a · outbound

This paper cites Analysis and Approximate Inference of Large Random Kronecker Graphs.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Analysis and Approximate Inference of Large Random Kronecker Graphs

Reference 20

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This paper cites Information network or social network? the structure of the twitter follow graph, in: Proceedings of the 23rd international conference on world wide web, pp.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Information network or social network? the structure of the twitter follow graph, in: Proceedings of the 23rd international conference on world wide web, pp

Reference 21

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Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation The structure and function of complex networks

Reference 22

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Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Randomgraphmodelsofsocialnetworks

Reference 23

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Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Using graph theory to analyze biological networks

Reference 24

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Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Topology of the world trade web

Reference 25

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Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Unresolved cited work

Reference 26

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This paper cites Collective dynamics of ‘small-world’networks.

Scalable inference of large-scale random kronecker graphs via tensor decomposition and Einstein summation Collective dynamics of ‘small-world’networks

Reference 27

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Source-reported events for the cited work

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