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Paper Citation Record · LEDGER

Graph Neural Networks for the Graphical Bootstrap

As of 8 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2607.03109.

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

pith.paper-citation-record.v1
2607.03109 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T04:50:25.686477Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

21 of 21 outbound references displayed

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External citation measurements

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Outbound references

Observation a8924110-9d2f-4bf0-9d77-c957e86bec63 · outbound

This paper cites What can we learn about QCD and collider physics from N=4 super Yang-Mills?.

Graph Neural Networks for the Graphical Bootstrap What can we learn about QCD and collider physics from N=4 super Yang-Mills?

Reference 1

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Observation ffc6315c-bc30-4136-8b21-b6232e02a603 · outbound

This paper cites Three-Loop Four-Point Correlator in N=4 SYM.

Graph Neural Networks for the Graphical Bootstrap Three-Loop Four-Point Correlator in N=4 SYM

Reference 2

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Observation e897d41d-41ab-434e-bdd8-a1b575641639 · outbound

This paper cites Hidden symmetry of four-point correlation functions and amplitudes in N=4 SYM.

Graph Neural Networks for the Graphical Bootstrap Hidden symmetry of four-point correlation functions and amplitudes in N=4 SYM

Reference 3

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source=pdf_text observed=2026-07-12T04:50:25.686477Z digest=sha256:05a5067464069b52f9ea38bc1f2800169a7ba50c113114825aca389f40dd374d

Observation e85cffb1-62da-415f-8367-95284ad70b06 · outbound

This paper cites Constructing the correlation function of four stress-tensor multiplets and the four-particle amplitude in N=4 SYM.

Graph Neural Networks for the Graphical Bootstrap Constructing the correlation function of four stress-tensor multiplets and the four-particle amplitude in N=4 SYM

Reference 4

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source=pdf_text observed=2026-07-12T04:50:25.686477Z digest=sha256:aa290bb51a5d63947c64c14fa550f7e56212da5b3993024319b87c582eb98237

Observation 2283a98f-e127-488e-b5ac-b38d2f588993 · outbound

This paper cites Perturbation Theory at Eight Loops: Novel Structures and the Breakdown of Manifest Conformality.

Graph Neural Networks for the Graphical Bootstrap Perturbation Theory at Eight Loops: Novel Structures and the Breakdown of Manifest Conformality

Reference 5

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source=pdf_text observed=2026-07-12T04:50:25.686477Z digest=sha256:0e2330df81f50f9272c04a1ea6ff6210d3de34f7ec30889a26326d91b6988bac

Observation 364ec3d3-a46d-4f45-a06c-b15eb8075b1f · outbound

This paper cites Amplitudes and Correlators to Ten Loops Using Simple, Graphical Bootstraps.

Graph Neural Networks for the Graphical Bootstrap Amplitudes and Correlators to Ten Loops Using Simple, Graphical Bootstraps

Reference 6

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source=pdf_text observed=2026-07-12T04:50:25.686477Z digest=sha256:13cfc9e537e76f4b7b410ab8cc003a009c45947028a5fb26514ead3596c40d45

Observation 3711b822-7ee9-4c2e-8c9b-c3d720637cc7 · outbound

This paper cites The Cusp Limit of Correlators and A New Graphical Bootstrap for Correlators/Amplitudes to Eleven Loops.

Graph Neural Networks for the Graphical Bootstrap The Cusp Limit of Correlators and A New Graphical Bootstrap for Correlators/Amplitudes to Eleven Loops

Reference 7

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Observation 7e8f9b52-0aa1-4f0f-95ce-48aad2c27450 · outbound

This paper cites The Four-Point Correlator of Planar sYM at Twelve Loops.

Graph Neural Networks for the Graphical Bootstrap The Four-Point Correlator of Planar sYM at Twelve Loops

Reference 8

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source=pdf_text observed=2026-07-12T04:50:25.686477Z digest=sha256:c84f39eba7e333a0339b2bbc93d5f6cc25fa9c5ce23a6738ab1959d441f1f72b

Observation b35a59d4-6c95-459c-9d15-b83ed3a28041 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks for the Graphical Bootstrap Unresolved cited work

Reference 9

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Observation 9886c4d8-acf7-40ce-ac3c-7b2d23a999be · outbound

This paper cites Alnuqaydan, S.

Graph Neural Networks for the Graphical Bootstrap Alnuqaydan, S

Reference 10

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Observation 5183bf97-75f1-4e98-983a-c839702cabd2 · outbound

This paper cites Simplifying Polylogarithms with Machine Learning.

Graph Neural Networks for the Graphical Bootstrap Simplifying Polylogarithms with Machine Learning

Reference 11

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Observation 4c49e56a-c3b0-4638-8cfc-9380e614ef74 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks for the Graphical Bootstrap Unresolved cited work

Reference 12

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Observation fa128f55-a6fb-4752-a68d-e1332861db13 · outbound

This paper cites Veliˇckovi´c, G.

Graph Neural Networks for the Graphical Bootstrap Veliˇckovi´c, G

Reference 13

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Observation fe190ce2-5af1-44ff-851f-bf7ef9b224e9 · outbound

This paper cites Do Transformers Really Perform Bad for Graph Representation?.

Graph Neural Networks for the Graphical Bootstrap Do Transformers Really Perform Bad for Graph Representation?

Reference 14

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Observation 9aca4afc-a22f-4566-a412-45a352e358a2 · outbound

This paper cites Duong, T.D.

Graph Neural Networks for the Graphical Bootstrap Duong, T.D

Reference 15

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Observation 6a1209c8-2bd7-42f1-9df4-d12c77332519 · outbound

This paper cites Dwivedi, A.T.

Graph Neural Networks for the Graphical Bootstrap Dwivedi, A.T

Reference 16

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Observation 65be319e-19e4-485e-8b74-f950cdef36a3 · outbound

This paper cites Graphlet and Orbit Computation on Heterogeneous Graphs.

Graph Neural Networks for the Graphical Bootstrap Graphlet and Orbit Computation on Heterogeneous Graphs

Reference 17

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Observation a3d1a87d-dbb3-4718-a702-87b1c21dcb5e · outbound

This paper cites an unresolved cited work.

Graph Neural Networks for the Graphical Bootstrap Unresolved cited work

Reference 18

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Observation 8a3e8a56-0614-4dc6-84b9-b2630b4eaeea · outbound

This paper cites Vaswani, N.

Graph Neural Networks for the Graphical Bootstrap Vaswani, N

Reference 19

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Observation 35c03069-0e5f-4995-9349-0083cc346717 · outbound

This paper cites McGraw and S.P.

Graph Neural Networks for the Graphical Bootstrap McGraw and S.P

Reference 20

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Observation bafdb60e-8ea7-4dc0-81da-f2f34a0d2b2c · outbound

This paper cites Alain and Y.

Graph Neural Networks for the Graphical Bootstrap Alain and Y

Reference 21

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Pith citing papers

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