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Paper Citation Record · LEDGER

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning

As of 9 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2510.03690.

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

pith.paper-citation-record.v1
2510.03690 v4

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:13:08.473230Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

18 of 18 outbound references displayed

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  • verified fuzzy0
  • unresolved17
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  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 76769229-9837-4da3-bf17-c67e039fc55a · outbound

This paper cites Output:Augmented set eD={(G (m) λ ,y (m) λ )}M m=1 of sizeM=⌈rT⌉.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Output:Augmented set eD={(G (m) λ ,y (m) λ )}M m=1 of sizeM=⌈rT⌉

Reference 1

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Observation 10d029f1-60c5-49c7-85a6-45764ecfb8e6 · outbound

This paper cites E EXPERIMENTAL DETAILS.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning E EXPERIMENTAL DETAILS

Reference 2

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Observation 1a99107f-9cce-4ba0-9303-7213a2b06e83 · outbound

This paper cites DropEdge: Towards Deep Graph Convolutional Networks on Node Classification.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 8

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Observation 884c5b8f-014a-43c4-b8e7-55e773f7b02e · outbound

This paper cites Model-agnostic augmentation for accurate graph classifi- cation.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Model-agnostic augmentation for accurate graph classifi- cation

Reference 11

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Observation 18543701-3b01-48e7-a569-cd241107aac9 · outbound

This paper cites Table 5: Benchmark datasets statistics.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Table 5: Benchmark datasets statistics

Reference 16

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Observation bce6f263-fa4a-4279-a698-271761169a41 · outbound

This paper cites • GraphCL You et al.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning • GraphCL You et al

Reference 17

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Observation 79be5723-017a-4647-9333-e46de02d6579 · outbound

This paper cites D GRAPHON ESTIMATION Here we expalin the details of SIGL.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning D GRAPHON ESTIMATION Here we expalin the details of SIGL

Reference 23

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Observation b328537f-a18f-4f50-aabd-f7b0bb8e00c1 · outbound

This paper cites an unresolved cited work.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Unresolved cited work

Reference 32

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Observation 313e9fcd-46c9-4793-9e28-87e8408c1530 · outbound

This paper cites The best test epoch is selected based on validation performance, and test accuracy is reported over eight runs with the sameseedused in Han et al.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning The best test epoch is selected based on validation performance, and test accuracy is reported over eight runs with the sameseedused in Han et al

Reference 128

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Observation ebf80fe9-c09e-4e7b-a00f-a672a7faf82a · outbound

This paper cites Fully distributed online training of graph neural networks in networked systems.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Fully distributed online training of graph neural networks in networked systems

Reference 2001

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Observation b224e49e-158f-4e17-8f27-a38d82257322 · outbound

This paper cites Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, and Marion Neumann.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, and Marion Neumann

Reference 2011

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Observation 0c1d86df-5697-42ee-a410-0ca15ed151b8 · outbound

This paper cites A Few Moments Please: Scalable Graphon Learning via Moment Matching.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning A Few Moments Please: Scalable Graphon Learning via Moment Matching

Reference 2014

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Observation 3243590a-e289-4278-b246-cf0823e7a8b6 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Semi-Supervised Classification with Graph Convolutional Networks

Reference 2015

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Observation 3ec09e9f-fd61-4c2c-b5fc-893c12afb620 · outbound

This paper cites Mixup for node and graph classification.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Mixup for node and graph classification

Reference 2019

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Observation 630d9d71-6008-42f0-a3b1-8d6b393b91d1 · outbound

This paper cites graph2vec: Learning Distributed Representations of Graphs.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning graph2vec: Learning Distributed Representations of Graphs

Reference 2020

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Observation 9ca14bae-68f9-4060-bd62-6b8b98dbfe5a · outbound

This paper cites ISBN 9781450383127.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning ISBN 9781450383127

Reference 2021

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Observation c1e79a12-7c85-4017-b384-335d13c1cbde · outbound

This paper cites Graphmad: Graph mixup for data augmentation using data- driven convex clustering.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Graphmad: Graph mixup for data augmentation using data- driven convex clustering

Reference 2022

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Observation 7e17d6fc-70dd-4deb-a70c-625e23b73391 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning Representation Learning with Contrastive Predictive Coding

Reference 2025

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Pith citing papers

No inbound Pith citation observations are available.