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Paper Citation Record · LEDGER

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks

As of 7 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2508.00267.

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

pith.paper-citation-record.v1
2508.00267 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:19:10.316909Z

measured 62 of 62 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.

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

62 of 62 outbound references displayed

  • verified exact4
  • verified fuzzy40
  • unresolved17
  • parse uncertain0
  • malformed identifier1
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External citation measurements

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Outbound references

Observation 4bcfd90b-ad9a-49ec-acc5-e6b90e39bab1 · outbound

This paper cites Stochastic Training of Graph Convolutional Networks with Variance Reduction.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Stochastic Training of Graph Convolutional Networks with Variance Reduction

Reference 1

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source=arxiv_source observed=2026-08-06T10:19:01.590669Z digest=sha256:b94b457a0e6b2917e3c1d629913235a0e121060eeca9410a16c967c45b01f104

Observation 252fdf2d-16d4-4f4a-ad7e-7f6114faa610 · outbound

This paper cites , Wang , Y.-C.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , Y.-C

Reference 2

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Observation a4b43d47-21cd-4b82-abda-d306cf278f6c · outbound

This paper cites , Ma , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ma , Y

Reference 3

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Observation db929f32-b919-4e7b-b188-0d2c8315b38b · outbound

This paper cites , Lee , Y.-C.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Lee , Y.-C

Reference 4

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source=arxiv_source observed=2026-08-06T10:19:01.971086Z digest=sha256:aca7ccd1435c34ec8ba35cedb70aca529d8942c251c1518245af241752be204d

Observation 236604e3-76ec-4238-879e-028f94f6a132 · outbound

This paper cites , Sanchez-Gonzalez , A.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Sanchez-Gonzalez , A

Reference 5

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Observation 340ae92b-32ac-46de-8acf-6e13a297f358 · outbound

This paper cites , Schoenholz , S.S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Schoenholz , S.S

Reference 6

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Observation 7cb3e6c4-bc4a-448d-b65e-60d2eb8bd557 · outbound

This paper cites , Zeng , J.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zeng , J

Reference 7

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source=arxiv_source observed=2026-08-06T10:19:02.390431Z digest=sha256:a516aa0673e7340f292367b1499991ac362040b8071ab39d37f2e3094ecaf345

Observation 3da2d566-a3b0-4c39-85e9-e2ecb200370c · outbound

This paper cites , Monfardini , G.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Monfardini , G

Reference 8

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source=arxiv_source observed=2026-08-06T10:19:02.517761Z digest=sha256:1dbf6f51e141252bbf7047c43a96f3d31cfd67842fdb7c7b006b4ba9485fd881

Observation c6c7c669-e381-49e5-a369-27c2e9df17c1 · outbound

This paper cites , Gori , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Gori , M

Reference 9

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Observation d51cf396-2b42-4188-911e-91bf68c9b168 · outbound

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

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Semi-Supervised Classification with Graph Convolutional Networks

Reference 10

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source=arxiv_source observed=2026-08-06T10:19:02.769657Z digest=sha256:bbec37c7ea7a5ef74479ab7cf3879d726247803dff350e43b2d5b5ecfcb8bfc0

Observation 31b9ad19-c345-4493-afc9-8bb460624566 · outbound

This paper cites DeeperGCN: All You Need to Train Deeper GCNs.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks DeeperGCN: All You Need to Train Deeper GCNs

Reference 11

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source=arxiv_source observed=2026-08-06T10:19:02.881461Z digest=sha256:57863c2fa27f73ce6a54e87346e8c7aebd463e14ea6a91444f59f6dadb84ca80

Observation ad500c2c-cbad-4cf3-8e1f-72e2905ecbf9 · outbound

This paper cites , Yang , J.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Yang , J

Reference 12

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source=arxiv_source observed=2026-08-06T10:19:03.069375Z digest=sha256:e1d611900fe98900a20c89d7030a5198253cc52f65e38e399a23a6661f8d1bcd

Observation efa9c0c7-b421-4bc2-948e-dd27c3c0d23d · outbound

This paper cites , Ying , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ying , Z

Reference 13

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Observation d610a253-a09c-44a7-aa42-0935ee6c2518 · outbound

This paper cites FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

Reference 14

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source=arxiv_source observed=2026-08-06T10:19:03.283361Z digest=sha256:43618d164b22999526270ca2f03b7897b1353b09fa0b7739be07ae1790dbc783

Observation 59510a0f-e7e3-48c3-95d5-a20c00bdc9e3 · outbound

This paper cites GraphSAINT: Graph Sampling Based Inductive Learning Method.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 15

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source=arxiv_source observed=2026-08-06T10:19:03.413357Z digest=sha256:0c64b0bcf90057410b5a19eda51fdc28a00139bd717caf3ce5da34be5755b24c

Observation e0e0513c-c0c1-4364-91d4-ea772dec987e · outbound

This paper cites , M \"u ller , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , M \"u ller , M

Reference 16

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:03.579803Z digest=sha256:40b7f0a9f9ffa843f9cef9c7f2745ddbdb6f7174635dd4e7ec44651b89af37d6

Observation f6bb27f3-68a0-4c73-97f8-14b7cf804abf · outbound

This paper cites , Monro , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Monro , S

Reference 17

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source=arxiv_source observed=2026-08-06T10:19:03.708419Z digest=sha256:17b3637eecacac840a919ec29e884aa4d4fcf981a28710af3bda3132267e3f93

Observation 841d0c9c-37a4-4562-ad81-cda072a29d2a · outbound

This paper cites : Introductory lectures on convex optimization - a basic course.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks : Introductory lectures on convex optimization - a basic course

Reference 18

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source=arxiv_source observed=2026-08-06T10:19:03.873509Z digest=sha256:aaf9174462f33b3b4f2c3cb436305ed0cc5329041e6daee3581bfdfc87bef484

Observation 20a37e67-0495-41b1-9900-b3df9f58aab4 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Adam: A Method for Stochastic Optimization

Reference 19

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Observation 489df2bc-1e1d-4f7e-848e-a6dbfa95e050 · outbound

This paper cites , Xu , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Xu , Y

Reference 20

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Observation a947c109-700c-46cc-a4e3-462c49abd0a2 · outbound

This paper cites : Some methods of speeding up the convergence of iteration methods.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks : Some methods of speeding up the convergence of iteration methods

Reference 21

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Observation ba49fd55-b695-4bb5-acc0-057b5baba4bf · outbound

This paper cites On the Convergence of Adam and Beyond.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks On the Convergence of Adam and Beyond

Reference 22

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Observation e48acaeb-6fd9-4fc8-83e7-6ecec0fb9a02 · outbound

This paper cites , Hazan , E.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Hazan , E

Reference 23

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source=arxiv_source observed=2026-08-06T10:19:04.575581Z digest=sha256:48593e4754c69ebee95d6c577ce4359d9ea9fcbb8f768f92de9a493ef3b5660e

Observation 4cde7304-9e3f-4584-befc-dfa5ff692a0b · outbound

This paper cites On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization

Reference 24

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source=arxiv_source observed=2026-08-06T10:19:04.740760Z digest=sha256:2736ac49b14cb0b118775d4c8034f1ac88415a68b058d8ce95f3c52df7eedec8

Observation eeb6df83-598a-49f4-afe3-a1b022ba2b7b · outbound

This paper cites Gated Graph Sequence Neural Networks.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Gated Graph Sequence Neural Networks

Reference 25

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Observation 5c439ebf-b98c-47fc-a37b-59a00b3f550b · outbound

This paper cites , Micheli , A.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Micheli , A

Reference 26

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Observation abf12a0b-c2ba-4bc6-ba84-4b1d53cabf8e · outbound

This paper cites , Kozareva , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Kozareva , Z

Reference 27

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source=arxiv_source observed=2026-08-06T10:19:05.210684Z digest=sha256:d979a7d574a75da604d007618b7ffc55628ba4caea8102e4907d007ce9771166

Observation c58e829b-37fa-4aef-beb7-6001979b3d52 · outbound

This paper cites , Pan , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Pan , S

Reference 28

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source=arxiv_source observed=2026-08-06T10:19:05.391697Z digest=sha256:11e5efe41cf25e8f3bb3784f3fc8938f5a6170be4fa37fb0aa7361d5914b0e0c

Observation 05e82857-b165-4119-8b59-6245ba46e15e · outbound

This paper cites Spectral Networks and Locally Connected Networks on Graphs.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Spectral Networks and Locally Connected Networks on Graphs

Reference 29

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source=arxiv_source observed=2026-08-06T10:19:05.537427Z digest=sha256:ca440067815b11d0926479b8ff922fb8a58b8ae35eaae545f5c8ac35c2bc2b3c

Observation 6e299552-f47b-4359-8eaa-f1c8a5c28457 · outbound

This paper cites Deep Convolutional Networks on Graph-Structured Data.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Deep Convolutional Networks on Graph-Structured Data

Reference 30

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source=arxiv_source observed=2026-08-06T10:19:05.710102Z digest=sha256:2ec3d73fc796228f305b613adf10c5d45f908b6a421e6d391c5b7958a79141ea

Observation d89a65a8-53ed-45ba-8128-8f8cb76e35c3 · outbound

This paper cites , Bresson , X.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Bresson , X

Reference 31

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source=arxiv_source observed=2026-08-06T10:19:05.844054Z digest=sha256:23dd25675023d24d8250560ceeb3956e3ab6a191357b0c56620fdaf212e177ad

Observation 518591de-8ec4-47f3-9f5c-86a92b6f9661 · outbound

This paper cites , Monti , F.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Monti , F

Reference 32

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Observation bbe0a83a-81f9-4185-bcbf-0b875e2ec0ef · outbound

This paper cites , Wang , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , S

Reference 33

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source=arxiv_source observed=2026-08-06T10:19:06.113429Z digest=sha256:1c320dcdd0b7db5a3f3f439e8e61ee465f7c1b976eb17079173ee3ce23c80474

Observation 461ac51f-3a28-4916-b49c-f7ce14e73e56 · outbound

This paper cites , Ma , Q.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ma , Q

Reference 34

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source=arxiv_source observed=2026-08-06T10:19:06.265469Z digest=sha256:5911e59eb36385738f2846dd26603183697109f280c5bc2202c7e4944d6ff555

Observation ebb7f712-12ad-45de-adb4-fd45063bb209 · outbound

This paper cites , Wang , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , Z

Reference 35

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source=arxiv_source observed=2026-08-06T10:19:06.395396Z digest=sha256:89b7163bb543e1dda7656de3929e03daf6b63d5a15440a6cbd7be99cdb7b37ce

Observation 6fa451fb-671e-4ba8-be68-53fd4dcedd91 · outbound

This paper cites , Hu , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Hu , Z

Reference 36

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source=arxiv_source observed=2026-08-06T10:19:06.533122Z digest=sha256:976d645a4818a20ed0459ab7126bce4471236d32d702db7e1f5ee5dd3cd63e7f

Observation cf7640ac-7fb8-40cd-be49-db8faefa5304 · outbound

This paper cites MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks

Reference 37

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local_arxiv, observed 2026-08-06T10:19:11.484007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.672858Z digest=sha256:9cb4346ddb3d241f80ccb1b12df39ada091a919eafdac52cc6ea8b626f964a23

Observation d1d0d86a-0ef3-40f2-8417-1d0ee0693f47 · outbound

This paper cites , Zhang , T.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zhang , T

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:16.645420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.798233Z digest=sha256:ef863b3888e8e12527a1437c33b1398362bd56cf28cfb636c18854a36f0ab2bd

Observation a4df1047-bcfc-4408-8717-daadb4745aac · outbound

This paper cites , Liu , X.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Liu , X

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:16.346219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.894270Z digest=sha256:50cd970fcf4f0ed918d6b5adc52247363780434cac51ab892052fc719fb07c1c

Observation 1e4509c3-e62e-41d2-ae4c-31ef655a7a3e · outbound

This paper cites PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:19:11.232422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.996256Z digest=sha256:ad372056b1bda66d69eea99a16f3d68a36f9a998ad02df4850c786936b37fcb3

Observation 67512972-91e1-4a67-913c-87434b44ce29 · outbound

This paper cites , Yang , X.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Yang , X

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:16.056402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.090435Z digest=sha256:2d1304063f6e8d29bda3ca6871ea524254dc4e152415a4c497df88ba8f7524bd

Observation 0b46f53e-f604-4ed0-98cd-9f24ae0f792e · outbound

This paper cites , Wang , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Wang , Y

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:15.764133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.201832Z digest=sha256:7f8e5b3f34436ef82adfa0c890656b6878bf91dea468316e82d3ed54fce74cb2

Observation fc67b2de-5cdd-4f80-8662-75501ade45cb · outbound

This paper cites Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:19:10.945843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.354078Z digest=sha256:90d995ef967134ae39250c28bc0cbce118545c92273098707740effc0f517ad1

Observation ca11c649-9e81-405a-80c2-e4175671381d · outbound

This paper cites GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:19:10.616111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.491084Z digest=sha256:e5ce17ec1a81b0b9a87f41a3fb57ea97b625aae76dd6112df72b425627423e51

Observation 13148f3f-bdc0-4096-867a-a38e6bd1cb5e · outbound

This paper cites , Liu , G.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Liu , G

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:15.493312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.625585Z digest=sha256:fadc72951c3a6c5dc1acee0c38ef732ae3a6badbb5875c7d93203e73749ccea1

Observation a48b209e-c4bf-4a62-bb3b-7e24fa4b8683 · outbound

This paper cites , Lu , J.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Lu , J

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:15.249183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.746062Z digest=sha256:b690a404106639acc4e004bf1233ec3e8b548ab4045df7746287dcb01bdf59bf

Observation 90898b8b-d007-4c76-b134-2e6b5ef0ec03 · outbound

This paper cites , Ramezani , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Ramezani , M

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.879213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.854033Z digest=sha256:ec8cc52ab6cd0564599ec1d0ec7fda470502c02c5e5b34618fb9793194cb61fe

Observation e0fb7412-1d38-4a21-8d6e-8e1c8d8b4f26 · outbound

This paper cites , Lou , H.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Lou , H

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.579781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.017962Z digest=sha256:74a4e8d7ffa4a4b269352409da2780c906280523cb5aebb288dab971b88152bb

Observation b405db17-5e51-494a-a9ff-ab175dcc2263 · outbound

This paper cites , Feng , T.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Feng , T

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.253430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.221759Z digest=sha256:eb5cf57b9a56b8dd549a148b9c729853bb57b5a99400ca8d8ed3624d91441df8

Observation b71e5307-a8e5-48c4-9c24-31f728119e32 · outbound

This paper cites , Zhang , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zhang , Y

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:14.011437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.387857Z digest=sha256:ec4385c941031559ea5ed893c2f04324f12a188299ecd4fa650c3e976ff0c277

Observation 40e8d92f-dbc3-4b9d-8a5c-2b393e86b439 · outbound

This paper cites , Khalid , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Khalid , M

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:13.725724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.592394Z digest=sha256:12771537557085231b1dbf4bcdfb069b01fb8be42e834af872a24ba1e2c6d014

Observation ffc7a728-ab2a-4a0b-9ca4-283d6bb6c096 · outbound

This paper cites , Zheng , Z.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Zheng , Z

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:13.471330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.679844Z digest=sha256:2d861f3f5aa44d90b060fde36921df1ab8e7640fb6a33f875978ae900a64e8e1

Observation 67f6aa36-8aab-41fc-bc17-6767fa0759bb · outbound

This paper cites On the Convergence of SGD with Biased Gradients.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks On the Convergence of SGD with Biased Gradients

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:08.874670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:08.874670Z digest=sha256:2ea6c3463cb06104a07a0b8b24decaefc76a98a3277b9f72fece3115345bb6ed

Observation d98c7f71-0963-4958-93af-3844bbb969a1 · outbound

This paper cites , Yin , W.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Yin , W

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:13.111712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.020753Z digest=sha256:ee52d64320179ff6c979ba8724538f87bd1960840040ef55b69a7bddf38eddf3

Observation 50dab936-8d95-4c99-9dcf-34ae6c451f7f · outbound

This paper cites , Carmon , Y.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Carmon , Y

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:12.844610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.187227Z digest=sha256:104f92a9e6674051b1ea843ee1b04a0a9e08a8fabc77b7d5fa0ba8819564425a

Observation fe5adee0-5a5e-4015-8467-f5ed6f51eaef · outbound

This paper cites CogDL: A Comprehensive Library for Graph Deep Learning.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks CogDL: A Comprehensive Library for Graph Deep Learning

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:09.330652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:09.330652Z digest=sha256:34fb470a0dd85766e43c8d3ea7f744e3cda7ceb2bc11a45c7d13f1334bb2ff8c

Observation 5bd4fdb6-d753-4e95-b83c-a2e071fbf7e1 · outbound

This paper cites , Gross , S.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Gross , S

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:12.563383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.430549Z digest=sha256:fb20fa90f16ea42d67453887079f9eb16d8c98b6e7435ae6a56e1656bfdf8eed

Observation bda93e3b-10bd-4aab-9694-2ccf27486825 · outbound

This paper cites , Namata , G.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Namata , G

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:12.258512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.613186Z digest=sha256:c3c193fcf070600ceb9728e7d23df582d054b737061a30db272aa773a675c25d

Observation 2deb5a45-893a-4a00-bd25-5d24e7b670c0 · outbound

This paper cites , Fey , M.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks , Fey , M

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T10:19:11.967081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.763685Z digest=sha256:ff27a729cfb7d0d071f84bd95b0c52f87be9dcf5ca3d31d0016c185b594245e4

Observation 09d5c99e-9238-466f-bac0-07485114f5f0 · outbound

This paper cites sn-basic.bst.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks sn-basic.bst

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:09.925497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:09.925497Z digest=sha256:67353b91dd29caf9d0a999433ec5cd1ac13d4d795ad763954fdadb3aefa3d0ad

Observation bfd5ca5b-7f57-4fff-8907-8cf241658dcc · outbound

This paper cites write newline.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks write newline

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T10:19:10.096506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:10.096506Z digest=sha256:0b22e5ffa42075aa9fb1516b39147dd4dd888c0c88c52a3a769ca23e942a742b

Observation accc6c32-a423-4330-b0e3-9e5be827d245 · outbound

This paper cites write newline.

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks write newline

Reference 62

Resolution
malformed identifier
no resolver link, observed 2026-08-06T10:19:10.316909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:19:10.316909Z digest=sha256:8191e966723246bdc816498d6632672300d9e7537bdaf99a68d157cc53fc61ce

Pith citing papers

No inbound Pith citation observations are available.