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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-08T06:32:00.761636+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

62 of 62 outbound references displayed

  • verified exact4
  • verified fuzzy40
  • unresolved17
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

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:bf7b333529a2cb0f781f1f07104f5c8b8a8b9f79a7e5a10a0f3ea7fa205c34a8

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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source=arxiv_source observed=2026-08-06T10:19:01.657466Z digest=sha256:4808ae18a9cace7ccd36580cd6843426709ee492a7ab058f07f2d98069f3ad41

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=sha256:41d0584c186bafaab173d384f407d70224a14d6ac9ef570ed5a1c8aa110b7ccf

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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source=arxiv_source observed=2026-08-06T10:19:02.085500Z digest=sha256:37a6c0017e94ebbf8e36923db6cb069456f3717b69c2d53a8eb8630f9eb42cea

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=sha256:15bd034dd0775d213e4724052b964ce3bc0d5e1480eb17ca960996a5a383017f

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=sha256:92ba9a31394d949016eeb8b975413720b5ff29a56fdfa2410ffc86e8246195c6

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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source=arxiv_source observed=2026-08-06T10:19:02.646829Z digest=sha256:93571527f89e99e56d184b4ccd7b9e0f1dee715ab424a53a20244d53ec1c80cb

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=sha256:9c3c1734272ac80473b882fc24c0f2cb2d07f82701ae9436964c43c35cc22f20

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:a4c96f1d97caa67bfe5fdcb2471f44d3218a12eb6ca22e4e17558914c539a7a7

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=sha256:40c250f4e433203576e81d26ad697db3fddf3b8c3f96b3d7d3300acde82ac363

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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source=arxiv_source observed=2026-08-06T10:19:03.186426Z digest=sha256:912ecf08274c3a20c91e80c782b26c4007be35110d3570af7e466a2b66efb0c3

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=sha256:369956c186229c799a354cc446b0720d3e68a9bdef0a168d33b7b0f6d145574a

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=sha256:457a770afa064ce7063481821b5c622a38ef8a9cd1befd82b3b31eb09e88d7c6

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:03.579803Z digest=sha256:5d2a90463fbe0d020340ab970ecf776f88830f8d380b14f53b8795b0a231d406

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:f32a23f44f86166cd7886062381d17089c72cc14e377971a41a81f2789b67c64

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=sha256:3cbfdd542a85c6010435ff1bd2991385a37848bd37667296528961099568d949

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:f77388bec3fadd64ca864761dce0cdc681b19cef416757239dc0ba77b97b1a81

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=sha256:78179ea01cd132b8b7f694c45d8e7752232e2baf56e49a304cdd95a3fda45f79

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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source=arxiv_source observed=2026-08-06T10:19:05.054145Z digest=sha256:8fb5ea8c1606d04c66996b9fe7f10d70cfcd6f2fe2267436764eebaa2623874a

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:d24645117851e8c4f16608d8932f75322da82a554d8e3ffaff9fe4f4ecae0017

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:aaeb500d40c1667c9d6957fb18b2ca8071121f9cc2b9a6bf8b92a2c6400dbe0e

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:cec054ead90153ca961e06e5bca777cea2a4da8169a1c2fcd8dfa52b52b3dbbb

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:fb2763744650487ac7a19f623627b8cfdfe82e910688cf8fa91d22eddce89cb5

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=sha256:8b2f668da2fc4e9285ffcf8d5f081b9b33bd65f6f736c6a496674408469da92a

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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source=arxiv_source observed=2026-08-06T10:19:05.977147Z digest=sha256:829c169cde22be9d6b2aec88148f9820a7543fc6f31cd25de0185940f0ff2878

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:d46ec7add5c353cf3bd2810102419b3d44d30381ba4b4e5cecf717b2c8075554

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=sha256:44f54e5545b665c957c26631c63aedf05d1cbd18384fbcf809058cbb60a6ffb4

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:a5411663562d741e58786e0fd0a31d3a4c39d0d52d3bf02402ded693e202c76d

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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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.533122Z digest=sha256:c33d480ed6d4d729fed866241ef9ce56ed2e71e9522c4e6a7a7665ea2b24e488

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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verified exact
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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.672858Z digest=sha256:5bdaf58018e0a4fe0106a168b15bc4dff813b8a80e83a2845518c2fbd8c5ef9c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.798233Z digest=sha256:cf0319514bc08039061f878192c86fbfcf602df858bcc3f32de4deea1faae260

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.894270Z digest=sha256:7646489d0ae3542be1132621e0209d165e2d23affc813df28dfea1dd7d6ae84b

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:06.996256Z digest=sha256:c9e164050da27cc07ac855cf5b79eee5461e43d533c0eeffdf577a18f587523f

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.090435Z digest=sha256:50c96710303fb30363754d2eb7a876753d7e4e36bef85d964771c189b98c8978

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.201832Z digest=sha256:a78f5bac9004ba498be2b83a6b11e83776a37e7f5d0c8fdd40117e197c28f263

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.354078Z digest=sha256:aa991e4d2dd90b6427f8594f7143a735ab33b424db3692d649b73f4110bf6eb7

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.491084Z digest=sha256:706e5e0ea8d5046dbc0dea4e60c6e9b5485aedab7124e269e46b846410ae7a2a

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.625585Z digest=sha256:af649a68d7399c0ed07764fef0efc49d1427fecdfbd542b85f02f2244cf8d67a

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.746062Z digest=sha256:56973e94232a9ff3e001b3ba060b3d0fe9b6ef46c4d9ab00d22fb36103359973

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:07.854033Z digest=sha256:2d9551e020e97d1e99c52616e61459857ac646b67fa2c11e3c373be4ad9fbcd8

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.017962Z digest=sha256:d10b83a557d506db298292e6510f2a99c3a8d0ebdd9ce07be8f05b7d0b59ea94

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.221759Z digest=sha256:ca27dd8c715078ae1c81d0faf3ca8abd8700d27516074a3b4709875c355330fd

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.387857Z digest=sha256:5718768204b80b4823b25edf6ad46a295eb433ccfa466809b89143dcff25a516

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.592394Z digest=sha256:70d82f549f5de25cdf344b6ef17d6215069c9fc0f2d6259d7f5e86b91f12a2d8

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:08.679844Z digest=sha256:b1204874622b0f2fd17a3ff870d46fb6ad02133b33fdf391e84016d3d38185eb

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=sha256:9b440e5b32c022f2f5bf170ca56aa3a6f3295555d36a59d5b5891ab20e232b53

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.020753Z digest=sha256:339434a2f85db448df528edcea1f51202c750cf0c2d64719b58225f8312a788e

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.187227Z digest=sha256:49b600bf86f8507b1b9746d6a2606c7670df434025b77901a47c74ef1ba6ff3c

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=sha256:106dd7169524858b19ead01d6aac47867bd2cc77c4418528773eec25a8eb1bcd

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.430549Z digest=sha256:b42855c49b35826c58fbe386c5beecc537b2bc982c31b74e9d53d9cf810878fa

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.613186Z digest=sha256:be7f4710af6b2cd040b57578f78f79090977c8980edcffeb513c94b19cca2ca3

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-06T10:19:09.763685Z digest=sha256:1d9c2b2dc90109f25fb64853b60603ba188795ae8393b32b6d6bf1ed69dcc585

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=sha256:3f312063e73d7f16356aa51f4f7fef35e981ba729d2b77f03d16ec558e3d8608

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:a32dff730a4092aff45ca4e2e36215d981423021ddf336463d3d7ada8824b7ae

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=sha256:207adae836625fe8a41721ceee5346d5cbccb9bcc7b87ba1b5d313eed40e9a06

Pith citing papers

No inbound Pith citation observations are available.