Paper Citation Record · LEDGER

GraphSAINT: Graph Sampling Based Inductive Learning Method

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:1907.04931.

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

pith.paper-citation-record.v1
1907.04931 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 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 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:25:28.211581Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:08:56.229471Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a478809b-03ba-49a1-8d9f-19c2600f185b · inbound

How Attentive are Graph Attention Networks? cites this paper.

How Attentive are Graph Attention Networks? GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-17T02:33:38.773994Z

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.

Observation 5c97689c-2403-40b9-89eb-48f2dfbd9c8d · inbound

DESIGN: Encrypted GNN Inference via Server-Side Input Graph Pruning cites this paper.

DESIGN: Encrypted GNN Inference via Server-Side Input Graph Pruning GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:25:28.211581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc23273a-296e-496f-9c60-4ae78a3547cb · inbound

Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation cites this paper.

Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T18:59:23.667922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ff07029-4c61-436c-8654-aa401294cd59 · inbound

HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data cites this paper.

HGCN(O): A Self-Tuning GCN HyperModel Toolkit for Outcome Prediction in Event-Sequence Data GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T11:41:58.510672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Neighbor-Sampling Based Momentum Stochastic Methods for Training Graph Neural Networks cites this paper.

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

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T10:19:03.413357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f506cd3-8dc7-40bc-b9ca-9d99e7f43798 · inbound

From free-evolution to tomographic representation cites this paper.

From free-evolution to tomographic representation GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T21:34:39.985472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f72a4ea-75b4-4adc-8462-7aaa72690231 · inbound

RapidGNN: Energy and Communication-Efficient Distributed Training on Large-Scale Graph Neural Networks cites this paper.

RapidGNN: Energy and Communication-Efficient Distributed Training on Large-Scale Graph Neural Networks GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T05:33:03.256264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46badaef-09db-4a61-94da-b106b506d120 · inbound

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks cites this paper.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T23:12:24.226668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ec21f5e-ac26-4c97-bf56-99c2f73670cd · inbound

Attention Enhanced Entity Recommendation for Intelligent Monitoring in Cloud Systems cites this paper.

Attention Enhanced Entity Recommendation for Intelligent Monitoring in Cloud Systems GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T08:28:05.715817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad07ed6f-db8f-45dc-8c79-58fc0afbf992 · inbound

FuseSampleAgg: One-Pass Neighborhood Estimation for Budgeted Knowledge-Graph Refresh and Validation cites this paper.

FuseSampleAgg: One-Pass Neighborhood Estimation for Budgeted Knowledge-Graph Refresh and Validation GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T21:50:37.746200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38cccb8c-10eb-4714-90f6-c26b47d1ae49 · inbound

Wrong Code, Right Structure: Learning Netlist Representations from Imperfect LLM-Generated RTL cites this paper.

Wrong Code, Right Structure: Learning Netlist Representations from Imperfect LLM-Generated RTL GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T01:22:44.715677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ca95ce-efdc-41d9-93b9-2b57dd091a6f · inbound

Communication-free Sampling and 4D Hybrid Parallelism for Scalable Mini-batch GNN Training cites this paper.

Communication-free Sampling and 4D Hybrid Parallelism for Scalable Mini-batch GNN Training GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:43:15.364748Z

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.

Observation 72be9bc9-c677-46bc-8883-42c258da46e8 · inbound

TypeBandit: Type-Level Context Allocation and Reweighting for Effective Attribute Completion in Heterogeneous Graph Neural Networks cites this paper.

TypeBandit: Type-Level Context Allocation and Reweighting for Effective Attribute Completion in Heterogeneous Graph Neural Networks GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:01:29.274391Z

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.

Observation cc56265b-1ca7-4d60-b3f8-cf594015c8b4 · inbound

Trapping Attacker in Dilemma: Examining Internal Correlations and External Influences of Trigger for Defending GNN Backdoors cites this paper.

Trapping Attacker in Dilemma: Examining Internal Correlations and External Influences of Trigger for Defending GNN Backdoors GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:36:25.536237Z

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.

Observation 2cd35de1-4aa2-4162-a5d4-fcdad14671c8 · inbound

Trapping Attacker in Dilemma: Examining Internal Correlations and External Influences of Trigger for Defending GNN Backdoors cites this paper.

Trapping Attacker in Dilemma: Examining Internal Correlations and External Influences of Trigger for Defending GNN Backdoors GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:35:09.367593Z

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.

Observation ee27b772-070d-4ee5-997f-f5c1c8e21dcf · inbound

Universal Graph Backdoor Defense: A Feature-based Homophily Perspective cites this paper.

Universal Graph Backdoor Defense: A Feature-based Homophily Perspective GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-19T21:12:47.023277Z

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.

Observation f25c9512-a40e-4297-b1f7-7a1cdb866a41 · inbound

Universal Graph Backdoor Defense: A Feature-based Homophily Perspective cites this paper.

Universal Graph Backdoor Defense: A Feature-based Homophily Perspective GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-30T19:45:00.922718Z

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.

Observation 90f4d609-f592-4039-be58-c963a1564299 · inbound

Learning over Positive and Negative Edges with Contrastive Message Passing cites this paper.

Learning over Positive and Negative Edges with Contrastive Message Passing GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:33:16.874578Z

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.

Observation a65f15f1-a212-42c9-b87f-1def9aa8ba10 · inbound

EUPHORIA: Efficient Universal Planning via Hybrid Optimization for Robust Industrial Robotic Assembly cites this paper.

EUPHORIA: Efficient Universal Planning via Hybrid Optimization for Robust Industrial Robotic Assembly GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:03:43.374641Z

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.

Observation d1967980-de1c-425f-ba4e-6093bf6fb9ba · inbound

Incorporating Deep Learning Design in Database Queries cites this paper.

Incorporating Deep Learning Design in Database Queries GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:24:45.232962Z

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.

Observation bd92cf33-cb8f-4611-b1bd-73b279a51e5f · inbound

Graph Cascades: Contagion-Based Mesoscopic Rewiring for Structure-Aware Graph Machine Learning cites this paper.

Graph Cascades: Contagion-Based Mesoscopic Rewiring for Structure-Aware Graph Machine Learning GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 176

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T06:06:41.472963Z

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.

Observation 5b954183-7135-4ef3-8b1b-323a9d6c7ac4 · inbound

From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction cites this paper.

From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-03T01:17:30.932262Z

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.

Observation e62ee49f-fe5b-40e8-b19f-e30c9a3be7d5 · inbound

Handling Feature Heterogeneity with Learnable Graph Patches cites this paper.

Handling Feature Heterogeneity with Learnable Graph Patches GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:08:56.231515Z

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.

Observation 86407185-c58a-433d-a023-7516b0ac4bb5 · inbound

CoRe-GNN: Multilevel Message passing on Coarsened graphs cites this paper.

CoRe-GNN: Multilevel Message passing on Coarsened graphs GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T14:42:49.212802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.