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Paper Citation Record · LEDGER

Graph Neural Networks on Graph Databases

As of 15 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2411.11375.

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

pith.paper-citation-record.v1
2411.11375 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:38:42.694233Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

55 of 55 outbound references displayed

  • verified exact6
  • verified fuzzy31
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c2f4fd3-5a36-4470-a0b7-ae8c28a2e108 · outbound

This paper cites Fineman, Matteo Frigo, John R.

Graph Neural Networks on Graph Databases Fineman, Matteo Frigo, John R

Reference 1

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Observation dcf7a525-0f62-478f-af5e-051980f60d4c · outbound

This paper cites Hamilton, Zhitao Ying, and Jure Leskovec.

Graph Neural Networks on Graph Databases Hamilton, Zhitao Ying, and Jure Leskovec

Reference 2

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Observation 5e91731e-a180-4bbc-b48a-9f4e3a74f6a0 · outbound

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

Graph Neural Networks on Graph Databases FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

Reference 3

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Observation 997d24c1-d322-45a5-aa2c-630708438f3c · outbound

This paper cites Layer- dependent importance sampling for training deep and large graph convolutional networks.

Graph Neural Networks on Graph Databases Layer- dependent importance sampling for training deep and large graph convolutional networks

Reference 4

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Observation c987b7fb-372e-4b42-869b-d82f70a005c9 · outbound

This paper cites Distdgl: Distributed graph neural network training for billion-scale graphs.

Graph Neural Networks on Graph Databases Distdgl: Distributed graph neural network training for billion-scale graphs

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 54bf8e2a-d90d-4bd5-b89e-81ef27bbd56d · outbound

This paper cites Pytorch distributed: experiences on accelerating data parallel training.

Graph Neural Networks on Graph Databases Pytorch distributed: experiences on accelerating data parallel training

Reference 6

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Unavailable: canonical work link unavailable.

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Observation 8224a6c2-19fa-46db-a9fd-95af08bdf3b3 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Graph Neural Networks on Graph Databases Fast Graph Representation Learning with PyTorch Geometric

Reference 7

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T18:38:42.322788Z digest=sha256:92d46cb25fc4125e369527504e66a67c83bc195cc671ceed4d856679100059ab

Observation 72ead72a-b4ee-4464-a972-604169f5ac29 · outbound

This paper cites Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks.

Graph Neural Networks on Graph Databases Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks

Reference 8

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source=pdf_text observed=2026-08-12T18:38:42.325451Z digest=sha256:87d2c52a9540ea3e10db33d6b205059f131b8933f0ca493bbac134d391f7e24d

Observation 7ce009ce-00ca-4946-bcf8-82de9ec7fe09 · outbound

This paper cites TF-GNN: Graph Neural Networks in TensorFlow.

Graph Neural Networks on Graph Databases TF-GNN: Graph Neural Networks in TensorFlow

Reference 9

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T18:38:42.331966Z digest=sha256:00b388a0f4fed62a3e0125b7b5deebebdd2ab333131ef20625e9bb3f59d70d8a

Observation a2e87686-728f-4106-90c3-b5dab39408c7 · outbound

This paper cites A fast and high quality multilevel scheme for parti- tioning irregular graphs.

Graph Neural Networks on Graph Databases A fast and high quality multilevel scheme for parti- tioning irregular graphs

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 6deeb626-e1aa-469c-be75-e9f67ab7091c · outbound

This paper cites METIS: A Software Package for Partitioning Unstructured Graphs, Partitioning Meshes, and Computing Fill-Reducing Orderings of Sparse Matrices , September 1998.

Graph Neural Networks on Graph Databases METIS: A Software Package for Partitioning Unstructured Graphs, Partitioning Meshes, and Computing Fill-Reducing Orderings of Sparse Matrices , September 1998

Reference 11

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4bed9239-a0d0-4ad6-ae8d-87d7111b7a6d · outbound

This paper cites Communication-Free Distributed GNN Training with Vertex Cut.

Graph Neural Networks on Graph Databases Communication-Free Distributed GNN Training with Vertex Cut

Reference 12

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local_arxiv, observed 2026-08-12T18:38:43.223829Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 1850d665-1ac0-4a0a-8b9c-9aa520c6d4bb · outbound

This paper cites Scalable and efficient full-graph gnn training for large graphs.

Graph Neural Networks on Graph Databases Scalable and efficient full-graph gnn training for large graphs

Reference 13

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation aeed18b6-ceeb-4720-9230-afd3d4576be3 · outbound

This paper cites Bytegnn: efficient graph neural network training at large scale.

Graph Neural Networks on Graph Databases Bytegnn: efficient graph neural network training at large scale

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 4f72a670-62e6-44bf-9b82-14024daf0c53 · outbound

This paper cites Foundations of Modern Query Languages for Graph Databases.

Graph Neural Networks on Graph Databases Foundations of Modern Query Languages for Graph Databases

Reference 15

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Source-reported events for the cited work

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Observation d5102af1-a9d4-4f07-aa43-e3797f9dc8a4 · outbound

This paper cites https://www.w3.org/RDF/, 2014.

Graph Neural Networks on Graph Databases https://www.w3.org/RDF/, 2014

Reference 16

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation dab1ddd9-82b0-48a3-8e9d-7896c01dcc99 · outbound

This paper cites Automating the construction of internet portals with machine learning.

Graph Neural Networks on Graph Databases Automating the construction of internet portals with machine learning

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 45f9ab14-52d1-4b83-a06e-e1eb929fdd9b · outbound

This paper cites Open graph benchmark: Datasets for machine learning on graphs.

Graph Neural Networks on Graph Databases Open graph benchmark: Datasets for machine learning on graphs

Reference 18

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d94295a1-3e6d-4c71-a41d-ab4e77a389ea · outbound

This paper cites Cypher: An evolving query language for property graphs.

Graph Neural Networks on Graph Databases Cypher: An evolving query language for property graphs

Reference 19

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Source-reported events for the cited work

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Observation b4f8c4af-c2e1-4065-8b28-50b622920231 · outbound

This paper cites Formal Semantics of the Language Cypher.

Graph Neural Networks on Graph Databases Formal Semantics of the Language Cypher

Reference 20

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local_arxiv, observed 2026-08-12T18:38:43.077139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b28ab08c-4115-4354-8c32-b72899243d8c · outbound

This paper cites opencypher: New directions in property graph querying.

Graph Neural Networks on Graph Databases opencypher: New directions in property graph querying

Reference 21

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doi, observed 2026-08-12T18:38:42.723450Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 70dd9351-043f-4566-8df2-67f2b77d3ec1 · outbound

This paper cites https://www.iso.org/standard/76120.html, 2024.

Graph Neural Networks on Graph Databases https://www.iso.org/standard/76120.html, 2024

Reference 22

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 35202af8-9761-4577-86c7-d52898645315 · outbound

This paper cites Graph Pattern Matching in GQL and SQL/PGQ.

Graph Neural Networks on Graph Databases Graph Pattern Matching in GQL and SQL/PGQ

Reference 23

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local_arxiv, observed 2026-08-12T18:38:43.042129Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7be4963a-8f42-4948-b29d-bf26291e1fad · outbound

This paper cites https://neo4j.com/.

Graph Neural Networks on Graph Databases https://neo4j.com/

Reference 24

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 9da72c44-bef3-4835-be4d-1afe9a3385f6 · outbound

This paper cites https://arangodb.com/.

Graph Neural Networks on Graph Databases https://arangodb.com/

Reference 25

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 3456bfa7-4821-46f3-a892-f40a208bcdfb · outbound

This paper cites https://www.tigergraph.com/.

Graph Neural Networks on Graph Databases https://www.tigergraph.com/

Reference 26

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 240f33bd-4bee-49a3-b86a-4d2f80b80706 · outbound

This paper cites https://www.w3.org/TR/sparql11-query/, 2013.

Graph Neural Networks on Graph Databases https://www.w3.org/TR/sparql11-query/, 2013

Reference 27

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation c03c84bf-461f-454c-8e22-35be4fa3c1df · outbound

This paper cites Rdfox: A highly-scalable rdf store.

Graph Neural Networks on Graph Databases Rdfox: A highly-scalable rdf store

Reference 28

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raw_fallback, observed 2026-08-12T18:38:44.117872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 990caa4d-56ea-4be7-84c1-c34bd954cab5 · outbound

This paper cites https://aws.amazon.com/neptune/.

Graph Neural Networks on Graph Databases https://aws.amazon.com/neptune/

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 665a835a-669f-43d1-9875-bdad76d7476a · outbound

This paper cites Kùzu: Graph learning applications need a modern graph DBMS.

Graph Neural Networks on Graph Databases Kùzu: Graph learning applications need a modern graph DBMS

Reference 30

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raw_fallback, observed 2026-08-12T18:38:43.977040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation b92eef40-3e54-4048-b6c3-c9bf1d876cc0 · outbound

This paper cites Neural graph databases.

Graph Neural Networks on Graph Databases Neural graph databases

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation cde6deec-8f25-4a79-9027-210dd70e341c · outbound

This paper cites an unresolved cited work.

Graph Neural Networks on Graph Databases Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-12T18:38:43.950185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ff457a81-1ae1-4053-b6ca-5445c63ea648 · outbound

This paper cites node2vec: Scalable feature learning for networks.

Graph Neural Networks on Graph Databases node2vec: Scalable feature learning for networks

Reference 33

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raw_fallback, observed 2026-08-12T18:38:43.941683Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.439091Z digest=sha256:ece12ef752e2d4085ab3d3584e2c2b12ec41017dd0075aab294b4e2606f5d8e5

Observation fd7ca8c4-f0f7-4eab-af36-2bf1ab11f7ce · outbound

This paper cites Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases.

Graph Neural Networks on Graph Databases Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases

Reference 34

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no resolver link, observed 2026-08-12T18:38:42.451234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:38:42.451234Z digest=sha256:03d5f122ae5ae483a238f9c97f4b9fb0433e62e1ff7d09bdeb4b165c79d5d4a3

Observation cd50fd52-7ed8-4ca7-8fd4-f80c68dddd40 · outbound

This paper cites Relational Deep Learning: Graph Representation Learning on Relational Databases.

Graph Neural Networks on Graph Databases Relational Deep Learning: Graph Representation Learning on Relational Databases

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:38:42.503601Z digest=sha256:d34e8b5b98fd79582763505c451e078d16c96749b8bb8dd4682cfe128e74e9eb

Observation 10328bc6-e0d8-4fe9-9be2-328f7d8aa3b2 · outbound

This paper cites The shift from models to compound ai systems.

Graph Neural Networks on Graph Databases The shift from models to compound ai systems

Reference 36

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raw_fallback, observed 2026-08-12T18:38:43.822846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.575095Z digest=sha256:7d1b2c0d405735f8bb6c3653248f1905d1830cd2c429cd353560d37167e933a7

Observation 415248fe-da8a-4244-9720-98b0b3f3df19 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.

Graph Neural Networks on Graph Databases Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 750ba800-dc34-43d5-9fa3-90174dc0e7b4 · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

Graph Neural Networks on Graph Databases From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 38

Resolution
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no resolver link, observed 2026-08-12T18:38:42.580782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8ccfae1a-1a00-4cd7-b9ca-62227accdcf1 · outbound

This paper cites GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning.

Graph Neural Networks on Graph Databases GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T18:38:42.584532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3c37bca3-7526-4d61-ba6e-677cbd9f53ea · outbound

This paper cites Exploration of approaches for in- database ml.

Graph Neural Networks on Graph Databases Exploration of approaches for in- database ml

Reference 40

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fb4c23a6-5860-4e39-8c1d-2abe439875d9 · outbound

This paper cites Learning Models over Relational Data using Sparse Tensors and Functional Dependencies.

Graph Neural Networks on Graph Databases Learning Models over Relational Data using Sparse Tensors and Functional Dependencies

Reference 41

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unresolved
no resolver link, observed 2026-08-12T18:38:42.589634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:38:42.589634Z digest=sha256:f5cb2c393a259340daa7f6ff46ae00a891dbb277a66c2020bd28bc6ec92e999c

Observation a511ede3-5e0d-486d-ab2f-e99c6e136992 · outbound

This paper cites The Relational Data Borg is Learning.

Graph Neural Networks on Graph Databases The Relational Data Borg is Learning

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-12T18:38:42.951680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 54d1b672-c3d4-405d-9575-4dde967919fe · outbound

This paper cites https://www.pinecone.io/.

Graph Neural Networks on Graph Databases https://www.pinecone.io/

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:38:43.765068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 0ce8fc9b-ec22-4aeb-8958-5c3fb9c78edc · outbound

This paper cites The graph database interface: Scaling online transactional and analytical graph workloads to hundreds of thousands of cores.

Graph Neural Networks on Graph Databases The graph database interface: Scaling online transactional and analytical graph workloads to hundreds of thousands of cores

Reference 44

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.597739Z digest=sha256:9157afe1f3ad2674e0e4f0117ee6349cace5f830c9b3033b63b27b36ba55e4ba

Observation b28c3f29-fe4d-4887-bc75-6f0b47ecc8a7 · outbound

This paper cites Powerlyra: Differentiated graph computation and partitioning on skewed graphs.

Graph Neural Networks on Graph Databases Powerlyra: Differentiated graph computation and partitioning on skewed graphs

Reference 45

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.600229Z digest=sha256:870354625b18c12089f65e69bddf0de5aecb091584b3195392819c0ea117b16d

Observation c0ff9aee-9e97-4599-abf6-a1115867c6ff · outbound

This paper cites G-Tran: Making Distributed Graph Transactions Fast.

Graph Neural Networks on Graph Databases G-Tran: Making Distributed Graph Transactions Fast

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-12T18:38:42.902830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.638625Z digest=sha256:673b710d138bb3579a8fff3faafe026c48d92388731ef1ffa073bccaa760078f

Observation 7acfdbf3-a14e-453c-adff-097bb64835ed · outbound

This paper cites Kùzu graph database management system.

Graph Neural Networks on Graph Databases Kùzu graph database management system

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:38:43.643459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.656460Z digest=sha256:165cafde02695708fb0dddc76379b053fa9c5272d244e739363d35cc29ebc84a

Observation 13a51a4d-b468-438c-b9d0-577224de49d5 · outbound

This paper cites https://graph500.org/.

Graph Neural Networks on Graph Databases https://graph500.org/

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:38:43.536493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.668102Z digest=sha256:3f5492b0ab4e6fc35209a65e632489249e90252f9c0a0a97cb4a9d1274f8bbde

Observation 21eafc5d-b501-45d1-b8de-25c82f958bd8 · outbound

This paper cites Sampling meth- ods for efficient training of graph convolutional networks: A survey.

Graph Neural Networks on Graph Databases Sampling meth- ods for efficient training of graph convolutional networks: A survey

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:38:43.492642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.683594Z digest=sha256:406a68e3dd5dab926bf5f367083167ee363941564f72d09bb702fdd0c1fb5179

Observation 9bb92ab9-f0da-4fc1-af8a-40660135d7cf · outbound

This paper cites Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding.

Graph Neural Networks on Graph Databases Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:38:43.483158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.686968Z digest=sha256:381b59bd06f8ffa7b2326eb9ed6c97ddbbadfafe98e522da48b6c369cc1535ba

Observation 4225fd78-2bb3-42fa-b8d8-c3f3ea00d3b4 · outbound

This paper cites Het- erogeneous graph attention network.

Graph Neural Networks on Graph Databases Het- erogeneous graph attention network

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:38:43.474970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T18:38:42.690217Z digest=sha256:f8562b247158f34b6e76cad7fd3dd6553879df13d62d343da03f26438d4e1902

Observation 8e528a4f-af08-411a-8d03-16816334c74a · outbound

This paper cites Chawla, and Ananthram Swami.

Graph Neural Networks on Graph Databases Chawla, and Ananthram Swami

Reference 52

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unresolved
no resolver link, observed 2026-08-12T18:38:42.692186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:38:42.692186Z digest=sha256:ec8a2fbaf8e8b9cc1545cb1ad99e395aa235cc9536db0377be62c8e4d81e854f

Observation 9ef27059-9db2-460f-b841-ac3a49a5dfbd · outbound

This paper cites an unresolved cited work.

Graph Neural Networks on Graph Databases Unresolved cited work

Reference 53

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unresolved
no resolver link, observed 2026-08-12T18:38:42.694233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:38:42.694233Z digest=sha256:37af80d84531c5c820c51fee0d5b1e0634874e8b84542fa58cf36f46517679a8

Observation fc4dd157-e820-40bf-be79-be37d56ceae9 · outbound

This paper cites doi: 10.1023/A:1009953814988.

Graph Neural Networks on Graph Databases doi: 10.1023/A:1009953814988

Reference 2000

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unresolved
no resolver link, observed 2026-08-12T18:38:42.397126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:38:42.397126Z digest=sha256:4da1638a211965dac02fea4a2011e2d8a48b2c39f44127f997b5bb483f7f66f5

Observation 49856fd0-f675-4202-af74-314524a67d8f · outbound

This paper cites an unresolved cited work.

Graph Neural Networks on Graph Databases Unresolved cited work

Reference 2023

Resolution
unresolved
raw_fallback, observed 2026-08-12T18:38:43.968260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Pith citing papers

No inbound Pith citation observations are available.