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Paper Citation Record · LEDGER

Open Graph Benchmark: Datasets for Machine Learning on Graphs

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 59 inbound Pith citation observations for arXiv:2005.00687.

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

pith.paper-citation-record.v1
2005.00687 v7

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measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 59 of 59 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 59 of 59 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:19:33.955710Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:49:18.647891Z

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Outbound references

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Pith citing papers

Observation 6bda76c1-54c6-43d2-96bd-be93f6189929 · inbound

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

Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 8

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arxiv_id, observed 2026-05-24T00:39:33.141199Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 295d3210-2a20-4a9c-93e6-4279da46c718 · inbound

How Attentive are Graph Attention Networks? cites this paper.

How Attentive are Graph Attention Networks? Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 26

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arxiv_id, observed 2026-05-17T02:33:38.778840Z

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Observation d9b0e251-8704-45ea-99cf-0217dd57b658 · inbound

Spectral Subspace Clustering for Attributed Graphs cites this paper.

Spectral Subspace Clustering for Attributed Graphs Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 36

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source=pdf_text observed=2026-08-12T19:06:55.737396Z digest=sha256:bb247da69b1546e006b8ac7c65bbde3c779fb5c6e4c63deac5f1074e07af0986

Observation b90e845d-266e-4c63-92a6-321b51be16e0 · inbound

Instance-Aware Graph Prompt Learning cites this paper.

Instance-Aware Graph Prompt Learning Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 18

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source=arxiv_source observed=2026-08-12T11:56:36.714523Z digest=sha256:cd9d417f5b1787aa5d91a28e7d254ddbf81ecfd63f4bbb8de7d0eac35edfd261

Observation ee54581c-8003-4128-864b-11d3242f6c4e · inbound

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks cites this paper.

Revisiting the Necessity of Graph Learning and Common Graph Benchmarks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 16

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source=arxiv_source observed=2026-08-11T20:00:34.298186Z digest=sha256:835d87df7ecbbfc2c808dca22a71899a376c3e57cd4f47427e31678876e6bef2

Observation 02606d9e-2b2c-408a-b3d9-13ee2b5e58ab · inbound

MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media cites this paper.

MGM: Global Understanding of Audience Overlap Graphs for Predicting the Factuality and the Bias of News Media Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 40

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source=arxiv_source observed=2026-08-11T17:02:47.399858Z digest=sha256:05a37bea1d5a1501ecd31f9efdb9f1e15a0ca7050db06bfeb92f45dd954ea255

Observation 353528ec-ac2b-4406-b741-b72514bd890b · inbound

Graph-Guided Textual Explanation Generation Framework cites this paper.

Graph-Guided Textual Explanation Generation Framework Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 17

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source=arxiv_source observed=2026-08-11T14:18:17.149953Z digest=sha256:dd0427261820b351f3e09f14dadfb46c0e13812482f020a384e0a46ca4a77bc2

Observation 57542c6c-e579-4d05-94c7-8fc0a6bfc674 · inbound

Enhancing Persona Classification in Dialogue Systems: A Graph Neural Network Approach cites this paper.

Enhancing Persona Classification in Dialogue Systems: A Graph Neural Network Approach Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 10

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source=arxiv_source observed=2026-08-11T13:20:06.463887Z digest=sha256:8b047f148382485fea8a79820f4a665e044de360da0b3b27a1552d93d7d8e5ac

Observation c276d391-3d1a-4781-bae7-ed59ce8d4ef9 · inbound

PASCO (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms cites this paper.

PASCO (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 37

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source=pdf_text observed=2026-08-11T13:03:17.426897Z digest=sha256:edac1b45748e8cc9aa31cc8eafd13ac4b82e65aa05e6eafaa1f551ca4378b356

Observation d2f911e7-96d0-4d19-a956-1b68e143a58f · inbound

Is Peer-Reviewing Worth the Effort? cites this paper.

Is Peer-Reviewing Worth the Effort? Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 22

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source=arxiv_source observed=2026-08-11T12:24:04.986107Z digest=sha256:9d4106460bc909ce2802334b366f15e1a9051c3f83c93f3ffffb1369011dce08

Observation c5b331e1-763f-4188-a5e3-c40e91ac76fc · inbound

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks cites this paper.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 25

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source=arxiv_source observed=2026-08-11T10:51:16.178177Z digest=sha256:70d613030b78332a81403a1236c544e403733b8bfdd8288ff84f06a31d4019ba

Observation 08c0e4d8-8ded-42a4-9b44-487f86315581 · inbound

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators cites this paper.

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 23

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source=pdf_text observed=2026-08-10T22:20:58.810421Z digest=sha256:0b5283fb3b3f243a96e77c250fec4830623a9602dee21f06ad404d219d6d3a04

Observation 940e5b22-fbb8-4a2e-89bb-b9ead694f30e · inbound

ReInc: Scaling Training of Dynamic Graph Neural Networks cites this paper.

ReInc: Scaling Training of Dynamic Graph Neural Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 21

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source=pdf_text observed=2026-08-10T14:28:16.785348Z digest=sha256:f42bc2d244b88e6cece0159e22dd515a90a2364ffb08be4aeadfa6e0a650524b

Observation 3e925a93-dc90-49fd-904e-0cbe667515bb · inbound

On the Effectiveness of Random Weights in Graph Neural Networks cites this paper.

On the Effectiveness of Random Weights in Graph Neural Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 19

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source=arxiv_source observed=2026-08-09T19:59:58.762819Z digest=sha256:519ce175adceca0739eaf22a30ba0b7806603bc825922a051c016b4f7f5801c1

Observation 0f642535-ceba-486c-bf20-5abdb34707db · inbound

Computing and Learning on Combinatorial Data cites this paper.

Computing and Learning on Combinatorial Data Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 259

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source=pdf_text observed=2026-08-08T20:29:47.178238Z digest=sha256:ba20f043998b5a5ab8c656d7482537133bda0f51307c1a24e638791070166a5f

Observation 7296b421-3244-4327-b68a-16183b01ff05 · inbound

Effects of Dropout on Performance in Long-range Graph Learning Tasks cites this paper.

Effects of Dropout on Performance in Long-range Graph Learning Tasks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 40

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source=pdf_text observed=2026-08-08T13:03:13.869632Z digest=sha256:85897eb7bebeeef642039f989e17aada82f02116788347b9e5e0007403591611

Observation 9896b0d5-edd6-49ca-ac09-393412c7c530 · inbound

Active Few-Shot Learning for Vertex Classification Starting from an Unlabeled Dataset cites this paper.

Active Few-Shot Learning for Vertex Classification Starting from an Unlabeled Dataset Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 38

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source=pdf_text observed=2026-08-16T10:19:33.955710Z digest=sha256:b6d75d392943bb17cf918884394b621a2a1bdba561e427ac8eed2f1b8a5b878b

Observation 6c97110a-06b5-41ec-ab7c-01f2d63578c2 · inbound

GRAIL: Graph Edit Distance and Node Alignment Using LLM-Generated Code cites this paper.

GRAIL: Graph Edit Distance and Node Alignment Using LLM-Generated Code Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 21

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source=arxiv_source observed=2026-08-16T01:08:47.809212Z digest=sha256:72aaa70fc6e61c38057e985cfe5a0bf33b3fe4346967b3f8bbc0cffe3cbf029a

Observation 81eb9813-e817-4c86-abb7-d4c08859773a · inbound

Fused3S: Fast Sparse Attention on Tensor Cores cites this paper.

Fused3S: Fast Sparse Attention on Tensor Cores Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 14

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Observation 5c484b94-d834-4b66-8dfd-7c9cd761ad54 · inbound

GNN-Suite: a Graph Neural Network Benchmarking Framework for Biomedical Informatics cites this paper.

GNN-Suite: a Graph Neural Network Benchmarking Framework for Biomedical Informatics Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 18

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Observation 6d9d9eb2-86c2-45d4-8794-ace4e1fc0e07 · inbound

MolTextNet: A Two-Million Molecule-Text Dataset for Multimodal Molecular Learning cites this paper.

MolTextNet: A Two-Million Molecule-Text Dataset for Multimodal Molecular Learning Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 8

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Observation 08a8fcbe-ad34-41cc-9afd-ab6acb71cfa2 · inbound

ReconXF: Graph Reconstruction Attack via Public Feature Explanations on Privatized Node Features and Labels cites this paper.

ReconXF: Graph Reconstruction Attack via Public Feature Explanations on Privatized Node Features and Labels Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 7

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Observation e5b61d6e-a1d7-4568-910c-10c06414de59 · inbound

The Oversmoothing Fallacy: A Misguided Narrative in GNN Research cites this paper.

The Oversmoothing Fallacy: A Misguided Narrative in GNN Research Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 15

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source=pdf_text observed=2026-08-07T10:43:58.034479Z digest=sha256:4bb29e9d951516c6a132ef486121828e792978221df9fde8116e3ebe5c724950

Observation c9b9c978-8514-4096-ba95-63c0e5da51c6 · inbound

NOCL: Node-Oriented Conceptualization LLM for Graph Tasks without Message Passing cites this paper.

NOCL: Node-Oriented Conceptualization LLM for Graph Tasks without Message Passing Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 18

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Observation 3a1510c9-837c-4907-b226-b696858b67aa · inbound

Toward a Graph Foundation Model: Pre-Training Transformers With Random Walks cites this paper.

Toward a Graph Foundation Model: Pre-Training Transformers With Random Walks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 35

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Observation 2af4eac9-4e06-417c-a00f-588a14b09972 · inbound

ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs cites this paper.

ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 50

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Observation 3abc0a6f-d97e-4720-a462-38995d49bdec · inbound

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion cites this paper.

SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 23

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source=arxiv_source observed=2026-08-05T18:43:44.238519Z digest=sha256:4597a9d26b1c20891223745ed119959105b0a0d3c80a1cab90bdee9e41ae1df3

Observation 61baf7f2-f2ab-4736-b375-469c944253b7 · inbound

Memorization in Graph Neural Networks cites this paper.

Memorization in Graph Neural Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 30

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source=pdf_text observed=2026-08-05T15:53:52.465158Z digest=sha256:957be6c3174b71d192a27f50922f35e025605ccee66b62334094b7842f8c3206

Observation fc7841b2-f986-42a8-95b1-4837cde75461 · inbound

A Graph Talks, But Who's Listening? Rethinking Evaluations for Graph-Language Models cites this paper.

A Graph Talks, But Who's Listening? Rethinking Evaluations for Graph-Language Models Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 2021

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source=pdf_text observed=2026-08-15T16:47:43.605247Z digest=sha256:be685b193295f4392111f474689daace7b914d5a7bb80c0726a11c1c2cf80805

Observation 9d0a692f-520b-41d9-8258-dd55b59d57a0 · inbound

Task-Aware Adaptive Modulation: A Replay-Free and Resource-Efficient Approach For Continual Graph Learning cites this paper.

Task-Aware Adaptive Modulation: A Replay-Free and Resource-Efficient Approach For Continual Graph Learning Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 2020

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source=pdf_text observed=2026-08-05T13:23:08.533196Z digest=sha256:c00a1f5686bceaa780f83584ac089aa03b9e768a60bc7b10af8be53aac9e65e6

Observation e39185db-53b3-4286-9663-a6ea95366768 · inbound

SHIRO: Near-Optimal Communication Strategies for Distributed Sparse Matrix Multiplication cites this paper.

SHIRO: Near-Optimal Communication Strategies for Distributed Sparse Matrix Multiplication Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 18

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arxiv_id, observed 2026-05-16T20:41:15.416943Z

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source=pdf_text observed=2026-05-16T20:38:25.847537Z digest=sha256:ad5cf54bc08a03ca174b3bafaae85dc9480e041ea626e641fa0487633fa423a9

Observation bbecfb7f-041c-48f9-a8a0-c34f121fe244 · inbound

Plain Transformers are Surprisingly Powerful Link Predictors cites this paper.

Plain Transformers are Surprisingly Powerful Link Predictors Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 2024

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source=pdf_text observed=2026-08-03T05:44:24.825958Z digest=sha256:cf422b55c0acf51975adf4b33e3a1a5e85c65c94ff16142adf365fd087346475

Observation e34aa49d-df5f-4a42-99e7-256370da68de · inbound

CTS-Bench: Benchmarking Graph Coarsening Trade-offs for GNNs in Clock Tree Synthesis cites this paper.

CTS-Bench: Benchmarking Graph Coarsening Trade-offs for GNNs in Clock Tree Synthesis Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 9

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source=pdf_text observed=2026-08-02T21:41:05.520058Z digest=sha256:80159e7adfd18b35ca1ca3fc790f507483bc9ab51356cfda0eea70318f4f2fdd

Observation 7b95725f-008c-402c-af40-0d51c17cefe4 · 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 Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 57

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arxiv_id, observed 2026-05-13T20:43:15.341475Z

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source=pdf_text observed=2026-05-13T20:38:31.444109Z digest=sha256:9512801c15227e1592573d18d750df4bb07f442782e4237534fd5c4f00bd2686

Observation cb21a7f0-be7a-4660-ab8b-c357ef5cea3f · inbound

TRAVELFRAUDBENCH: A Configurable Evaluation Framework for GNN Fraud Ring Detection in Travel Networks cites this paper.

TRAVELFRAUDBENCH: A Configurable Evaluation Framework for GNN Fraud Ring Detection in Travel Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 8

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arxiv_id, observed 2026-05-11T13:51:02.425249Z

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source=arxiv_source observed=2026-05-10T00:30:25.954515Z digest=sha256:ba3ae2b5d2a487289eef8c4d606e3571d99cb69a9dc18012e64a1d63b9147908

Observation c317fa1d-b5cc-47a9-a6f9-5abe9ae3cc81 · inbound

Exploring Sparse Matrix Multiplication Kernels on the Cerebras CS-3 cites this paper.

Exploring Sparse Matrix Multiplication Kernels on the Cerebras CS-3 Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 15

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arxiv_id, observed 2026-05-12T10:26:28.875922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-07T06:14:12.828938Z digest=sha256:63eb85af86a76763c75c8c0b74e044c7fdf2c1b8667edcd71918dbf1b4a57e62

Observation c090f555-c509-43e3-b91c-16ecb461ed56 · inbound

GraphSculptor: Sculpting Pre-training Coreset for Graph Self-supervised Learning cites this paper.

GraphSculptor: Sculpting Pre-training Coreset for Graph Self-supervised Learning Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 7

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verified exact
arxiv_id, observed 2026-05-11T16:51:09.449829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-09T14:36:29.620205Z digest=sha256:8c54a5768dce542dc212ed803666cb16b2a994f4bafeb214f297e1c67ae04b6b

Observation 39d8451b-57d8-41a5-9ce2-6f22d192f1c9 · inbound

Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks cites this paper.

Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 204

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verified exact
arxiv_id, observed 2026-05-11T16:46:06.622014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-09T15:09:03.417040Z digest=sha256:4d25e74235d4db3202d51a0e18afa50136434ec6cc9a3f9f1f99c21444c87ccc

Observation 8117d752-b3ab-46d3-88f8-b522204428d1 · inbound

H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction cites this paper.

H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 50

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metadata mismatch
arxiv_id, observed 2026-05-11T22:46:11.712695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-08T02:31:27.091956Z digest=sha256:d5cd318dac9043d8eeab4545fdeca0dc9e45402d61d706615213547bcecfd6ca

Observation c6c86121-e5ef-4ef3-84b2-6b53ee280dcd · inbound

Fast and Featureless Node Representation Learning with Partial Pairwise Supervision cites this paper.

Fast and Featureless Node Representation Learning with Partial Pairwise Supervision Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 33

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arxiv_id, observed 2026-05-20T06:43:06.025290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T06:39:02.277629Z digest=sha256:190e160294bf8dce397aafa7d37bce53392978e4326527031223d79df740f7b9

Observation 4e0b7c82-a3f9-4318-89d1-4fd4d284f189 · inbound

Efficient Higher-order Subgraph Attribution via Message Passing cites this paper.

Efficient Higher-order Subgraph Attribution via Message Passing Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 40

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verified exact
arxiv_id, observed 2026-05-22T07:54:43.110168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-22T07:53:40.841765Z digest=sha256:ddaddbd68000ea220c470b1613c61f1ce3e499f0ca2b7394a8876d190360d9f2

Observation c9c1e942-d2c1-4a2d-b8bd-be469393b86d · inbound

Relevant Walk Search for Explaining Graph Neural Networks cites this paper.

Relevant Walk Search for Explaining Graph Neural Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 41

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verified exact
arxiv_id, observed 2026-05-25T05:15:22.514791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-25T05:12:00.156450Z digest=sha256:33613006ee7ef0f1f78b0407427cad4ea727d5409adcdf42c1a8214f8569afad

Observation f9ee4208-18a2-4309-8809-9536a09232d8 · inbound

Learning Dynamic Stability Landscapes in Synchronization Networks cites this paper.

Learning Dynamic Stability Landscapes in Synchronization Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 295

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verified exact
arxiv_id, observed 2026-05-25T05:05:22.674246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-25T05:04:16.957305Z digest=sha256:02206946083df896b2c6eef696e9cb8b9773b9dc9595f8abd9310e446bdfe86d

Observation cf414894-db55-49a4-8cab-25bfdf5e2971 · inbound

On Efficient Scaling of GNNs via IO-Aware Layers Implementations cites this paper.

On Efficient Scaling of GNNs via IO-Aware Layers Implementations Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 11

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metadata mismatch
arxiv_id, observed 2026-07-01T19:16:01.092980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T22:52:59.081816Z digest=sha256:77711e50948194c00192a4901735fcb97189276d5e951e8c031e5217e210180b

Observation 2cb18971-1bb4-4bb7-9220-4955a45b0329 · inbound

Handling Feature Heterogeneity with Learnable Graph Patches cites this paper.

Handling Feature Heterogeneity with Learnable Graph Patches Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 17

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verified exact
arxiv_id, observed 2026-07-03T20:08:56.272946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-27T01:36:45.977332Z digest=sha256:e7a015615199a067eab3b720825c2a1df205bc772b4cd59e94bc08dff9b9aa39

Observation 635dfa1c-7879-40b3-be02-91831e9c633d · inbound

DeXposure-Claw: An Agentic System for DeFi Risk Supervision cites this paper.

DeXposure-Claw: An Agentic System for DeFi Risk Supervision Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 63

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verified exact
arxiv_id, observed 2026-07-04T00:49:18.650500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-26T20:57:32.647600Z digest=sha256:2ce12903b49ccfe7fd54d334797b6c993c312bcece0fedfaed374b8b2faf14e1

Observation 777c6378-e6a1-4b10-be41-53ac21aeaa8a · inbound

DeXposure-Claw: An Agentic System for DeFi Risk Supervision cites this paper.

DeXposure-Claw: An Agentic System for DeFi Risk Supervision Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-07-01T07:35:28.916229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-07-01T07:31:47.518981Z digest=sha256:1de3c2d45073c948380d14c6cb89ab7abd80f51b5684e3dc322d156115777d40

Observation 03b7b94a-8448-4059-b73d-989f97d78aca · inbound

Graph Dimensionality Reduction for Contextual Bandits: Structure-Specific Regret Bounds under Approximate Smoothness and Noisy Eigenspaces cites this paper.

Graph Dimensionality Reduction for Contextual Bandits: Structure-Specific Regret Bounds under Approximate Smoothness and Noisy Eigenspaces Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 17

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verified exact
arxiv_id, observed 2026-07-01T16:55:51.224765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-29T04:24:32.483334Z digest=sha256:eeb5645fcd91320f22ffe02b2d6f3e745fc0e271dab276bdc0fcc2d68c463b25

Observation 8a99fc3c-e001-4dd7-af92-1012b2789030 · inbound

T3R: Deeper Test-Time Adaptation for Graph Neural Networks via Gradient Rotation cites this paper.

T3R: Deeper Test-Time Adaptation for Graph Neural Networks via Gradient Rotation Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 4

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verified exact
arxiv_id, observed 2026-06-30T07:34:21.948157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-30T07:26:05.735508Z digest=sha256:981d7d15af35fcc6ec8a3222b0fd08df09ac4c4eb2d09be8b78c7d07d7149d36

Observation a8e80baa-2eae-4e1d-b89d-11e338f23aa8 · inbound

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation cites this paper.

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 25

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no resolver link, observed 2026-08-01T13:29:53.256490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T13:29:53.256490Z digest=sha256:e45f32c4fe3802c7cfe61f5472c175415a2d7d3f53a4f236842f8b87dab82289

Observation d0ea85ae-5b2f-45b1-b1d9-fe8540d38f3b · inbound

One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models cites this paper.

One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language Models Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 40

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unresolved
no resolver link, observed 2026-08-01T13:26:33.058578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T13:26:33.058578Z digest=sha256:5198ecb5c26a3fbfd96d08f718c881718dc74cfec8ef0a4b28a669fb26fcefe3

Observation 5c86a81a-e22a-4a05-9b72-a1c0f9866722 · inbound

ParasGB: A Graph Benchmark Suite for Parasitic Estimation on AMS Circuits cites this paper.

ParasGB: A Graph Benchmark Suite for Parasitic Estimation on AMS Circuits Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 12

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no resolver link, observed 2026-08-01T00:04:26.891576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:04:26.891576Z digest=sha256:8b6b36bb623ce354a28ee3112e5c02ee006a49e263b3dd078c8f5c07bd674767

Observation 9513f994-a1ae-471c-bfd8-1a8f39f75927 · inbound

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning cites this paper.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 41

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no resolver link, observed 2026-07-31T18:33:46.767206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T18:33:46.767206Z digest=sha256:3b91475f71be8566a56030fa3fb45e885bebc4649d07c49414e90f1b612a90a2

Observation 2373ea57-5968-4296-b834-8c67b20d19d7 · inbound

THGFM: Dual-Branch Temporal Heterogeneous Graph Fusion Model cites this paper.

THGFM: Dual-Branch Temporal Heterogeneous Graph Fusion Model Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 8

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no resolver link, observed 2026-08-01T09:58:38.391913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T09:58:38.391913Z digest=sha256:0bccbba60d1e24dff366bbf639f007c887dba963b2d282f9527ebc242b5277db

Observation b54ff34f-0946-423c-992a-f26465db395f · inbound

THBKG: A Temporal Biomedical Knowledge Graph for Decision-Aligned Clinical Advancement Prediction cites this paper.

THBKG: A Temporal Biomedical Knowledge Graph for Decision-Aligned Clinical Advancement Prediction Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 22

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no resolver link, observed 2026-08-07T20:00:45.962410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:00:45.962410Z digest=sha256:07c986d6ea3fd53fb8f2f2a8c336001d852aae450b0c79dc5de2cd8b5533f253

Observation e50552a8-7fb1-4d63-8e36-34d76fe9582e · inbound

MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records cites this paper.

MiGHT-EHR: A Multi-task Graph Transformer for Heterogeneous Temporal Electronic Health Records Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 74

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no resolver link, observed 2026-08-10T04:32:43.144169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:32:43.144169Z digest=sha256:dc02ead2910500173ce9b5247bc76511ad14faee0d846cf619175f7032007ce0

Observation 7afafab2-8717-4c02-b136-b54fbed61bf7 · inbound

SNI-GNN: SmartNIC-Assisted Full-Graph GNN Training with In-Network Embedding Prediction cites this paper.

SNI-GNN: SmartNIC-Assisted Full-Graph GNN Training with In-Network Embedding Prediction Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 40

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no resolver link, observed 2026-08-10T04:30:57.364939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T04:30:57.364939Z digest=sha256:ac292fdfc64639eba0c14c4981feabd5fd00e1fa5634ccfacfebddee875eec76

Observation e501fdc0-2e80-483f-b4d5-5065e60f52e2 · inbound

LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs cites this paper.

LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 11

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unresolved
no resolver link, observed 2026-08-11T00:24:53.863601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:24:53.863601Z digest=sha256:3d93bec6d1dd7be579c8fcece00fcfa0d75beb922f06b3be57d71f77abc8f2f4

Observation 2740b79f-1747-479e-816c-3182420fc23a · inbound

Neural Message Passing on Structural Interaction Graphs for Fully-Inductive Graph Neural Networks cites this paper.

Neural Message Passing on Structural Interaction Graphs for Fully-Inductive Graph Neural Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 54

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no resolver link, observed 2026-08-14T04:38:54.283876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:38:54.283876Z digest=sha256:91bfb893d6ccc33e62b2c3d02ac56d5cfa524c4b73ccaad56ade00b3f592cd27