Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection | Paper Citation Record

Observation 453c52a4-2147-4d65-9f3b-9b57972bc656 · outbound

This paper cites Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models,

Reference 1

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This paper cites Self-supervised learning for time series analysis: Taxonomy, progress, and prospects,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Self-supervised learning for time series analysis: Taxonomy, progress, and prospects,

Reference 2

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This paper cites Fighting against organized fraudsters using risk diffusion-based parallel graph neural network.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Fighting against organized fraudsters using risk diffusion-based parallel graph neural network

Reference 3

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Observation 2f5c7fef-c6c5-4c46-8ddd-7d7ecc3b0be8 · outbound

This paper cites A comprehensive survey on graph neural networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection A comprehensive survey on graph neural networks,

Reference 4

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This paper cites Comga: Community-aware attributed graph anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Comga: Community-aware attributed graph anomaly detection,

Reference 5

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Observation b9b91b16-cfb1-4a3a-bac4-c01e53e33710 · outbound

This paper cites Interleaved sequence rnns for fraud detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Interleaved sequence rnns for fraud detection,

Reference 6

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This paper cites Fang: Leverag- ing social context for fake news detection using graph representation,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Fang: Leverag- ing social context for fake news detection using graph representation,

Reference 7

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Observation a2243735-ce44-4f29-995d-6c25c1d08e69 · outbound

This paper cites Netwalk: A flexible deep embedding approach for anomaly detection in dynamic networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Netwalk: A flexible deep embedding approach for anomaly detection in dynamic networks,

Reference 8

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Observation 99bca3a8-386b-4166-a80f-f970066e24e9 · outbound

This paper cites Bond: Benchmarking unsupervised outlier node detection on static attributed graphs,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Bond: Benchmarking unsupervised outlier node detection on static attributed graphs,

Reference 9

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Observation 3c1eb930-b46c-4fa0-b9fd-e508f6269e1f · outbound

This paper cites Counter- factual data augmentation with denoising diffusion for graph anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Counter- factual data augmentation with denoising diffusion for graph anomaly detection,

Reference 10

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This paper cites Radar: Residual analysis for anomaly detection in attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Radar: Residual analysis for anomaly detection in attributed networks,

Reference 11

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Observation 7a01817c-733c-431b-915e-d6314d0ba683 · outbound

This paper cites Mixedad: A scalable algorithm for detecting mixed anomalies in attributed graphs,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Mixedad: A scalable algorithm for detecting mixed anomalies in attributed graphs,

Reference 12

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Observation 2b793e22-a9a7-40f5-8b5b-1aede26a7e47 · outbound

This paper cites Anomaly de- tection on attributed networks via contrastive self-supervised learning,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Anomaly de- tection on attributed networks via contrastive self-supervised learning,

Reference 13

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Observation 245894cb-d218-475a-a99f-74a96f567e6f · outbound

This paper cites A comprehensive survey on graph anomaly detection with deep learning,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection A comprehensive survey on graph anomaly detection with deep learning,

Reference 14

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Observation 5da4a1b9-7e47-441e-a227-e37c34134138 · outbound

This paper cites Deep anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Deep anomaly detection on attributed networks,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 12380986-912a-4ef8-bda2-45e3eac0cb21 · outbound

This paper cites Hybrid-order anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Hybrid-order anomaly detection on attributed networks,

Reference 16

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Observation aca66c0c-af6a-4b3c-bb9a-126414c9d8ec · outbound

This paper cites A deep multi- view framework for anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection A deep multi- view framework for anomaly detection on attributed networks,

Reference 17

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This paper cites Generative and contrastive self-supervised learning for graph anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Generative and contrastive self-supervised learning for graph anomaly detection,

Reference 18

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Observation f3ca6895-8be2-4e49-838c-d79e319ad592 · outbound

This paper cites Reconstruction enhanced multi-view contrastive learning for anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Reconstruction enhanced multi-view contrastive learning for anomaly detection on attributed networks,

Reference 19

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Observation 171c9783-269c-480a-999b-7db5a7db3a1c · outbound

This paper cites Graph anomaly detection via multi-scale contrastive learning networks with augmented view,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Graph anomaly detection via multi-scale contrastive learning networks with augmented view,

Reference 20

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Observation 19de37dd-5392-48b8-86a9-a42f0b8a9665 · outbound

This paper cites Embracing change: Continual learning in deep neural networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Embracing change: Continual learning in deep neural networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:55.803122Z

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This paper cites Octavius: Mitigating task inter- ference in mllms via moe,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Octavius: Mitigating task inter- ference in mllms via moe,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:55.642597Z

Source-reported events for the cited work

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Observation f2f97726-fd7c-4055-859c-198136fdf02e · outbound

This paper cites Graph neural networks beyond compromise between attribute and topology,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Graph neural networks beyond compromise between attribute and topology,

Reference 23

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Observation d826b387-90b2-4a4e-a60d-68eac83c72d7 · outbound

This paper cites Am-gcn: Adaptive multi-channel graph convolutional networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Am-gcn: Adaptive multi-channel graph convolutional networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:55.313221Z

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This paper cites Divide and contrast: Self- supervised learning from uncurated data,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Divide and contrast: Self- supervised learning from uncurated data,

Reference 25

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This paper cites Component divide-and-conquer for real-world image super-resolution,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Component divide-and-conquer for real-world image super-resolution,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:55.017715Z

Source-reported events for the cited work

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Observation 491f2bed-adac-4199-933e-dcfb3ebfc23c · outbound

This paper cites A divide-and-conquer approach to the summarization of long documents,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection A divide-and-conquer approach to the summarization of long documents,

Reference 27

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Observation 26a92262-7589-4235-9288-6ea565734854 · outbound

This paper cites Ricci curvature of markov chains on metric spaces,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Ricci curvature of markov chains on metric spaces,

Reference 28

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Source-reported events for the cited work

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Observation 9dc4c803-ac6c-419b-b197-4fee740c3fdd · outbound

This paper cites Curvature graph network,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Curvature graph network,

Reference 29

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Source-reported events for the cited work

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Observation 785203cf-538b-4c61-bb90-b3ed76b6cc2f · outbound

This paper cites Learning stochastic equivalence based on discrete ricci curvature,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Learning stochastic equivalence based on discrete ricci curvature,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:54.366131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3b04f0b9-2ce3-4ed8-bd8c-e9bff809289e · outbound

This paper cites Curvature graph neural network,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Curvature graph neural network,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9432bbe6-ffd3-44bd-afe6-ade354fae749 · outbound

This paper cites Measuring and relieving the over-smoothing problem for graph neural networks from the topological view,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Measuring and relieving the over-smoothing problem for graph neural networks from the topological view,

Reference 32

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Source-reported events for the cited work

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Observation 8663d7be-dad1-43a9-82f7-5d19f2155ade · outbound

This paper cites Eliciting structural and semantic global knowledge in unsupervised graph contrastive learning,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Eliciting structural and semantic global knowledge in unsupervised graph contrastive learning,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c247fa3d-1f58-4401-8552-bb70d1eaef8a · outbound

This paper cites Self-supervised representation learning via latent graph prediction,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Self-supervised representation learning via latent graph prediction,

Reference 34

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Observation f6e8adc0-51ff-4fe3-b6d5-8b5c57d72a0d · outbound

This paper cites Counterfactual graph learning for anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Counterfactual graph learning for anomaly detection on attributed networks,

Reference 35

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Source-reported events for the cited work

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Observation e11ce737-a520-4c59-ae4a-71c35444f348 · outbound

This paper cites Learning strong graph neural networks with weak information,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Learning strong graph neural networks with weak information,

Reference 36

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Source-reported events for the cited work

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Observation b29d934b-6662-48eb-97aa-9b13c607fdc0 · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Semi-supervised classification with graph convolutional networks,

Reference 37

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Observation bd0b390b-d468-45a0-b5d6-035527b53d22 · outbound

This paper cites Knowledge distillation: A survey,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Knowledge distillation: A survey,

Reference 38

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Source-reported events for the cited work

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Observation 19f87bb8-e7f7-43bf-ae8b-86486774d115 · outbound

This paper cites Knowledge distillation on graphs: A survey,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Knowledge distillation on graphs: A survey,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:53.409655Z

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Observation 511e31e5-836a-40c9-beee-5910b91dce8b · outbound

This paper cites Triplet loss for knowledge distillation,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Triplet loss for knowledge distillation,

Reference 40

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Observation e63bb3c9-3c0c-4b20-a34b-26bd5c7cd766 · outbound

This paper cites Self-restrained triplet loss for accurate masked face recognition,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Self-restrained triplet loss for accurate masked face recognition,

Reference 41

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Source-reported events for the cited work

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Observation 76058b09-d1bb-44b5-9c00-324e76c7d0a7 · outbound

This paper cites Non-negative residual matrix factorization with application to graph anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Non-negative residual matrix factorization with application to graph anomaly detection,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:52.613409Z

Source-reported events for the cited work

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Observation daa696fc-f45f-4f3c-a33d-84985d510e98 · outbound

This paper cites Rethinking graph neural networks for anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Rethinking graph neural networks for anomaly detection,

Reference 43

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Source-reported events for the cited work

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Observation 70970a19-b93d-4479-ad46-6dd47f21e609 · outbound

This paper cites Inductive anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Inductive anomaly detection on attributed networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:52.002007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0cbe018e-1115-4c53-81c3-0d8c2c8ab8fb · outbound

This paper cites Scalable anomaly ranking of attributed neighborhoods,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Scalable anomaly ranking of attributed neighborhoods,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:51.764976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2c3ce880-eba2-4227-ae40-cf30cbccd0ab · outbound

This paper cites Anomalous: A joint modeling approach for anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Anomalous: A joint modeling approach for anomaly detection on attributed networks,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:51.529152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation beee456d-2f77-4cc3-baf0-9ba9c4a54ee9 · outbound

This paper cites Anomalydae: Dual autoencoder for anomaly detection on attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Anomalydae: Dual autoencoder for anomaly detection on attributed networks,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:51.326294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 109cb7f6-e52c-4418-8ed3-5eb37e4a2b77 · outbound

This paper cites Ada-gad: Anomaly- denoised autoencoders for graph anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Ada-gad: Anomaly- denoised autoencoders for graph anomaly detection,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:51.032828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 00ad1bc2-9877-4bb6-a258-0a783d32841a · outbound

This paper cites Gad- nr: Graph anomaly detection via neighborhood reconstruction,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Gad- nr: Graph anomaly detection via neighborhood reconstruction,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:50.815398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 87cc834b-06bf-4cb1-baa5-34a3e67d39e6 · outbound

This paper cites Federated graph anomaly detection via contrastive self-supervised learning,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Federated graph anomaly detection via contrastive self-supervised learning,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:50.641384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6d82a96b-b21c-4fc6-9b8c-7d76d656edab · outbound

This paper cites Lifelong language pretraining with distribution-specialized experts,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Lifelong language pretraining with distribution-specialized experts,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:50.340565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f4588ba-f6f3-4b4e-ae94-3c06cc94637a · outbound

This paper cites A divide-and-conquer method for scalable robust multitask learning,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection A divide-and-conquer method for scalable robust multitask learning,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:50.108564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation abf6277c-3804-4e73-a4cd-1ede65e34ab3 · outbound

This paper cites Graph learning: A survey,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Graph learning: A survey,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:49.907966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e4635471-b338-4907-bc6e-445578791d1a · outbound

This paper cites Augmentation-free self-supervised learning on graphs,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Augmentation-free self-supervised learning on graphs,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:49.654631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3934c403-5dea-4395-8c1b-cfae247080dc · outbound

This paper cites Accelerated local anomaly detection via resolving attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Accelerated local anomaly detection via resolving attributed networks,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:49.405799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 180c07c7-acc6-4b09-88af-3463d1dde1c2 · outbound

This paper cites an unresolved cited work.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:49:49.173916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2ba4f64d-c1c4-4744-9edc-54b6e5580fd4 · outbound

This paper cites Multiplex graph representation learning via dual correlation reduction,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Multiplex graph representation learning via dual correlation reduction,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:49.042958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c1d98a8d-61f7-4a8b-b1ed-3be404730f19 · outbound

This paper cites Self- attentive attributed network embedding through adversarial learning,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Self- attentive attributed network embedding through adversarial learning,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.873670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 00e9d351-4f6a-4cc2-b138-7508e3ffc82e · outbound

This paper cites Addressing het- erophily in graph anomaly detection: A perspective of graph spectrum,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Addressing het- erophily in graph anomaly detection: A perspective of graph spectrum,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.704661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e2244de5-918b-437a-aaad-814c844d8059 · outbound

This paper cites Motif- consistent counterfactuals with adversarial refinement for graph-level anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Motif- consistent counterfactuals with adversarial refinement for graph-level anomaly detection,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.591947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4a7386a2-f9eb-4e95-b339-8d17d0bdb600 · outbound

This paper cites Alleviat- ing structural distribution shift in graph anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Alleviat- ing structural distribution shift in graph anomaly detection,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.426508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7fc42af7-7e78-40ae-b27c-d18d691819e2 · outbound

This paper cites Learning graph deep autoencoder for anomaly detection in multi-attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Learning graph deep autoencoder for anomaly detection in multi-attributed networks,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.303587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 129b1280-5559-4c1e-93f8-9dc336902b29 · outbound

This paper cites Anomman: Detect anomalies on multi-view attributed networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Anomman: Detect anomalies on multi-view attributed networks,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.233342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 00870997-a209-4f1a-b3c6-cdd53623557e · outbound

This paper cites Arise: Graph anomaly detection on attributed networks via substructure awareness,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Arise: Graph anomaly detection on attributed networks via substructure awareness,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.162300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a0479ed4-9098-4856-8f3e-4b093d4f2382 · outbound

This paper cites Samcl: Subgraph-aligned multiview contrastive learning for graph anomaly detection,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Samcl: Subgraph-aligned multiview contrastive learning for graph anomaly detection,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:48.037581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fc96d2ab-ca5e-47a6-9e24-39b51b3b1b3b · outbound

This paper cites Anemone: Graph anomaly detection with multi-scale contrastive learning,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Anemone: Graph anomaly detection with multi-scale contrastive learning,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:47.900939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b4866151-9a52-44c0-8c8f-df50695236f6 · outbound

This paper cites Data augmentation for deep graph learning: A survey,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Data augmentation for deep graph learning: A survey,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:47.792527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b60e595b-d179-4407-81a8-123fdad5393c · outbound

This paper cites Learning on attribute-missing graphs,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Learning on attribute-missing graphs,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:47.663750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 090fc84f-a151-4fdd-a6a0-adbf8f3aa467 · outbound

This paper cites Heterogeneous graph neural net- work via attribute completion,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Heterogeneous graph neural net- work via attribute completion,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:47.551025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 415a3023-984b-406e-9f22-5fc2584733c9 · outbound

This paper cites Initializing then refining: A simple graph attribute imputation network,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Initializing then refining: A simple graph attribute imputation network,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:47.442513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1911bd45-a990-4932-b808-a10a6a1b9547 · outbound

This paper cites Missing data imputation with adversarially-trained graph convolutional networks,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Missing data imputation with adversarially-trained graph convolutional networks,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:47.217476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 240f4d1e-7575-4534-9fe4-613ef25c9c93 · outbound

This paper cites Graph convolutional networks for graphs containing missing features,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Graph convolutional networks for graphs containing missing features,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.938089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6aa41a84-081b-4d97-9da8-bb3a21ee5686 · outbound

This paper cites Handling missing data via max-entropy regularized graph autoencoder,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Handling missing data via max-entropy regularized graph autoencoder,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.819000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ba96d28-cdb5-4ce2-8219-12175804b98e · outbound

This paper cites S2gae: Self-supervised graph autoencoders are generalizable learners with graph masking,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection S2gae: Self-supervised graph autoencoders are generalizable learners with graph masking,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.718146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f5ac9e16-6827-454a-add3-0f7557d3da3f · outbound

This paper cites Inductive and unsupervised representation learning on graph structured objects,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Inductive and unsupervised representation learning on graph structured objects,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.608941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d705609b-80b4-47cc-a7f4-713aaf21f22d · outbound

This paper cites Neo-gnns: Neigh- borhood overlap-aware graph neural networks for link prediction,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Neo-gnns: Neigh- borhood overlap-aware graph neural networks for link prediction,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.462820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4e329f43-60d1-4374-9ca9-52a8cba6d652 · outbound

This paper cites Neural bellman- ford networks: A general graph neural network framework for link prediction,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Neural bellman- ford networks: A general graph neural network framework for link prediction,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.366068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 714eefaa-c100-4720-8a7f-788d6b5bcefa · outbound

This paper cites Linkless link prediction via relational distillation,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Linkless link prediction via relational distillation,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.235896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b7cacd2-ebda-4189-9246-3258cec2a1af · outbound

This paper cites Learning from counterfactual links for link prediction,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Learning from counterfactual links for link prediction,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.122871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8d1d2dc6-ee57-48c4-bf21-412be63226f7 · outbound

This paper cites Self-supervised temporal graph learning with temporal and structural intensity alignment,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Self-supervised temporal graph learning with temporal and structural intensity alignment,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:46.023463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1001c8e5-9c94-4341-8da6-c6cd69a3903e · outbound

This paper cites Learning robust representations with graph denoising policy network,.

Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection Learning robust representations with graph denoising policy network,

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:49:45.867594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Reference resolution

Outbound references

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