SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search | Paper Citation Record

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This paper cites Representation learning on graphs: Methods and applications,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Representation learning on graphs: Methods and applications,

Reference 1

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Observation e932a8d5-127d-4f5f-aaf8-f6ca0e8a3a05 · outbound

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

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Semi-supervised classification with graph convolutional networks,

Reference 2

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This paper cites Graph attention networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graph attention networks,

Reference 3

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Observation d05627a4-1628-43e2-beff-40e705a1dc68 · outbound

This paper cites Inductive representation learning on large graphs,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Inductive representation learning on large graphs,

Reference 4

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Observation 331b93ae-7fdc-4b24-b433-d4c7e5214672 · outbound

This paper cites How powerful are spectral graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search How powerful are spectral graph neural networks,

Reference 5

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Observation 2de9b83a-4e5f-48ca-84f1-dc54916740fc · outbound

This paper cites Graph neural network for traffic forecasting: A survey,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graph neural network for traffic forecasting: A survey,

Reference 6

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Observation 0999a541-dce0-4e1e-9a6d-8ae40455a364 · outbound

This paper cites Combinatorial optimization and reasoning with graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Combinatorial optimization and reasoning with graph neural networks,

Reference 7

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This paper cites an unresolved cited work.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Unresolved cited work

Reference 8

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Observation 86335d05-fb05-4d6e-a68c-b24516c929c0 · outbound

This paper cites Graph neural networks in recommender systems: A survey,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graph neural networks in recommender systems: A survey,

Reference 9

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Observation cfecc90d-5715-4e7f-9a08-a9d5238542f0 · outbound

This paper cites Hgnn+: General hypergraph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Hgnn+: General hypergraph neural networks,

Reference 10

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Observation 088fa2ae-de90-4e6f-b1d3-821757820f50 · outbound

This paper cites Deep constraint- based propagation in graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Deep constraint- based propagation in graph neural networks,

Reference 11

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Observation 44c26598-ea31-45b2-b5ea-867411b7e47b · outbound

This paper cites Unsupervised graph embedding via adaptive graph learning,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Unsupervised graph embedding via adaptive graph learning,

Reference 12

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Observation 934dcd56-2812-43ad-8aa0-59b2989b9a99 · outbound

This paper cites Automated machine learning on graphs: A survey,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Automated machine learning on graphs: A survey,

Reference 13

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Observation a59d8d96-7ac6-4fda-86ce-43963084f608 · outbound

This paper cites Graph neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graph neural architecture search,

Reference 14

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Observation 7feee5fd-e3e5-4b4a-b2d3-c19875254441 · outbound

This paper cites Graph differentiable architec- ture search with structure learning,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graph differentiable architec- ture search with structure learning,

Reference 15

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Observation cdd4420e-bb4f-474d-9a89-4b7a50e67fa6 · outbound

This paper cites Auto-GNN: Neural Architecture Search of Graph Neural Networks.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Auto-GNN: Neural Architecture Search of Graph Neural Networks

Reference 16

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Observation e20da976-5e0f-4ac3-b8e9-32756338ab70 · outbound

This paper cites Search to aggregate neighborhood for graph neural network,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Search to aggregate neighborhood for graph neural network,

Reference 17

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Observation 5e5f0106-9dc2-436b-8ab3-1ff247b44b83 · outbound

This paper cites Psp: Progressive space pruning for efficient graph neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Psp: Progressive space pruning for efficient graph neural architecture search,

Reference 18

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Observation 57a0af62-b0b3-4d19-b61a-a417014cd522 · outbound

This paper cites Large-scale graph neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Large-scale graph neural architecture search,

Reference 19

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Observation 43c7f746-19f7-4397-8021-966286c61497 · outbound

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

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Open graph benchmark: Datasets for machine learning on graphs,

Reference 20

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Observation 82dea311-7ce1-4cf9-a1cc-6f8293769b5e · outbound

This paper cites Redundancy- free computation for graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Redundancy- free computation for graph neural networks,

Reference 21

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Observation b5724775-90f0-42e9-8a5b-c32e1ad24852 · outbound

This paper cites Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks,

Reference 22

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This paper cites Graph- saint: Graph sampling based inductive learning method,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graph- saint: Graph sampling based inductive learning method,

Reference 23

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Observation 539f3fdb-9169-4934-aa9e-ff068efad9b1 · outbound

This paper cites Layer-neighbor sampling — defusing neighborhood explosion in gnns,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Layer-neighbor sampling — defusing neighborhood explosion in gnns,

Reference 24

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Observation 83f9f50d-69b6-44aa-9d84-9489640a3289 · outbound

This paper cites Efficient graph neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Efficient graph neural architecture search,

Reference 25

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Observation 632c5589-e825-4c31-aebb-753caf31760b · outbound

This paper cites Neural architecture search: A survey,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Neural architecture search: A survey,

Reference 26

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Observation fbc4c0f1-135a-4bcc-848a-447a282400c6 · outbound

This paper cites Automl: A survey of the state-of-the-art,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Automl: A survey of the state-of-the-art,

Reference 27

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Observation c317398d-50e2-4f95-a2cd-0e9e62c8ee95 · outbound

This paper cites A comprehensive survey of neural architecture search: Challenges and solutions,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search A comprehensive survey of neural architecture search: Challenges and solutions,

Reference 28

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Observation ba955904-71c7-467a-af90-7b0f0f5bc647 · outbound

This paper cites Understanding and accelerating neural architecture search with training-free and theory-grounded metrics,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Understanding and accelerating neural architecture search with training-free and theory-grounded metrics,

Reference 29

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Observation fe8a2243-1a5e-4432-b364-1973af9d97cd · outbound

This paper cites Migo-nas: Towards fast and generalizable neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Migo-nas: Towards fast and generalizable neural architecture search,

Reference 30

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Observation 6f988acb-09e5-4fb0-b66f-b42f9abde248 · outbound

This paper cites You only search once: Single shot neural architecture search via direct sparse optimization,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search You only search once: Single shot neural architecture search via direct sparse optimization,

Reference 31

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Observation b94f1779-7e41-43c3-8735-7b86b87eae18 · outbound

This paper cites Mngnas: distilling adaptive combination of multiple searched networks for one- shot neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Mngnas: distilling adaptive combination of multiple searched networks for one- shot neural architecture search,

Reference 32

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Observation 69e70369-23f2-4f82-ad27-7dd2cec300d2 · outbound

This paper cites Sample-efficient neural architecture search by learning actions for monte carlo tree search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Sample-efficient neural architecture search by learning actions for monte carlo tree search,

Reference 33

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Observation c3809437-7ed9-4f7d-8bb0-8ee14204a913 · outbound

This paper cites Darts: Differentiable architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Darts: Differentiable architecture search,

Reference 34

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Observation 3c0a171f-d234-4895-aeb0-607738018932 · outbound

This paper cites Nas-fpn: Learning scalable fea- ture pyramid architecture for object detection,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Nas-fpn: Learning scalable fea- ture pyramid architecture for object detection,

Reference 35

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Observation 4a916b74-f332-4d59-a963-43d9a94468ea · outbound

This paper cites Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation,

Reference 36

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Observation 727deb64-48fc-42bc-9406-26d2e70694a5 · outbound

This paper cites Alphagan: Fully differ- entiable architecture search for generative adversarial networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Alphagan: Fully differ- entiable architecture search for generative adversarial networks,

Reference 37

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Observation b4b7a0e8-ab2d-449d-88b9-877bafed0321 · outbound

This paper cites Nas-ctr: Efficient neural architecture search for click-through rate prediction,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Nas-ctr: Efficient neural architecture search for click-through rate prediction,

Reference 38

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Observation 14808b30-54eb-45b8-aaac-3f8c19c75a21 · outbound

This paper cites Autogsr: Neural architecture search for graph-based session recommendation,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Autogsr: Neural architecture search for graph-based session recommendation,

Reference 39

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Observation 4eaa1f96-0a12-4352-9e2b-94376fc7a328 · outbound

This paper cites Neural architecture search with reinforcement learning,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Neural architecture search with reinforcement learning,

Reference 40

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Observation 9e3bb18c-8bc4-4f40-a19c-fe8016316c18 · outbound

This paper cites Efficient neural architecture search via parameters sharing,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Efficient neural architecture search via parameters sharing,

Reference 41

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Observation 8764b8e6-6d9c-44bd-97ea-e8a0a1c425d0 · outbound

This paper cites Learning transferable architectures for scalable image recognition,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Learning transferable architectures for scalable image recognition,

Reference 42

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Observation 4e399c1f-25ab-48bc-97ca-cce6e17fabc5 · outbound

This paper cites Hierarchical representations for efficient architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Hierarchical representations for efficient architecture search,

Reference 43

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Observation b6102858-8091-42ff-958d-d30b1d762763 · outbound

This paper cites Regularized evolution for image classifier architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Regularized evolution for image classifier architecture search,

Reference 44

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Observation 900a6b03-d9a8-48a2-933d-c4d9f7cc5d8f · outbound

This paper cites Efficient neural architecture search via proximal iterations.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Efficient neural architecture search via proximal iterations

Reference 45

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Observation ec8db4c9-7617-420e-8923-f888a2fa522c · outbound

This paper cites Rethinking architecture selection in differentiable nas,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Rethinking architecture selection in differentiable nas,

Reference 46

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Observation 4f4cd7ea-d548-4643-9907-e6ca8d297fe8 · outbound

This paper cites Operation-level early stopping for robustifying differentiable nas,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Operation-level early stopping for robustifying differentiable nas,

Reference 47

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Observation 4357f92a-eec1-4b31-90fc-825d10e8905e · outbound

This paper cites Cyclic differentiable architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Cyclic differentiable architecture search,

Reference 48

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Observation 8458dee3-fb28-4d61-bfd4-2069d123e675 · outbound

This paper cites Zeronas: Differentiable generative adversarial networks search for zero- shot learning,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Zeronas: Differentiable generative adversarial networks search for zero- shot learning,

Reference 49

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Observation dc2e3824-a1b6-471b-9eb1-ef1143a13da3 · outbound

This paper cites High performance graph convolutionai networks with applications in testability analysis,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search High performance graph convolutionai networks with applications in testability analysis,

Reference 50

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Observation 592ff4d8-6ccb-4461-9466-8d6ab6757086 · outbound

This paper cites Genetic-gnn: Evolutionary architecture search for graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Genetic-gnn: Evolutionary architecture search for graph neural networks,

Reference 51

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Observation e26bd8d9-5c02-4874-ba08-e8a27a23bcc6 · outbound

This paper cites Autoattend: Automated attention rep- resentation search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Autoattend: Automated attention rep- resentation search,

Reference 52

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 69a0bade-d2ab-462d-afb1-7c49f5d1965f · outbound

This paper cites Simplifying Architecture Search for Graph Neural Network.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Simplifying Architecture Search for Graph Neural Network

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T23:48:48.621496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d977b38a-dafb-4c3d-83a1-f8ec85c10d13 · outbound

This paper cites One-shot graph neural architec- ture search with dynamic search space,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search One-shot graph neural architec- ture search with dynamic search space,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:49.064627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fb4f823f-4389-47bb-a688-f6b913f565c3 · outbound

This paper cites Meta-gnas: Meta-reinforcement learning for graph neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Meta-gnas: Meta-reinforcement learning for graph neural architecture search,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:49.055196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation be132a96-12e6-4eaf-bba5-fe606f6c86ef · outbound

This paper cites Hgnas++: Efficient architecture search for heterogeneous graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Hgnas++: Efficient architecture search for heterogeneous graph neural networks,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:49.045377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d839ffbc-4b3b-453f-97d3-2f1a16ad97e2 · outbound

This paper cites Li and I.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Li and I

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:49.033647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 05097534-1799-42a1-a486-a68753f0e40a · outbound

This paper cites Graphpas: Parallel architecture search for graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graphpas: Parallel architecture search for graph neural networks,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:49.022253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f9a35ec4-fae3-4d91-9f2b-808ba5910f46 · outbound

This paper cites Sgas: Sequential greedy architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Sgas: Sequential greedy architecture search,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:49.011442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 01e8ecc1-c726-4a85-8925-af6a8ac53d8d · outbound

This paper cites Autostg: Neural architecture search for predictions of spatio-temporal graph,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Autostg: Neural architecture search for predictions of spatio-temporal graph,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:49.001169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a3784885-00e1-457a-ab6f-d7206d1357e0 · outbound

This paper cites Do not train it: A linear neural architecture search of graph neural networks,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Do not train it: A linear neural architecture search of graph neural networks,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.990807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bf4fd45e-615d-41bc-80b9-3237c77a5571 · outbound

This paper cites Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T23:48:48.651192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34aec9a9-9524-41ac-922e-aaa2a1c83ad0 · outbound

This paper cites Pasca: A graph neural architecture search system under the scalable paradigm,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Pasca: A graph neural architecture search system under the scalable paradigm,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.980178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c671cb10-6dd0-45f9-bfd0-d97047502ef3 · outbound

This paper cites Efficient and explainable graph neural architecture search via monte-carlo tree search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Efficient and explainable graph neural architecture search via monte-carlo tree search,

Reference 64

Resolution: verified exact; raw_fallback, observed 2026-08-11T23:48:48.839114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5d968288-06dc-47bc-9abb-1463bfeea242 · outbound

This paper cites GraphPNAS: Learning prob- abilistic graph generators for neural architecture search,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search GraphPNAS: Learning prob- abilistic graph generators for neural architecture search,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.969721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 30eb079f-2ea0-4bf7-92c4-cd1cd2509d40 · outbound

This paper cites Graph neural networks with convolutional arma filters,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Graph neural networks with convolutional arma filters,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.959438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0ccb1f48-8e14-4ad9-9a7d-969d6df1fe8c · outbound

This paper cites Predict then propagate: Graph neural networks meet personalized pagerank,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Predict then propagate: Graph neural networks meet personalized pagerank,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.949259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b995d7bc-2ea2-4159-abe4-924c69e5526a · outbound

This paper cites Puka, Kendall’s Tau.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Puka, Kendall’s Tau

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.939324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2523eb39-3c1d-4c09-be9b-05a81fd881ad · outbound

This paper cites A weighted kendall’s tau statistic,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search A weighted kendall’s tau statistic,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.926889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 430374f2-90b8-4072-b00f-a7bc06cb6c8c · outbound

This paper cites Toward unsupervised outlier model selection,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Toward unsupervised outlier model selection,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.915428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8ac6c518-3acc-4249-aaf7-e265caf5cff6 · outbound

This paper cites Microsoft academic graph: When experts are not enough,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Microsoft academic graph: When experts are not enough,

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.904018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b3779a8b-6afa-4e48-8af5-688071ad45c5 · outbound

This paper cites Auto- gnas: A parallel graph neural architecture search framework,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Auto- gnas: A parallel graph neural architecture search framework,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.892619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f396a4d6-39d7-4e5b-a12a-c113caaf6114 · outbound

This paper cites node2vec: Scalable feature learning for net- works,.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search node2vec: Scalable feature learning for net- works,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:48:48.881102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a8eb2ffb-ac9f-4dd6-9be7-eae9c6623b50 · outbound

This paper cites Bag of Tricks for Node Classification with Graph Neural Networks.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Bag of Tricks for Node Classification with Graph Neural Networks

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T23:48:48.692323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8802bfe-895e-410c-b944-2d9294d818b5 · outbound

This paper cites Combining Label Propagation and Simple Models Out-performs Graph Neural Networks.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Combining Label Propagation and Simple Models Out-performs Graph Neural Networks

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T23:48:48.695984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27561f75-16a1-4c54-ae5e-a2b98d89eb7c · outbound

This paper cites Distilling the Knowledge in a Neural Network.

SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture Search Distilling the Knowledge in a Neural Network

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-11T23:48:48.699904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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