Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T12:18:34.177210Z
Paper Citation Record · LEDGER
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs
As of 22 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2504.13266.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
52 of 52 outbound references displayed
- verified exact0
- verified fuzzy40
- unresolved12
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 550b7dff-44d6-4604-9ccf-6ea515a5be26 · outbound
This paper cites u rek, \.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs u rek, \
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.531286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 06208c25-8f0e-482c-8cba-236e9ef6c74d · outbound
This paper cites DSP: Efficient GNN Training with Multiple GPUs.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs DSP: Efficient GNN Training with Multiple GPUs
Reference 2
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4decd93c-ffd5-4eaf-8583-1a0d7b3970b2 · outbound
This paper cites Stochastic Training of Graph Convolutional Networks with Variance Reduction.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Stochastic Training of Graph Convolutional Networks with Variance Reduction
Reference 3
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2899d217-167c-452c-90dd-8b3f15aaa514 · outbound
This paper cites FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.388119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation dcf87627-0bb2-4075-a210-4cc504bbd5f6 · outbound
This paper cites On Graph Neural Networks versus Graph-Augmented MLPs.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs On Graph Neural Networks versus Graph-Augmented MLPs
Reference 5
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 827f7090-e45d-4619-bc1a-8caacedf2c1f · outbound
This paper cites Scalable Graph Neural Networks via Bidirectional Propagation.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Scalable Graph Neural Networks via Bidirectional Propagation
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.344996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6f9c1a1e-73da-49e9-ac94-8e0107b99dee · outbound
This paper cites Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.293235Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0ba5caaa-db22-4e91-8797-904fadacd0f3 · outbound
This paper cites Less is More: Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Less is More: Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.231342Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6f2b0742-346c-4f46-a3be-89495a1f22b7 · outbound
This paper cites On the Equivalence of Decoupled Graph Convolution Network and Label Propagation.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs On the Equivalence of Decoupled Graph Convolution Network and Label Propagation
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.211828Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation bc32c440-acc7-4c76-ad77-2bb078fb2560 · outbound
This paper cites SIGN: Scalable Inception Graph Neural Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs SIGN: Scalable Inception Graph Neural Networks
Reference 10
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac1af4ab-3a54-441f-9bf0-d1d7d563a6f6 · outbound
This paper cites Diffusion Improves Graph Learning.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Diffusion Improves Graph Learning
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 225d65d8-42ee-4c1f-83de-2f900fd537af · outbound
This paper cites S., Riley, P.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs S., Riley, P
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.130386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5bbc11fc-a8fa-499d-adfc-867b9d7b8688 · outbound
This paper cites Inductive Representation Learning on Large Graphs.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Inductive Representation Learning on Large Graphs
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:36.038474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 65b1e6f3-3a7c-43e2-9d36-9210086f6647 · outbound
This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Open Graph Benchmark: Datasets for Machine Learning on Graphs
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.980661Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6dcd5059-5210-4b44-ba6c-42c33fabccf8 · outbound
This paper cites GE-SpMM: General-Purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs GE-SpMM: General-Purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.919286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e22c3500-deb8-468b-b0e9-eeefe06fd58e · outbound
This paper cites WiseGraph: Optimizing GNN with Joint Workload Partition of Graph and Operations.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs WiseGraph: Optimizing GNN with Joint Workload Partition of Graph and Operations
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.905689Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0f0cbae5-8e10-49d4-b8c6-1c84dcaaea1d · outbound
This paper cites E., and Chen, J.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs E., and Chen, J
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.822391Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 54df1c73-f0d3-4fa7-96fd-0b94403c4064 · outbound
This paper cites S., Taleka, B., Ma, T., Song, X., and Hwu, W.-m.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs S., Taleka, B., Ma, T., Song, X., and Hwu, W.-m
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.809969Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation c14ce95b-d0cd-4e89-8ef1-06f51213d528 · outbound
This paper cites an unresolved cited work.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Unresolved cited work
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7655a84a-4668-4cda-a5fd-0e5f0cc89e41 · outbound
This paper cites SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.727988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 23256316-9d62-4fd5-ab1f-1b6849287e25 · outbound
This paper cites LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.715350Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d1e747fc-abe6-4828-a5d5-9048a8b5fb03 · outbound
This paper cites L., Gupta, V., Bhalerao, O., and Lim, S.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs L., Gupta, V., Bhalerao, O., and Lim, S
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.702667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6e50e3ab-1d96-49c4-b638-b57cd12e0e9e · outbound
This paper cites PaGraph: Scaling GNN Training on Large Graphs via Computation-Aware Caching.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs PaGraph: Scaling GNN Training on Large Graphs via Computation-Aware Caching
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.651266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5a54a40b-cd1a-499e-ad8a-d3812070e4dc · outbound
This paper cites BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs BGL: GPU-Efficient GNN Training by Optimizing Graph Data I/O and Preprocessing
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.535437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 767b9217-a787-481e-9ac7-0e095048bbad · outbound
This paper cites Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.523972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a1be8fbd-a344-4220-a019-950d40d2e645 · outbound
This paper cites Random Reshuffling: Simple Analysis With Vast Improvements.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Random Reshuffling: Simple Analysis With Vast Improvements
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.461909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 24122ca3-39d4-463d-aef4-5a12c0d110ee · outbound
This paper cites T., Trahay, F., Domke, J., Drozd, A., Vatai, E., Liao, J., Wahib, M., and Gerofi, B.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs T., Trahay, F., Domke, J., Drozd, A., Vatai, E., Liao, J., Wahib, M., and Gerofi, B
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.393362Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ce7c62e3-dba2-47d2-b853-f325a97ea6cc · outbound
This paper cites Revisiting Graph Neural Networks: All We Have is Low-Pass Filters.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
Reference 28
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 679681bf-49d5-4554-96b5-57d8bdc2c7dd · outbound
This paper cites an unresolved cited work.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Unresolved cited work
Reference 29
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a891e56f-9889-4a2a-b7fe-6b7e533d4e5a · outbound
This paper cites TPUGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs TPUGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs
Reference 30
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ee40437a-30ce-4695-a9bf-b31672b06722 · outbound
This paper cites an unresolved cited work.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Unresolved cited work
Reference 31
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0b49d084-0be7-4238-bcef-750d92397805 · outbound
This paper cites u tt, K., Kindermans, P.-J., Sauceda Felix, H. E., Chmiela, S., Tkatchenko, A., and M \.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs u tt, K., Kindermans, P.-J., Sauceda Felix, H. E., Chmiela, S., Tkatchenko, A., and M \
Reference 32
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 73e3678b-20ef-447b-8de8-c6b50ab27f61 · outbound
This paper cites Legion: Automatically Pushing the Envelope of Multi-GPU System for Billion-Scale GNN Training.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Legion: Automatically Pushing the Envelope of Multi-GPU System for Billion-Scale GNN Training
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:35.103010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 11b2eb63-1460-4a4d-b110-c2ed54f386ab · outbound
This paper cites Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness
Reference 34
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b908e71-e700-4145-b59f-7c0873cbc07b · outbound
This paper cites and Newburn, C.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs and Newburn, C
Reference 35
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation f99e4d19-5cff-41d9-abcb-c5eb0fdb1aeb · outbound
This paper cites Graph Clustering with Graph Neural Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Graph Clustering with Graph Neural Networks
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.983455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6c633d1c-51f7-449c-8ca7-b09e2dfc90bf · outbound
This paper cites Graph Attention Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Graph Attention Networks
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.855558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5c4a9470-802b-4e7a-960c-e263c1a49722 · outbound
This paper cites an unresolved cited work.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Unresolved cited work
Reference 38
- Resolution
- unresolved
- raw_fallback, observed 2026-08-16T12:18:34.727179Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 4bc53d4e-def9-494e-97f3-237131a06615 · outbound
This paper cites Simplifying Graph Convolutional Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Simplifying Graph Convolutional Networks
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.683956Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation de61f03a-3ea0-4f15-951c-8af3e66a855b · outbound
This paper cites Gamora: Graph Learning Based Symbolic Reasoning for Large-Scale Boolean Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Gamora: Graph Learning Based Symbolic Reasoning for Large-Scale Boolean Networks
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.626948Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation fadf6970-6c53-4764-8790-304968e55032 · outbound
This paper cites and Cong, G.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs and Cong, G
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.562439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation b0e6b9da-d762-42fa-8336-b7a5acd47da8 · outbound
This paper cites GNNLab: A Factored System for Sample-Based GNN Training Over GPUs.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs GNNLab: A Factored System for Sample-Based GNN Training Over GPUs
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.549496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 374175e6-f212-43ee-bbfa-23c4abe7740b · outbound
This paper cites L., and Leskovec, J.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs L., and Leskovec, J
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.497836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation e7b0e79d-92f3-425f-940c-a319b242f2c2 · outbound
This paper cites Hierarchical Graph Representation Learning with Differentiable Pooling.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Hierarchical Graph Representation Learning with Differentiable Pooling
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.486173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5ff191e6-2e00-4153-a87d-3cd296c43e8b · outbound
This paper cites Scalable Graph Neural Networks for Heterogeneous Graphs.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Scalable Graph Neural Networks for Heterogeneous Graphs
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:18:34.057379Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0915bcbb-6d58-4786-bd9d-931ce1088133 · outbound
This paper cites GraphSAINT: Graph Sampling Based Inductive Learning Method.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs GraphSAINT: Graph Sampling Based Inductive Learning Method
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.473340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5a8b177d-ec94-45cc-a369-1dcd5ae5b87b · outbound
This paper cites and Chen, Y.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs and Chen, Y
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.395140Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 74f60e6c-b6a5-412e-aea7-5c5d3768c122 · outbound
This paper cites Graph Attention Multi-Layer Perceptron.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Graph Attention Multi-Layer Perceptron
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.383089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 5abfd239-4079-4cac-a5e7-ec54af4b6154 · outbound
This paper cites Attributed Graph Clustering via Adaptive Graph Convolution.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Attributed Graph Clustering via Adaptive Graph Convolution
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:18:34.165793Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dc05354b-718c-44e1-8d12-acbc182a0ac4 · outbound
This paper cites and Koniusz, P.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs and Koniusz, P
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.369397Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 3d2d71bc-d314-42ce-9557-780247ae9a2d · outbound
This paper cites Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T12:18:34.356078Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 7f2e4d63-fc37-4e8d-8337-d6005ff33c58 · outbound
This paper cites write newline.
Graph Learning at Scale: Characterizing and Optimizing Pre-Propagation GNNs write newline
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:18:34.177210Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.