Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:58:37.254075Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2411.14796.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:58:37.254075Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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
58 of 58 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ce46e38f-8d44-4b1d-afc9-6b967e74481b · outbound
Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections Skeleton-based action recognition using sparse spatio- temporal gcn with edge effective resistance
Reference 1
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Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections Hypergraph convolution and hypergraph attention
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Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections Channel-wise topology refinement graph convolution for skeleton-based action recognition
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Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections Decoupling gcn with dropgraph module for skeleton-based action recognition
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Observation afa768d3-e061-4eba-ad76-1f367f1f02a2 · outbound
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Observation b57dbf44-6294-400e-99fb-9f7423b38cbf · outbound
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Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections Ddgcn: A dynamic directed graph convolutional network for action recognition
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Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections Hierarchically decomposed graph convolutional net- works for skeleton-based action recognition
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Observation fab1bf13-0992-4447-adf6-716f30e2c322 · outbound
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Observation 68ee3035-ebb7-452d-85d1-5173853c95f1 · outbound
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Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections A skeleton-based approach for campus violence detection
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No inbound Pith citation observations are available.