Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T13:33:17.033153Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2607.19086.
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 2026-08-01T13:33:17.033153Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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
67 of 67 outbound references displayed
External citation measurements
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Unresolved cited work
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Anguita, A
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Cheng, J
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Towards Transparent AI Systems: Interpreting Visual Question Answering Models
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Reference 22
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Unresolved cited work
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Unresolved cited work
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Unresolved cited work
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Advancing Multimodal Fusion on Heterogeneous Medical Data with Hybrid Geometry Attention Quantum Self-Attention Neural Networks for Text Classification
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