Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T04:51:09.791522Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 2 inbound Pith citation observations for arXiv:2501.18637.
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 2026-08-10T04:51:09.791522Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T08:11:24.869074Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
57 of 57 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Observation 754a38a9-4768-4225-92d2-a48a9d3b35ee · outbound
Reference 1
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Reference 2
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Observation 0d1c37c8-86e5-48fe-b2c5-119cd496dae6 · outbound
Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Reference 4
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 5
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 8
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Hall, Variation of hardness of metals with grain size, Nature 173 (4411) (1954) 948–949
Reference 9
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 12
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers SR-CLD: Spatially Resolved Chord Length Distributions for Statistical Description and Visualization of Non-uniform Microstructures
Reference 16
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 17
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 18
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 20
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 26
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 27
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers DINOv2: Learning Robust Visual Features without Supervision
Reference 30
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Observation 80426454-9b1c-498c-a37f-52753d95b37a · outbound
Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Van der Maaten, G
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers E92-17, Standard test methods for vickers hardness and knoop hardness of metallic materials (2017)
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Torquato, et al., Random heterogeneous materials: microstructure and macroscopic properties, Vol
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Unresolved cited work
Reference 56
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Machine learning of microstructure--property relationships in materials leveraging microstructure representation from foundational vision transformers Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning
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