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Paper Citation Record · LEDGER

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2508.09453.

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pith.paper-citation-record.v1
2508.09453 v1

Coverage vector

measured 34 of 34 reference resolution

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measured 34 of 34 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation 8f6dbae6-b3bf-46bc-a1cb-3a598351ca53 · outbound

This paper cites The enmap imaging spectroscopy mission towards operations,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss The enmap imaging spectroscopy mission towards operations,

Reference 1

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Observation b64d020c-330a-4f25-8de5-242bc018f01a · outbound

This paper cites Prisma: The italian hyperspectral mission,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Prisma: The italian hyperspectral mission,

Reference 2

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Observation 36af45d0-44ec-48f1-ba85-377e02ca2a38 · outbound

This paper cites Planet imagery and data,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Planet imagery and data,

Reference 3

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Observation 4f0c0ddd-e1d7-4530-a148-932f76cd80ed · outbound

This paper cites Spectralgpt: Spectral remote sensing foun- dation model,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Spectralgpt: Spectral remote sensing foun- dation model,

Reference 4

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Observation d489d418-40f9-4107-af90-079be64c8249 · outbound

This paper cites Remoteclip: A vision language foundation model for remote sensing,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Remoteclip: A vision language foundation model for remote sensing,

Reference 5

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Observation 908acb21-4902-4df6-abd4-fd9b4e3323a4 · outbound

This paper cites Ringmo: A remote sensing foundation model with masked image modeling,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Ringmo: A remote sensing foundation model with masked image modeling,

Reference 6

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Observation 8372e7be-307a-446e-99ad-df707d523dd8 · outbound

This paper cites Foundation models for generalist geospatial artificial intelligence,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Foundation models for generalist geospatial artificial intelligence,

Reference 7

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Observation 7b22a683-e7ef-456e-8315-bd7a6c77891a · outbound

This paper cites Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery,

Reference 8

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Observation c03622ba-c9bd-443f-a16e-852849c15e3c · outbound

This paper cites Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning

Reference 9

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Observation 5fe07cd7-3f32-4b1e-aaf7-af1c7893f23a · outbound

This paper cites The harmonized landsat and sentinel-2 surface reflectance data set,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss The harmonized landsat and sentinel-2 surface reflectance data set,

Reference 10

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Observation b41397f3-f65e-4412-aa4f-3332051cdcdb · outbound

This paper cites Knowledge distillation: A survey,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Knowledge distillation: A survey,

Reference 11

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Observation 07a2b8e4-014b-48cb-b5f0-21f55a729639 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Distilling the Knowledge in a Neural Network

Reference 12

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Observation 6012d2eb-3f6d-4843-bbc4-823476aedd7b · outbound

This paper cites Knowledge distillation with feature self attention,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Knowledge distillation with feature self attention,

Reference 13

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Observation ab9830e9-e72a-46fe-b03c-90b9e642246b · outbound

This paper cites Efficient object detection in optical remote sensing imagery via attention-based feature distillation,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Efficient object detection in optical remote sensing imagery via attention-based feature distillation,

Reference 14

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Observation a1e6a5cf-acd5-4142-960a-944a06b2c55b · outbound

This paper cites Self-supervised learning with adaptive distillation for hyperspectral image classification,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Self-supervised learning with adaptive distillation for hyperspectral image classification,

Reference 15

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Observation a79e5632-34a9-498c-af35-149c99ffbb02 · outbound

This paper cites A novel knowledge distillation method for self-supervised hyperspectral image classification,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss A novel knowledge distillation method for self-supervised hyperspectral image classification,

Reference 16

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Observation 7398e00e-117f-4e63-9075-736c286b91b9 · outbound

This paper cites Siamohot: A lightweight dual siamese network for onboard hyperspectral object tracking via joint spatial-spectral knowledge distillation,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Siamohot: A lightweight dual siamese network for onboard hyperspectral object tracking via joint spatial-spectral knowledge distillation,

Reference 17

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Observation 40899f6d-248e-431b-8316-924323761e6c · outbound

This paper cites Random shuffling data for hyperspectral image classification with siamese and knowledge distillation network,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Random shuffling data for hyperspectral image classification with siamese and knowledge distillation network,

Reference 18

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Observation a6a82141-6f2a-4e1f-9642-aa0e0b9eaf8e · outbound

This paper cites Self-supervised learning with adaptive distillation for hyperspectral image classification,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Self-supervised learning with adaptive distillation for hyperspectral image classification,

Reference 19

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Observation d52f01ba-9eea-4c01-b638-067a548e103c · outbound

This paper cites Multimodal online knowledge distillation framework for land use/cover classification using full or missing modalities,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Multimodal online knowledge distillation framework for land use/cover classification using full or missing modalities,

Reference 20

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Observation dffe6497-ccf5-4456-a783-01a9d3a11da9 · outbound

This paper cites Strm-kd: Semantic topological relation matching knowledge distillation model for smart agriculture apple leaf disease recognition,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Strm-kd: Semantic topological relation matching knowledge distillation model for smart agriculture apple leaf disease recognition,

Reference 21

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Source-reported events for the cited work

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Observation bd59d16e-c062-4f5d-8b68-6f3dfdace938 · outbound

This paper cites A survey on computational spectral reconstruction methods from rgb to hyperspectral imaging,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss A survey on computational spectral reconstruction methods from rgb to hyperspectral imaging,

Reference 22

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Observation 040ec6e4-86a7-4795-9b6d-3e37e61573b0 · outbound

This paper cites Lambertian reflectance,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Lambertian reflectance,

Reference 23

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Observation 371a6596-4e39-4665-87be-4011246a08eb · outbound

This paper cites On information and sufficiency,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss On information and sufficiency,

Reference 24

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Observation 0275c102-3d9d-445c-857e-d63e1a944c29 · outbound

This paper cites Divergence measures based on the shannon entropy.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Divergence measures based on the shannon entropy

Reference 25

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Observation c4a0d0ea-5ade-4dbe-a9f9-32840c2760b6 · outbound

This paper cites Theory of communication. part 1: the analysis of information. j inst electr eng-part iii: Radio commun eng 93 (26): 429–441,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Theory of communication. part 1: the analysis of information. j inst electr eng-part iii: Radio commun eng 93 (26): 429–441,

Reference 26

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Observation 29e1ee6f-5165-43c5-a762-67f8024058f1 · outbound

This paper cites Meyer, Wavelets and operators: volume 1.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Meyer, Wavelets and operators: volume 1

Reference 27

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Source-reported events for the cited work

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Observation f78ff688-f4e3-4182-9329-a29f440cad4e · outbound

This paper cites Gabor filter-based edge detection,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Gabor filter-based edge detection,

Reference 28

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Source-reported events for the cited work

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Observation cca607cf-5d12-4e0e-80bc-9be0b9a3de0f · outbound

This paper cites Image quality assess- ment: from error visibility to structural similarity,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Image quality assess- ment: from error visibility to structural similarity,

Reference 29

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Source-reported events for the cited work

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Observation 780f9d88-a272-402f-bef4-43ee6483ba72 · outbound

This paper cites A perceptually relevant mse-based image quality metric,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss A perceptually relevant mse-based image quality metric,

Reference 30

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Source-reported events for the cited work

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Observation 25670966-1d65-4e17-9ccd-5f39bd278310 · outbound

This paper cites Structural texture similarity metrics for image analysis and retrieval,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Structural texture similarity metrics for image analysis and retrieval,

Reference 31

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Source-reported events for the cited work

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Observation 86f1b2d6-d95e-4605-abf9-ba151330fe58 · outbound

This paper cites Annual nlcd (national land cover database)—the next generation of land cover mapping,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Annual nlcd (national land cover database)—the next generation of land cover mapping,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:05:39.092915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T21:05:38.441667Z digest=sha256:6013cf77e30ff2bdcfcb26e26babea88c31204bf4c0bf28270bc2a44c4e2d6f1

Observation 4e19dab5-e981-4b17-9dc0-ab1ab0dee931 · outbound

This paper cites Examining the characteristics of the cropland data layer in the context of estimating land cover change,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Examining the characteristics of the cropland data layer in the context of estimating land cover change,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:05:38.926129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T21:05:38.520748Z digest=sha256:0874d2c7a09453f556da215f4504e095f017c1f9ca2c76e79708d4fdda160df5

Observation 8f5fd0fd-cf8c-4f2f-acdd-273ab95ed911 · outbound

This paper cites Gridded national soil survey geographic (gnatsgo) database for the conterminous united states,.

HyperKD: Distilling Cross-Spectral Knowledge in Masked Autoencoders via Inverse Domain Shift with Spatial-Aware Masking and Specialized Loss Gridded national soil survey geographic (gnatsgo) database for the conterminous united states,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T21:05:38.788087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-05T21:05:38.585896Z digest=sha256:9400b800a6b4cd9a0f9d7469f008b684e92f9895e1dbd95835d02277e13e20b6

Pith citing papers

No inbound Pith citation observations are available.