Paper Citation Record · LEDGER

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data

As of 22 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2504.18770.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2504.18770 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:14:09.685545Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T08:50:49.531565Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:29:44.835051Z

Reference resolution

17 of 17 outbound references displayed

verified exact0
verified fuzzy1
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f12a503c-168f-4462-b8c4-fe4902e39dda · outbound

This paper cites OmniSat: Self-Supervised Modality Fusion for Earth Observation.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data OmniSat: Self-Supervised Modality Fusion for Earth Observation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.620366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 746313b4-94b6-43bc-9bc0-efd80618bf16 · outbound

This paper cites Unsupervised Learning of Visual Features by Contrasting Cluster Assignments.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Unsupervised Learning of Visual Features by Contrasting Cluster Assignments

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.625073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 768ce829-a6f5-49e2-9f52-6da71453760f · outbound

This paper cites A Simple Framework for Contrastive Learning of Visual Representations.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data A Simple Framework for Contrastive Learning of Visual Representations

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.629340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1302baf-9c07-4999-aa36-12decd00e407 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Imagenet: A large-scale hierarchical image database

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.633307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 245e91bc-1a10-450b-be42-ae02109b2743 · outbound

This paper cites Fujita, Z.H.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Fujita, Z.H

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:14:09.944358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 47308797-5eed-47b7-8bcc-105fdebe1a4a · outbound

This paper cites Masked Autoencoders Are Scalable Vision Learners.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Masked Autoencoders Are Scalable Vision Learners

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.640622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fac91c54-b6aa-40e3-9152-bded6442544e · outbound

This paper cites Foundation Models for Generalist Geospatial Artificial Intelligence.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Foundation Models for Generalist Geospatial Artificial Intelligence

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.644948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2c1493f-da27-435b-82c5-6aa9e531e0b2 · outbound

This paper cites Scaling Laws for Neural Language Models.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Scaling Laws for Neural Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.648581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b01f79b2-73dc-4bcb-bdc5-df0c0e7c5ce6 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Adam: A Method for Stochastic Optimization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.652569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd60a76b-f41a-4933-a838-86757353ace8 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Imagenet classification with deep convolutional neural networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.656226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 462f70ad-e4a0-4835-b204-8a4f6817ee4b · outbound

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

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.660017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0731bce4-0cf8-4e30-bbf8-4904085aec44 · outbound

This paper cites Attention Is All You Need.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Attention Is All You Need

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.663798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 805a6b02-6b29-4d9e-b8d7-319a5e6e6875 · outbound

This paper cites On Layer Normalization in the Transformer Architecture.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data On Layer Normalization in the Transformer Architecture

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.667918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1592b522-a1d0-4dd9-bfde-20857c446a7c · outbound

This paper cites write newline.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data write newline

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.672611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f0773a2-fa82-400c-ba69-dbcd2eee7f2c · outbound

This paper cites @esa (Ref.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data @esa (Ref

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.677059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ae8a2a0-9fe8-4b10-8526-9bfb7f207044 · outbound

This paper cites an unresolved cited work.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Unresolved cited work

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.681221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af753421-a0a0-4dc0-a6c1-08b6c80e0230 · outbound

This paper cites an unresolved cited work.

PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T10:14:09.685545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 746ed7b2-4dd7-44f0-9af5-4c7aa06eb45f · inbound

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation cites this paper.

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation PyViT-FUSE: A Foundation Model for Multi-Sensor Earth Observation Data

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:29:44.836744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.