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Paper Citation Record · LEDGER

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025)

As of 15 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2509.06993.

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

pith.paper-citation-record.v1
2509.06993 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:17:02.886924Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

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

9 of 9 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac77a0e9-32d7-4f9a-a540-dac8d2677d04 · outbound

This paper cites write newline.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T11:17:02.062423Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:17:02.062423Z digest=sha256:5b9e1686adfd83fd5f06606ab6b9980c295d55600ee7541a35576bfcce14cd5e

Observation 22a3c2c6-ad61-43f4-ad31-821ed1d8a8dd · outbound

This paper cites Graph convolution for semi-supervised classification: Improved linear separability and out-of-distribution generalization, 2022.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Graph convolution for semi-supervised classification: Improved linear separability and out-of-distribution generalization, 2022

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:17:04.030223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-05T11:17:02.133534Z digest=sha256:f1e77e9f4cad8c7bfb647f6db6be178c664176e6c6a8a16f0db7d461733d11a6

Observation 3c523e38-21cf-47eb-971a-03370c445ccd · outbound

This paper cites Ssl4eo-s12 v1.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Ssl4eo-s12 v1

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T11:17:02.233037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:17:02.233037Z digest=sha256:b3a123aa988df557f79cbafbe4821c4ce8594e1655dc5a9ef680612222643e32

Observation b0b78407-b18e-4856-8580-0d640a30fe44 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Emerging properties in self-supervised vision transformers

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:17:03.864103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-05T11:17:02.373582Z digest=sha256:d32dd143753d92edaa6dda432c218a455421f423a793a396be837b5c776f56a1

Observation 6e154d7d-ae0c-46b0-a5f9-a04d0906b339 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Learning transferable visual models from natural language supervision

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:17:03.691107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-05T11:17:02.475928Z digest=sha256:8cea28039611f11a22883af37beb17ba75dcf57f3eae4afa8d28f2d8e6d87e37

Observation 179ceab5-973c-49b3-ac9d-9dee73f52c5e · outbound

This paper cites Cluster quality analysis using silhouette score.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Cluster quality analysis using silhouette score

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:17:03.537566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-05T11:17:02.586492Z digest=sha256:27a261e1b3e4758ed5c38ceae180561ede8a70019eec792e05fa34e5d667083d

Observation 43c5d39a-9ba9-478a-b853-2856537b6c0a · outbound

This paper cites Fast approximate truncated svd.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Fast approximate truncated svd

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:17:03.368055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-05T11:17:02.684564Z digest=sha256:84c60f013ca3b2de328a484d6671fcd79217156ec9da867bec4a3b9b9307bd2f

Observation 5b60ff6d-f55e-4687-a917-a7dfc673d3ac · outbound

This paper cites TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T11:17:02.780814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T11:17:02.780814Z digest=sha256:34759492d3380c72271a9bf5f70886d864de36f362f2758d24c463ff77bf6e76

Observation 28b7b885-5d96-429f-a80d-110d4319eaa6 · outbound

This paper cites Rs5m and georsclip: A large scale vision-language dataset and a large vision-language model for remote sensing.

Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Rs5m and georsclip: A large scale vision-language dataset and a large vision-language model for remote sensing

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:17:03.162092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-05T11:17:02.886924Z digest=sha256:08fd66ca46dbb70f9eaef26ff94327187a17878b2f70b23a1b2a62db2c8e3ca7

Pith citing papers

No inbound Pith citation observations are available.