Paper Citation Record · LEDGER

A Billion-scale Foundation Model for Remote Sensing Images

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2304.05215.

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

pith.paper-citation-record.v1
2304.05215 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:42:47.270459Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:16:39.431991Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c6fb755c-44ba-4213-a01e-bd79ed96afa9 · inbound

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models cites this paper.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models A Billion-scale Foundation Model for Remote Sensing Images

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:47.270459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b2eb232-cbb3-4ddf-96b2-24e4698f7aed · inbound

Distributed Cross-Channel Hierarchical Aggregation for Foundation Models cites this paper.

Distributed Cross-Channel Hierarchical Aggregation for Foundation Models A Billion-scale Foundation Model for Remote Sensing Images

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T22:29:59.371089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0374c22-d858-40c9-90ab-8fbde5a0086e · inbound

CGEarthEye:A High-Resolution Remote Sensing Vision Foundation Model Based on the Jilin-1 Satellite Constellation cites this paper.

CGEarthEye:A High-Resolution Remote Sensing Vision Foundation Model Based on the Jilin-1 Satellite Constellation A Billion-scale Foundation Model for Remote Sensing Images

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T21:23:14.733114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48319c15-b5a1-4410-99aa-9c0046f4f2d0 · inbound

SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing cites this paper.

SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing A Billion-scale Foundation Model for Remote Sensing Images

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T16:21:13.935816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff9d61d8-e25c-4ea8-b1f9-dc8c070e7ebd · inbound

Artificial intelligence for methane detection: from continuous monitoring to verified mitigation cites this paper.

Artificial intelligence for methane detection: from continuous monitoring to verified mitigation A Billion-scale Foundation Model for Remote Sensing Images

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:19:04.574773Z

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 97f27891-fdd1-4d3e-9af8-031fa12002fe · inbound

SLIP-RS: Structured-Attribute Language-Image Pre-Training for Remote Sensing Object Detection cites this paper.

SLIP-RS: Structured-Attribute Language-Image Pre-Training for Remote Sensing Object Detection A Billion-scale Foundation Model for Remote Sensing Images

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:16:39.434448Z

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.