Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.08413.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T10:54:52.480114Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T21:51:16.168040Z
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 a89e029c-6606-4426-a05b-8b9cc4a952e2 · inbound
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities cites this paper.
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward
Reference 1979
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T21:51:16.173416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e3ee8f62-3e84-487d-8d26-705614e80a6e · inbound
Dense Air Pollution Estimation from Sparse in-situ Measurements and Satellite Data cites this paper.
Dense Air Pollution Estimation from Sparse in-situ Measurements and Satellite Data Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:54:52.480114Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 704bc86d-0555-4c88-8396-21c9ac51348f · inbound
Summarize First, Download Later: Onboard VLMs for Bandwidth-Efficient Earth Observation cites this paper.
Summarize First, Download Later: Onboard VLMs for Bandwidth-Efficient Earth Observation Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:39:50.679131Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.