Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.03785.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T17:58:28.171419Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:19:45.409198Z
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 b56489ce-21dc-468a-95d8-4023fe940eb3 · inbound
Few-Shot Open-Vocabulary Remote Sensing Segmentation via Textual Inversion cites this paper.
Few-Shot Open-Vocabulary Remote Sensing Segmentation via Textual Inversion Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T02:09:22.737691Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ec65aa4-a4d6-4a24-a5f3-f818f608960a · inbound
Towards a satellite image manipulation and deepfake localization benchmark dataset cites this paper.
Towards a satellite image manipulation and deepfake localization benchmark dataset Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:19:45.415036Z
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 82785368-c16a-43c1-8bee-3d052fec6166 · inbound
ELMZip: Onboard Satellite Image Compression via Extreme Learning Machines for Efficient Downlink cites this paper.
ELMZip: Onboard Satellite Image Compression via Extreme Learning Machines for Efficient Downlink Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:58:28.171419Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.