Paper Citation Record · LEDGER

Large Language Models for Captioning and Retrieving Remote Sensing Images

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.06475.

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

pith.paper-citation-record.v1
2402.06475 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:21:13.286686Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T10:26:01.320673Z

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 19bc2291-6fe5-4971-a707-3496f8f536d9 · inbound

GeoMag: A Vision-Language Model for Pixel-level Fine-Grained Remote Sensing Image Parsing cites this paper.

GeoMag: A Vision-Language Model for Pixel-level Fine-Grained Remote Sensing Image Parsing Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:13.286686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76ec8b87-7db7-47eb-8f3b-52265e924568 · inbound

Semantic-Geometric Dual Compression: Training-Free Visual Token Reduction for Ultra-High-Resolution Remote Sensing Understanding cites this paper.

Semantic-Geometric Dual Compression: Training-Free Visual Token Reduction for Ultra-High-Resolution Remote Sensing Understanding Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:26:01.323487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9055eae1-c298-4208-b2ac-8dd227ea2830 · inbound

WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding cites this paper.

WeaveEarth: Structured Evidence Construction and Reasoning for Training-Free UHR Remote Sensing Understanding Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-14T14:09:30.395518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee5f5c56-7676-48be-be54-7f353920ff0c · inbound

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose? cites this paper.

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose? Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-01T10:20:58.622751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.