Paper Citation Record · LEDGER

Large Language Models for Captioning and Retrieving Remote Sensing Images

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 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 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:15:40.738353Z

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 f13c5ab6-8c04-4339-9d0c-2056a4f7e859 · inbound

Large Vision-Language Models for Remote Sensing Visual Question Answering cites this paper.

Large Vision-Language Models for Remote Sensing Visual Question Answering Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-12T19:15:40.738353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fd48f53-ff94-4cca-a7df-48431eba04b5 · inbound

REO-VLM: Transforming VLM to Meet Regression Challenges in Earth Observation cites this paper.

REO-VLM: Transforming VLM to Meet Regression Challenges in Earth Observation Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T10:30:49.661786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ab519ed-1830-44a5-b969-a1d1cb008ca9 · inbound

Visual Large Language Models for Generalized and Specialized Applications cites this paper.

Visual Large Language Models for Generalized and Specialized Applications Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 273

Resolution: unresolved; no resolver link, observed 2026-08-10T22:08:09.958503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7334579-dc88-4123-81ce-9256a2e1e75b · inbound

Multi-Agent Geospatial Copilots for Remote Sensing Workflows cites this paper.

Multi-Agent Geospatial Copilots for Remote Sensing Workflows Large Language Models for Captioning and Retrieving Remote Sensing Images

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T13:41:49.047023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-23T06:30:58.430688+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.