Paper Citation Record · LEDGER

GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2410.19552.

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

pith.paper-citation-record.v1
2410.19552 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:20:08.686351Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:27:40.000390Z

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 8ebd891d-8e31-42ea-bec9-8717b80a5135 · inbound

Vision-Language Models for Edge Networks: A Comprehensive Survey cites this paper.

Vision-Language Models for Edge Networks: A Comprehensive Survey GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 141

Resolution: unresolved; no resolver link, observed 2026-08-08T12:20:08.686351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cddd690e-fa14-49b9-a2bc-321b147da3a4 · inbound

Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modeling cites this paper.

Remote Sensing Large Vision-Language Model: Semantic-augmented Multi-level Alignment and Semantic-aware Expert Modeling GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T22:22:40.114061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25579411-a4fa-4a53-8687-69c83adccef3 · inbound

Animation Needs Attention: A Holistic Approach to Slides Animation Comprehension with Visual-Language Models cites this paper.

Animation Needs Attention: A Holistic Approach to Slides Animation Comprehension with Visual-Language Models GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T20:04:11.787732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 402e5d75-ed0f-4680-a137-99357aa52267 · inbound

VectorLLM: Human-like Extraction of Structured Building Contours vis Multimodal LLMs cites this paper.

VectorLLM: Human-like Extraction of Structured Building Contours vis Multimodal LLMs GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T19:46:12.158072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1eb793fa-ae0e-4c95-9ea8-928138022831 · inbound

ChatENV: An Interactive Vision-Language Model for Sensor-Guided Environmental Monitoring and Scenario Simulation cites this paper.

ChatENV: An Interactive Vision-Language Model for Sensor-Guided Environmental Monitoring and Scenario Simulation GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-18T23:16:54.077057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eab70322-2d20-4c19-8643-a24f106d5fd7 · inbound

HM-Bench: A Comprehensive Benchmark for Multimodal Large Language Models in Hyperspectral Remote Sensing cites this paper.

HM-Bench: A Comprehensive Benchmark for Multimodal Large Language Models in Hyperspectral Remote Sensing GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:30:57.820546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 21e2f93d-e85a-49f8-ae62-313af166f9de · inbound

A Multi-Agent Feedback System for Detecting and Describing News Events in Satellite Imagery cites this paper.

A Multi-Agent Feedback System for Detecting and Describing News Events in Satellite Imagery GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:21:01.037102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 300a3151-1c53-4c60-bbf2-9c673ce51cc4 · inbound

HiSem: Hierarchical Semantic Disentangling for Remote Sensing Image Change Captioning cites this paper.

HiSem: Hierarchical Semantic Disentangling for Remote Sensing Image Change Captioning GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 65

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:25:46.727444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c4c35a3-592e-479f-b4e3-23a7cf71ce3e · inbound

Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks cites this paper.

Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing

Reference 75

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T05:27:40.002549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.