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Paper Citation Record · LEDGER

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing

As of 23 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2608.04791.

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

pith.paper-citation-record.v1
2608.04791 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:34:06.398953Z

measured 26 of 26 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b787d18a-0767-449e-8e29-516c23b1c926 · outbound

This paper cites Federated learning across decentralized and unshared archives for remote sensing image classification: A review,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Federated learning across decentralized and unshared archives for remote sensing image classification: A review,

Reference 1

Resolution
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Source-reported events for the cited work

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Observation bcaeced9-bbf9-410e-9a4a-77d36ffa2d9f · outbound

This paper cites Federated learning meets remote sensing,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Federated learning meets remote sensing,

Reference 2

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verified fuzzy
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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.

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Observation 4921bd8c-76d4-41fb-b203-563cbc93374c · outbound

This paper cites A multi-modal federated learning framework for remote sensing image classification,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing A multi-modal federated learning framework for remote sensing image classification,

Reference 3

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Source-reported events for the cited work

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Observation 606089d8-7a43-491e-91c5-326c009cd949 · outbound

This paper cites Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions

Reference 4

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Source-reported events for the cited work

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Observation b3b0b20e-c4eb-4b27-b473-4957fe869d1f · outbound

This paper cites FedKL: Tackling data heterogeneity in federated reinforcement learning by penalizing KL divergence,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing FedKL: Tackling data heterogeneity in federated reinforcement learning by penalizing KL divergence,

Reference 5

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verified fuzzy
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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.

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Observation 10c69314-12df-4ae4-bbc3-3bccb1a0c0ba · outbound

This paper cites Learning transferable visual models from natural language supervision,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Learning transferable visual models from natural language supervision,

Reference 6

Resolution
verified fuzzy
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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.

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Observation cb0bf3f2-e0ad-4d00-bbde-0f8dd8ae2b0e · outbound

This paper cites PromptFL: Let federated participants cooperatively learn prompts instead of models–federated learning in age of foundation model,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing PromptFL: Let federated participants cooperatively learn prompts instead of models–federated learning in age of foundation model,

Reference 7

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verified fuzzy
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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.

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Observation f79a7463-00d6-434f-95bb-583a921837a9 · outbound

This paper cites Federated learning from vision-language foundation models: Theoretical analysis and method,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Federated learning from vision-language foundation models: Theoretical analysis and method,

Reference 8

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verified fuzzy
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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.

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Observation a835b85c-3fe0-4710-bb80-a023e522031d · outbound

This paper cites Global and local prompts cooperation via optimal transport for federated learning,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Global and local prompts cooperation via optimal transport for federated learning,

Reference 9

Resolution
verified fuzzy
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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.

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Observation 53038313-5e3c-491f-ad80-747177e70597 · outbound

This paper cites FedRSCLIP: Federated learning for remote sensing scene classification using vision-language models,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing FedRSCLIP: Federated learning for remote sensing scene classification using vision-language models,

Reference 10

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verified fuzzy
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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.

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Observation 89697a28-932b-4162-8024-ccc7e223ff4c · outbound

This paper cites Learning to prompt for vision-language models,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Learning to prompt for vision-language models,

Reference 11

Resolution
verified fuzzy
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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.

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Observation a8332bee-d1f0-4710-893c-cf1355e88ed2 · outbound

This paper cites CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model

Reference 12

Resolution
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no resolver link, observed 2026-08-06T16:34:05.566069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fad395de-31c2-4c04-8808-49919177880d · outbound

This paper cites Harmonizing generalization and personalization in federated prompt learning,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Harmonizing generalization and personalization in federated prompt learning,

Reference 13

Resolution
verified fuzzy
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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.

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Observation 69676696-22ba-4c4b-a6ef-31009bdd86d5 · outbound

This paper cites FedCLIP: Fast generalization and personalization for CLIP in federated learning,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing FedCLIP: Fast generalization and personalization for CLIP in federated learning,

Reference 14

Resolution
verified fuzzy
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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.

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Observation 80c2d1e6-5e2c-4ed4-8167-dae25b4f445a · outbound

This paper cites FedVLM: Scalable personalized vision-language models through federated learning,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing FedVLM: Scalable personalized vision-language models through federated learning,

Reference 15

Resolution
verified fuzzy
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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.

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Observation 0f32f9e7-6e06-4e8b-8a96-e0a24542b19d · outbound

This paper cites F AA-CLIP: Federated adversarial adaptation of CLIP,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing F AA-CLIP: Federated adversarial adaptation of CLIP,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation cbc34dd7-a34a-4dc1-ad4c-8bbc4c10af38 · outbound

This paper cites CLIP-guided federated learning on heterogeneity and long-tailed data,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing CLIP-guided federated learning on heterogeneity and long-tailed data,

Reference 17

Resolution
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Source-reported events for the cited work

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Observation 8a59b40f-eb68-40d1-b2bc-0012ebdbbb7e · outbound

This paper cites LoRA: Low-rank adaptation of large language models,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing LoRA: Low-rank adaptation of large language models,

Reference 18

Resolution
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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.

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Observation 3c9b7f67-fdf3-41a0-98ae-522dd6d6e170 · outbound

This paper cites reBEN: Refined BigEarthNet dataset for remote sensing image analysis,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing reBEN: Refined BigEarthNet dataset for remote sensing image analysis,

Reference 19

Resolution
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Source-reported events for the cited work

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Observation 0b352317-36f1-4006-a49a-3e279224526e · outbound

This paper cites EuroSAT: A novel dataset and deep learning benchmark for land use and land cover classification,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing EuroSAT: A novel dataset and deep learning benchmark for land use and land cover classification,

Reference 20

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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.

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Observation d2b1b8e9-7b68-4480-9368-08d749a618d2 · outbound

This paper cites Remote sensing image scene classification: Benchmark and state of the art,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Remote sensing image scene classification: Benchmark and state of the art,

Reference 21

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verified fuzzy
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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.

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Observation c0b65b78-81a5-4d9b-af0c-fc49a31d1b7e · outbound

This paper cites ImageNet: A large-scale hierarchical image database,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing ImageNet: A large-scale hierarchical image database,

Reference 22

Resolution
verified fuzzy
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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.

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Observation 88595aec-13f1-49d1-8ea7-516e1446808e · outbound

This paper cites ImageNet large scale visual recognition challenge,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing ImageNet large scale visual recognition challenge,

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 1534dd38-9d59-40f2-9fe4-2024285078b6 · outbound

This paper cites Finetune like you pretrain: Improved finetuning of zero-shot vision models,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Finetune like you pretrain: Improved finetuning of zero-shot vision models,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:34:06.794507Z

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.

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Observation 4d4d2e6e-b05c-45b0-981f-b2119adfd725 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Communication-efficient learning of deep networks from decentralized data,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:34:06.681032Z

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.

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Observation 8bc7eae9-b581-42a6-9829-ab40fe10898b · outbound

This paper cites Patching open-vocabulary models by interpolating weights,.

On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing Patching open-vocabulary models by interpolating weights,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:34:06.565698Z

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.

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Pith citing papers

No inbound Pith citation observations are available.