Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:34:06.398953Z
Paper Citation Record · LEDGER
On the Effectiveness of Adaptation Strategies for VLM-Based Federated Learning in Remote Sensing
As of 10 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
26 of 26 outbound references displayed
- verified exact0
- verified fuzzy24
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
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
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:09.252990Z
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 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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:09.244179Z
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 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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:09.235430Z
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 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
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:34:05.008101Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:09.227313Z
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 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
- raw_fallback, observed 2026-08-06T16:34:09.218734Z
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 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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:09.210301Z
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 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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:09.201640Z
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 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
- raw_fallback, observed 2026-08-06T16:34:09.193048Z
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 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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:09.184668Z
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 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
- raw_fallback, observed 2026-08-06T16:34:09.176067Z
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 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
- unresolved
- no resolver link, observed 2026-08-06T16:34:05.566069Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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
- raw_fallback, observed 2026-08-06T16:34:09.159290Z
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 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
- raw_fallback, observed 2026-08-06T16:34:09.075256Z
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 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
- raw_fallback, observed 2026-08-06T16:34:08.933411Z
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 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
- raw_fallback, observed 2026-08-06T16:34:08.816274Z
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 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
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:08.617107Z
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 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
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:08.186424Z
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 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
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:07.936541Z
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 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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:07.632981Z
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 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
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:34:07.438147Z
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 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
- raw_fallback, observed 2026-08-06T16:34:07.159678Z
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 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
- raw_fallback, observed 2026-08-06T16:34:06.950238Z
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 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 2026-08-09T06:31:02.800959+00:00.
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 2026-08-09T06:31:02.800959+00:00.
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 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.