Paper Citation Record · LEDGER

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery

As of 10 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 4 inbound Pith citation observations for arXiv:2510.22665.

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

pith.paper-citation-record.v1
2510.22665 v3

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-21T20:58:23.547519Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T19:54:51.780848Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

51 of 51 outbound references displayed

verified exact8
verified fuzzy39
unresolved3
parse uncertain0
malformed identifier0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 595db2c0-959c-44a1-abea-6405a5f34b89 · outbound

This paper cites The air force moving and stationary target recog- nition database.https://www.sdms.afrl.af.mil/ index.php?collection=mstar.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery The air force moving and stationary target recog- nition database.https://www.sdms.afrl.af.mil/ index.php?collection=mstar

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.872598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 44c55f8d-fdc6-4ff6-bb60-28b03a4d53ec · outbound

This paper cites Omnisat: Self-supervised modality fusion for earth observation.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Omnisat: Self-supervised modality fusion for earth observation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.816405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 90f80383-8bc5-4e01-a173-dea580560bd1 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with hu- man judgments.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Meteor: An automatic metric for mt evaluation with improved correlation with hu- man judgments

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.827043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 58a55fca-f833-4229-8f61-fc741b4503ba · outbound

This paper cites Tar- get classification using the deep convolutional networks for sar images.IEEE Transactions on Geoscience and Remote Sensing, 54(8):4806–4817.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Tar- get classification using the deep convolutional networks for sar images.IEEE Transactions on Geoscience and Remote Sensing, 54(8):4806–4817

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.829110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 02c234b2-47f6-4807-b6d8-d157e0d94efd · outbound

This paper cites A simple framework for contrastive learn- ing of visual representations.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery A simple framework for contrastive learn- ing of visual representations

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.862654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b93bb8c0-9c83-48e1-8c60-bc9e89c447e8 · outbound

This paper cites Reproducible scal- ing laws for contrastive language-image learning.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Reproducible scal- ing laws for contrastive language-image learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.797711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1d0303a7-12d8-4b37-9c56-62657eb06c75 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Rouge: A package for automatic evaluation of summaries

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.810059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 34660128-aa3e-4b8b-bae0-13d70febd330 · outbound

This paper cites Satmae: Pre-training transformers for tem- poral and multi-spectral satellite imagery.Advances in Neu- ral Information Processing Systems, 35:197–211.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Satmae: Pre-training transformers for tem- poral and multi-spectral satellite imagery.Advances in Neu- ral Information Processing Systems, 35:197–211

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.852174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 96e45adf-3e6a-49f8-a9f1-5cf87e548e3c · outbound

This paper cites Hyperspectral and sar image classification via graph convolutional fusion network.IEEE Transactions on Geoscience and Remote Sensing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Hyperspectral and sar image classification via graph convolutional fusion network.IEEE Transactions on Geoscience and Remote Sensing

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.848027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 29f3c5cd-b0ad-4ca9-8043-01a8f16e06d2 · outbound

This paper cites Rethinking remote sensing clip: Lever- aging multimodal large language models for high-quality vision-language dataset.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Rethinking remote sensing clip: Lever- aging multimodal large language models for high-quality vision-language dataset

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.864751Z

Source-reported events for the cited work

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Observation ad87c5ab-c97f-485a-bc60-f317710a0b24 · outbound

This paper cites Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:00:39.069199Z

Source-reported events for the cited work

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Observation bb02fe89-e5da-41b1-890b-91f962c218ba · outbound

This paper cites Fusar-ship: Building a high-resolution sar-ais matchup dataset of gaofen-3 for ship detection and recog- nition.Science China Information Sciences, 63(4):140303.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Fusar-ship: Building a high-resolution sar-ais matchup dataset of gaofen-3 for ship detection and recog- nition.Science China Information Sciences, 63(4):140303

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.860630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 35179151-b2ac-46dd-8c33-4d2302d3467a · outbound

This paper cites an unresolved cited work.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-05-21T21:05:37.866565Z

Source-reported events for the cited work

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Observation cf815b1b-4d35-4100-ada0-034423b2972b · outbound

This paper cites Sfr-net: Scattering feature relation network for aircraft detection in complex sar images.IEEE Transactions on Geo- science and Remote Sensing, 60:1–17.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Sfr-net: Scattering feature relation network for aircraft detection in complex sar images.IEEE Transactions on Geo- science and Remote Sensing, 60:1–17

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.883081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d6bd5864-c6dd-49eb-8136-5929a31f5307 · outbound

This paper cites Geochat: Grounded large vision-language model for remote sensing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Geochat: Grounded large vision-language model for remote sensing

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.856173Z

Source-reported events for the cited work

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Observation a41b4b7b-ce3f-4422-a36c-2ae3fdd3f5ba · outbound

This paper cites Synthetic sar image generation using sensor, terrain and target models.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Synthetic sar image generation using sensor, terrain and target models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.858503Z

Source-reported events for the cited work

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Observation d50d88e7-8a85-459f-9201-2d2131cff9c5 · outbound

This paper cites A sar dataset for atr development: the synthetic and measured paired labeled experiment (sample).

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery A sar dataset for atr development: the synthetic and measured paired labeled experiment (sample)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.850085Z

Source-reported events for the cited work

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Observation a9eacb8a-540e-43f2-aa67-6adcc63ae1c8 · outbound

This paper cites Opensarship 2.0: A large-volume dataset for deeper interpretation of ship targets in sentinel-1 imagery.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Opensarship 2.0: A large-volume dataset for deeper interpretation of ship targets in sentinel-1 imagery

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.814129Z

Source-reported events for the cited work

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Observation ac4931f7-8d54-4c8c-ac22-6ed9d39017d3 · outbound

This paper cites an unresolved cited work.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-05-21T21:05:37.854104Z

Source-reported events for the cited work

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Observation cec96f08-8074-49c1-a745-0dfa883b47f8 · outbound

This paper cites Saratr-x: Towards building a foundation model for sar target recognition.IEEE Transactions on Im- age Processing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Saratr-x: Towards building a foundation model for sar target recognition.IEEE Transactions on Im- age Processing

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.799878Z

Source-reported events for the cited work

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Observation 658cef66-1e9e-406c-9406-b95406e55496 · outbound

This paper cites SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery SARDet-100K: Towards Open-Source Benchmark and ToolKit for Large-Scale SAR Object Detection

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:00:39.062484Z

Source-reported events for the cited work

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Observation dafbb708-18a2-4e6b-b8a2-7249d97f980b · outbound

This paper cites Re- moteclip: A vision language foundation model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Re- moteclip: A vision language foundation model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.801949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bde9bda4-cfad-4323-8111-2c8efeda4fc1 · outbound

This paper cites Visual instruction tuning.Advances in Neural Information Processing Systems, 36:34892–34916.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Visual instruction tuning.Advances in Neural Information Processing Systems, 36:34892–34916

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.868539Z

Source-reported events for the cited work

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Observation e94ab6c3-c3c9-4e33-9820-53913729d089 · outbound

This paper cites Learning from Noisy Pseudo-labels for All-Weather Land Cover Mapping.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Learning from Noisy Pseudo-labels for All-Weather Land Cover Mapping

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:00:39.065953Z

Source-reported events for the cited work

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Observation 7a5670da-ed3b-4147-a273-2828f378877b · outbound

This paper cites Atrnet-star: A large dataset and bench- mark towards remote sensing object recognition in the wild.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Atrnet-star: A large dataset and bench- mark towards remote sensing object recognition in the wild

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.820448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9efe556d-afa3-465b-a3bc-9b9667275e63 · outbound

This paper cites Exploring models and data for remote sensing im- age caption generation.IEEE Transactions on Geoscience and Remote Sensing, 56(4):2183–2195.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Exploring models and data for remote sensing im- age caption generation.IEEE Transactions on Geoscience and Remote Sensing, 56(4):2183–2195

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.831497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 672ac5de-67e8-4e57-9766-4edc52e0a402 · outbound

This paper cites SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR Image Interpretation.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery SARChat-Bench-2M: A Multi-Task Vision-Language Benchmark for SAR Image Interpretation

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:00:39.059323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9b76e170-6b3a-4b40-90ce-4cfdeb94a0d4 · outbound

This paper cites Visualizing data using t-sne.Journal of Machine Learning Research, 9 (Nov):2579–2605.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Visualizing data using t-sne.Journal of Machine Learning Research, 9 (Nov):2579–2605

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.838235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 816adf27-7594-4126-997d-523ba6b80709 · outbound

This paper cites Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T21:00:39.055874Z

Source-reported events for the cited work

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Observation b686b35c-7114-492a-9715-01b4edbd6e4f · outbound

This paper cites Improving sar automatic target recognition models with transfer learning from simulated data.IEEE Geoscience and Remote Sensing Letters, 14(9):1484–1488.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Improving sar automatic target recognition models with transfer learning from simulated data.IEEE Geoscience and Remote Sensing Letters, 14(9):1484–1488

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.834045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 724078c5-b1aa-492c-8101-c872f9165470 · outbound

This paper cites Lhrs-bot: Empowering remote sensing with vgi-enhanced large multimodal language model.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Lhrs-bot: Empowering remote sensing with vgi-enhanced large multimodal language model

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.836166Z

Source-reported events for the cited work

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Observation 9ce74970-2d8a-4ca7-a6d5-0d9e6f43e493 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Bleu: a method for automatic evaluation of machine translation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.843672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c29af940-8d35-45dc-96b7-5ed8e882fed1 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Learn- ing transferable visual models from natural language super- vision

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.878548Z

Source-reported events for the cited work

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Observation 9203da91-24e0-49ef-a0bd-bb92ffe0f048 · outbound

This paper cites Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.840277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e7b6325e-822f-4a6d-9f1e-313ce05c3133 · outbound

This paper cites an unresolved cited work.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-05-21T21:05:37.818408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b4e42bf7-0193-4ece-9be4-92851600c8fb · outbound

This paper cites Ringmo: A remote sensing foundation model with masked image modeling.IEEE Transactions on Geo- science and Remote Sensing, 61:1–22.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Ringmo: A remote sensing foundation model with masked image modeling.IEEE Transactions on Geo- science and Remote Sensing, 61:1–22

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.880521Z

Source-reported events for the cited work

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Observation 43bbb105-a707-4cf1-8397-e59691918904 · outbound

This paper cites Cross-scale mae: A tale of multiscale exploita- tion in remote sensing.Advances in Neural Information Pro- cessing Systems, 36:20054–20066.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Cross-scale mae: A tale of multiscale exploita- tion in remote sensing.Advances in Neural Information Pro- cessing Systems, 36:20054–20066

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.808020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b64762f9-1aa5-460c-b530-ffb7d314b52d · outbound

This paper cites Cider: Consensus-based image description evalua- tion.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Cider: Consensus-based image description evalua- tion

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.824822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f762fd6c-4631-4944-825e-3f26df37cee8 · outbound

This paper cites LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:00:39.052291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 40f5e9a7-7a52-495e-bc19-504f593812f6 · outbound

This paper cites Skyscript: A large and seman- tically diverse vision-language dataset for remote sensing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Skyscript: A large and seman- tically diverse vision-language dataset for remote sensing

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.885906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d5e745fc-d866-4d90-a39a-610ae8cc25bc · outbound

This paper cites SARLANG-1M: A Benchmark for Vision-Language Modeling in SAR Image Understanding.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery SARLANG-1M: A Benchmark for Vision-Language Modeling in SAR Image Understanding

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:00:39.048711Z

Source-reported events for the cited work

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Observation f85b0a50-7d4e-47b4-88b6-6e7ed7fafa50 · outbound

This paper cites Robust fine-tuning of zero-shot models.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Robust fine-tuning of zero-shot models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.887946Z

Source-reported events for the cited work

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Observation aade4117-29eb-4e43-80e1-4b9c410f7107 · outbound

This paper cites Fair-csar: A benchmark dataset for fine-grained object detection and recognition based on single look complex sar images.IEEE Transactions on Geoscience and Remote Sensing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Fair-csar: A benchmark dataset for fine-grained object detection and recognition based on single look complex sar images.IEEE Transactions on Geoscience and Remote Sensing

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.804007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 37684e29-33a8-42e8-b4fb-fdb991bdf5db · outbound

This paper cites Dota: A large-scale dataset for object detection in aerial images.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Dota: A large-scale dataset for object detection in aerial images

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.805879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6617c505-adc6-4bfd-9fd1-5ce214477d90 · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-05-21T21:00:39.045218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e56ef695-2798-4491-a94d-e8b03aefa583 · outbound

This paper cites Selo v2: Toward for higher and faster semantic localization.IEEE Geoscience and Remote Sensing Letters, 20:1–5.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Selo v2: Toward for higher and faster semantic localization.IEEE Geoscience and Remote Sensing Letters, 20:1–5

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.876598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1c246da5-9e85-4c7a-a3ca-a9d95cc6ca1a · outbound

This paper cites Learning to evaluate performance of multimodal semantic localization.IEEE Transactions on Geoscience and Remote Sensing, 60:1–18.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Learning to evaluate performance of multimodal semantic localization.IEEE Transactions on Geoscience and Remote Sensing, 60:1–18

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.812137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eb194f4d-c8d2-4df2-8c35-9be6c9c3119b · outbound

This paper cites Sar ship detection dataset (ssdd): Offi- cial release and comprehensive data analysis.Remote Sens- ing, 13(18):3690.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Sar ship detection dataset (ssdd): Offi- cial release and comprehensive data analysis.Remote Sens- ing, 13(18):3690

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.874619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6d2303b8-db7b-4075-ac33-d8f989734b0d · outbound

This paper cites Earthgpt: A universal multi-modal large lan- guage model for multi-sensor image comprehension in re- mote sensing domain.IEEE Transactions on Geoscience and Remote Sensing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Earthgpt: A universal multi-modal large lan- guage model for multi-sensor image comprehension in re- mote sensing domain.IEEE Transactions on Geoscience and Remote Sensing

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.845934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6a422e3d-0dfa-4aba-867b-cc7d8a017c9f · outbound

This paper cites RSAR: Restricted State Angle Resolver and Rotated SAR Benchmark.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery RSAR: Restricted State Angle Resolver and Rotated SAR Benchmark

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:00:39.041826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fb45d4ad-d686-44d9-9e23-51088b9a49b8 · outbound

This paper cites Rs5m and georsclip: A large scale vision-language dataset and a large vision-language model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing.

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery Rs5m and georsclip: A large scale vision-language dataset and a large vision-language model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T21:05:37.870630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

Observation 03ed5731-6026-4e92-95f7-f5986f87b064 · inbound

Geospatial-Temporal Sensemaking of Remote Sensing Activity Detections with Multimodal Large Language Model cites this paper.

Geospatial-Temporal Sensemaking of Remote Sensing Activity Detections with Multimodal Large Language Model SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:00:26.580375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f1acadad-ad01-4719-b2d9-ac266179bb55 · inbound

FUSAR-R1: A Large-Scale Reasoning Model for Intelligent Interpretation of SAR Images cites this paper.

FUSAR-R1: A Large-Scale Reasoning Model for Intelligent Interpretation of SAR Images SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T19:54:51.780848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 079263cd-40ce-46ee-95bf-fd2d8cb81b38 · inbound

Not All Patches are Equal: Sampling Matters for Visible-Infrared Pre-Training cites this paper.

Not All Patches are Equal: Sampling Matters for Visible-Infrared Pre-Training SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-01T10:27:20.420271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1758c2eb-759e-4dc9-a6e1-48b025b2a09d · inbound

SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models cites this paper.

SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-01T03:22:09.867274Z

Source-reported events for the cited work

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