Paper Citation Record · LEDGER

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

As of 14 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 5 inbound Pith citation observations for arXiv:2507.16716.

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

pith.paper-citation-record.v1
2507.16716 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:07:36.719119Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T10:21:05.683216Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:27:39.981179Z

Reference resolution

69 of 69 outbound references displayed

verified exact3
verified fuzzy19
unresolved47
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e2806d67-64b6-4911-81da-35e16fd7a72c · outbound

This paper cites Radford, J.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Radford, J

Reference 1

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Observation 3019f3c6-92bd-4dd9-a3ef-3dcb089ff482 · outbound

This paper cites an unresolved cited work.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 2

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Observation a9d6ab1f-8d29-4de2-b802-510eeafda76c · outbound

This paper cites Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm

Reference 3

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Source-reported events for the cited work

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Observation 7a8c014c-382e-43f9-951c-22a96bef6602 · outbound

This paper cites EVA-CLIP: Improved Training Techniques for CLIP at Scale.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation EVA-CLIP: Improved Training Techniques for CLIP at Scale

Reference 4

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Observation 8c9ccf41-81f7-442a-9f57-cce6a39ec905 · outbound

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

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 5

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Source-reported events for the cited work

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Observation 29d824d2-72f4-4880-abf4-379da2137c6a · outbound

This paper cites an unresolved cited work.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 6

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Observation f31d2c5d-d876-4a47-aeca-499d7dd1d79a · outbound

This paper cites Open-vocabulary Object Detection via Vision and Language Knowledge Distillation.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Open-vocabulary Object Detection via Vision and Language Knowledge Distillation

Reference 7

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Source-reported events for the cited work

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Observation 4b2d807e-fe8f-405d-9432-e9dd4bc960fb · outbound

This paper cites VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding

Reference 8

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Observation b8b641c1-5144-4cb4-8d91-4ff30c4b3e16 · outbound

This paper cites Guzhov, F.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Guzhov, F

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:07:44.756793Z

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Observation f41a9961-96eb-4c30-bea4-a2e3c3bb2ea1 · outbound

This paper cites Zhang, Z.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Zhang, Z

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:07:44.546880Z

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Observation eef33338-2fcd-4956-a72c-68b423128418 · outbound

This paper cites an unresolved cited work.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 11

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Observation a27b1289-e4f8-44f9-afb6-193e35d6becb · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 12

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Observation 62e063e9-8e0c-4272-9650-6ab3f511cce6 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 13

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Observation 86f846a9-fb58-4047-9aa5-1a139a4bf6ec · outbound

This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 14

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Source-reported events for the cited work

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Observation c17bb975-54a7-435b-b4f1-2f0c2214e2f8 · outbound

This paper cites Doveh, A.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Doveh, A

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:07:44.134853Z

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Observation cb002f0b-3314-4303-bba3-99dd465ea32a · outbound

This paper cites Barham, A.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Barham, A

Reference 16

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Observation cf3829c2-7d83-4951-9146-66ae920f309b · outbound

This paper cites an unresolved cited work.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 17

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Observation 96ed866d-55eb-4ac4-99cf-8564ea5d0eea · outbound

This paper cites an unresolved cited work.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 18

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Observation 110fd7b9-844a-4393-b313-32597c7dba4f · outbound

This paper cites RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensing.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation RS5M and GeoRSCLIP: A Large Scale Vision-Language Dataset and A Large Vision-Language Model for Remote Sensing

Reference 19

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 20

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Observation 93ce4775-1446-443f-9774-75b34a954438 · outbound

This paper cites Djoufack Basso, Clip-rs: A cross-modal remote sens- ing image retrieval based on clip, a northern virginia case study, Ph.D.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Djoufack Basso, Clip-rs: A cross-modal remote sens- ing image retrieval based on clip, a northern virginia case study, Ph.D

Reference 21

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Observation 7c77d13b-af35-40ef-a0f2-b47fa981f50a · outbound

This paper cites an unresolved cited work.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 22

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Observation 88f2835b-5272-4196-83ea-6c24caab3b65 · outbound

This paper cites RSGPT: A Remote Sensing Vision Language Model and Benchmark.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation RSGPT: A Remote Sensing Vision Language Model and Benchmark

Reference 23

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Observation 8c20c456-09d7-4605-89a6-7cf0ff664e8d · outbound

This paper cites SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Model.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Model

Reference 24

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Observation 7d6495d9-a38b-4755-bf58-d828f63d00dd · outbound

This paper cites Goyal, P.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Goyal, P

Reference 25

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Observation 75051ead-b0f2-4a3d-b10d-a6e5699e43c4 · outbound

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 26

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Observation 14586e91-342f-48d9-b683-c7e61f2fe498 · outbound

This paper cites Urbanek, F.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Urbanek, F

Reference 27

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Observation 94e35f08-5ba2-4f15-b849-4ec187ca6933 · outbound

This paper cites an unresolved cited work.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 28

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 29

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Observation 4f1da913-ba2d-4fa8-afa2-1e25e0606f2c · outbound

This paper cites ChatEarthNet: A Global-Scale Image-Text Dataset Empowering Vision-Language Geo-Foundation Models.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation ChatEarthNet: A Global-Scale Image-Text Dataset Empowering Vision-Language Geo-Foundation Models

Reference 30

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 31

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Observation 0730433b-393e-4297-b842-fa15c1255689 · outbound

This paper cites Grubinger, P.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Grubinger, P

Reference 32

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Observation ca173249-0ede-493f-8201-acbd3fa2336b · outbound

This paper cites Rashtchian, P.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Rashtchian, P

Reference 33

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Observation 4dd10b93-6818-4d88-b412-4d26a8dc9d43 · outbound

This paper cites Hodosh, P.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Hodosh, P

Reference 34

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Observation 7690a2dd-8e54-493a-be30-ff01d64a64b5 · outbound

This paper cites Young, A.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Young, A

Reference 35

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Observation 2589d916-88c9-4f7f-a76e-c7ba9a1a587c · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 36

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Observation c7edbe8a-a924-4ed8-8801-66eb9cabf258 · outbound

This paper cites Ordonez, G.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Ordonez, G

Reference 37

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Observation 347efc2a-5043-4014-90d9-01444e8d4ea2 · outbound

This paper cites Sharma, N.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Sharma, N

Reference 38

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Observation 3663b2d3-f848-425a-8d24-f0108e5604e6 · outbound

This paper cites Florence: A New Foundation Model for Computer Vision.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Florence: A New Foundation Model for Computer Vision

Reference 39

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Observation ea14d85b-de72-45ec-824f-dfb1eaa81fff · outbound

This paper cites LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment

Reference 40

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Observation 0f8b4573-f24a-4936-861e-2e9dc61584a4 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 41

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Unresolved cited work

Reference 42

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Observation b37f7e74-1af2-4020-9195-a83a2d0ae509 · outbound

This paper cites Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval

Reference 43

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Source-reported events for the cited work

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Observation c0ed3e2a-92e4-4056-ae62-e5c6c5d12642 · outbound

This paper cites Cheng, H.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Cheng, H

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:07:40.450875Z

Source-reported events for the cited work

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Observation 7c54aa3f-1e57-4b99-bbf6-69277fa249b5 · outbound

This paper cites From LAION-5B to LAION-EO: Filtering Billions of Images Using Anchor Datasets for Satellite Image Extraction.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation From LAION-5B to LAION-EO: Filtering Billions of Images Using Anchor Datasets for Satellite Image Extraction

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:07:37.430966Z

Source-reported events for the cited work

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Observation ad146f19-99ca-4a85-a9be-d1e13d1ce6de · outbound

This paper cites Vaswani, Attention is all you need, Advances in Neural Information Processing Systems.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Vaswani, Attention is all you need, Advances in Neural Information Processing Systems

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:07:40.275687Z

Source-reported events for the cited work

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Observation ce5d8fda-a3eb-44aa-a21f-d9c27bf9bf36 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation On the Opportunities and Risks of Foundation Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T15:07:34.944450Z

Source-reported events for the cited work

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Observation 0edfebda-9437-452a-a738-70c5ba6eb63c · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T15:07:35.003254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a7c317-bb1b-470a-be22-3c84feaae38b · outbound

This paper cites Raffel, N.

Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Raffel, N

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:07:40.085017Z

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 50

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Radford, Improving language understanding by gen- erative pre-training

Reference 51

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Radford, J

Reference 52

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Language Models are Few-Shot Learners

Reference 53

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Reference 55

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Reference 56

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 57

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Huang, L

Reference 58

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Reference 59

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Reference 60

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Reference 61

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation GPT-4 Technical Report

Reference 62

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation CogVLM: Visual Expert for Pretrained Language Models

Reference 63

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Yi: Open Foundation Models by 01.AI

Reference 64

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Reference 65

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation IC3: Image Captioning by Committee Consensus

Reference 66

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Observation d6a2c483-0b6d-4c9e-a238-26af21359dc9 · outbound

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Teo, How i won singapore’s gpt-4 prompt engineering competition, Towards Data Science, Medium 29

Reference 67

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Observation f5abce0b-faeb-4d1a-ae2a-ca7288474770 · outbound

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Decoupled Weight Decay Regularization

Reference 68

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Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation Representation Learning with Contrastive Predictive Coding

Reference 69

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Reference 70

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Pith citing papers

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

SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery cites this paper.

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

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Observation a688868a-95e4-474c-af29-dc3b48572498 · inbound

Text-RSIR: A Text-Guided Framework for Efficient Remote Sensing Image Transmission and Reconstruction cites this paper.

Text-RSIR: A Text-Guided Framework for Efficient Remote Sensing Image Transmission and Reconstruction Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation

Reference 58

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Earth-OneVision: Extending Remote Sensing Multimodal Large Language Models to More Sensor Modalities and Tasks Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation

Reference 46

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Observation 413cc070-4f9d-4d42-9fac-5912104cc4e3 · inbound

Promptable Concept Segmentation from Above: Evaluating SAM 3's Zero-Shot and One-Shot Capabilities in Remote Sensing cites this paper.

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Reference 20

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Observation 4d2f9e03-9bd0-4dd7-937b-356e2d925030 · 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? Enhancing Remote Sensing Vision-Language Models Through MLLM and LLM-Based High-Quality Image-Text Dataset Generation

Reference 120

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Unavailable: canonical work link unavailable.