Paper Citation Record · LEDGER

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards

As of 17 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.21745.

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

pith.paper-citation-record.v1
2507.21745 v2

Coverage vector

measured 46 of 46 reference resolution

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measured 46 of 46 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

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External citation measurements

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Outbound references

Observation a09c18a0-9e20-43c3-a6ac-b66fd523279d · outbound

This paper cites GPT-4 Technical Report.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards GPT-4 Technical Report

Reference 1

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Observation 3e0dc74c-3be7-41dc-96d7-12b18ca0f0ec · outbound

This paper cites Open-r1v.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Open-r1v

Reference 2

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Observation c383c698-159a-4cdd-a930-34ccc57be0aa · outbound

This paper cites Qwen technical report,.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Qwen technical report,

Reference 3

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Observation a0ec97d7-bf13-42af-a190-a005fa69f39f · outbound

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

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 4

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Observation 07b43706-eae0-4c6d-9400-706c6ed9f795 · outbound

This paper cites Rs-llava: A large vision-language model for joint captioning and question an- swering in remote sensing imagery.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Rs-llava: A large vision-language model for joint captioning and question an- swering in remote sensing imagery

Reference 5

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Observation fbf23dde-e6be-4cde-a338-c82eccd40083 · outbound

This paper cites PaliGemma: A versatile 3B VLM for transfer.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards PaliGemma: A versatile 3B VLM for transfer

Reference 6

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Observation 22c77e13-fc0e-4655-b79d-437a84f3230a · outbound

This paper cites Lan- guage models are few-shot learners.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Lan- guage models are few-shot learners

Reference 7

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Observation 01e10c1a-239c-4664-93e5-8287b7f0de17 · outbound

This paper cites Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classification.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classification

Reference 8

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This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 9

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Observation 3d33c3d9-7a33-41ff-b277-a9a3c095ab4e · outbound

This paper cites Patch n’pack: Navit, a vision transformer for any aspect ratio and resolution.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Patch n’pack: Navit, a vision transformer for any aspect ratio and resolution

Reference 10

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Observation 4c0f8f6e-7b93-4488-a63f-d1792d7b3c49 · outbound

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

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 11

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Observation ff7ea501-7256-492a-b02f-e037c74442ab · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 12

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Observation be7c4269-2697-4420-b03c-e2f5093d0b11 · outbound

This paper cites Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs

Reference 13

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Observation 6f802c2f-6f76-4228-8a6d-d71f38533bb0 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 14

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Observation e97c7d2f-a67b-4739-aa56-6d7905bcad6d · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards LoRA: Low-Rank Adaptation of Large Language Models

Reference 15

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Observation 4fc331a4-3056-4123-b880-b41c7de012e1 · outbound

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

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards RSGPT: A Remote Sensing Vision Language Model and Benchmark

Reference 16

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Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Unresolved cited work

Reference 17

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This paper cites GPT-4o System Card.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards GPT-4o System Card

Reference 18

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This paper cites Milchat: Introduc- ing chain of thought reasoning and grpo to a multimodal small language model for remote sensing.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Milchat: Introduc- ing chain of thought reasoning and grpo to a multimodal small language model for remote sensing

Reference 19

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This paper cites Tinyrs-r1: Com- pact multimodal language model for remote sensing.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Tinyrs-r1: Com- pact multimodal language model for remote sensing

Reference 20

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Observation 22d67a7b-d9b8-40bc-a74b-cbb9afb53481 · outbound

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

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Geochat: Grounded large vision-language model for remote sensing

Reference 21

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Observation 1b61534a-9036-496c-a0ec-12edcc042d2b · outbound

This paper cites LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language Interpretation.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language Interpretation

Reference 22

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This paper cites Visual instruction tuning, 2023.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Visual instruction tuning, 2023

Reference 23

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This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Understanding R1-Zero-Like Training: A Critical Perspective

Reference 24

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Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Open-r1 multimodal

Reference 25

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

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Lhrs-bot: Empowering remote sensing with vgi-enhanced large multimodal language model

Reference 26

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This paper cites Quality-driven curation of remote sensing vision-language data via learned scoring models.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Quality-driven curation of remote sensing vision-language data via learned scoring models

Reference 27

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This paper cites Gpt-3.5 turbo fine-tuning and api updates, 2023.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Gpt-3.5 turbo fine-tuning and api updates, 2023

Reference 28

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This paper cites Gpt-4v(ision) system card, 2023.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Gpt-4v(ision) system card, 2023

Reference 29

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This paper cites Introducing openai o1-preview, 2024.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Introducing openai o1-preview, 2024

Reference 30

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Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Openai o3-mini, 2025

Reference 31

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This paper cites Vhm: Versatile and honest vision language model for remote sensing image analysis.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Vhm: Versatile and honest vision language model for remote sensing image analysis

Reference 32

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Observation e6a1a285-dc5e-4b3a-ad03-dcb239c61c5c · outbound

This paper cites Improving language understanding by gen- erative pre-training.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Improving language understanding by gen- erative pre-training

Reference 33

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Observation b0cf932c-2910-48c4-85b5-0d2bb6c81b05 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Learning Transferable Visual Models From Natural Language Supervision

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Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Rethinking Reflection in Pre-Training

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This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 36

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This paper cites PaliGemma 2: A Family of Versatile VLMs for Transfer.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards PaliGemma 2: A Family of Versatile VLMs for Transfer

Reference 37

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This paper cites Gemma: Open models based on gemini research and technology,.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Gemma: Open models based on gemini research and technology,

Reference 38

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Observation 07019a97-2c42-4ba7-8da9-c579c45f5bc6 · outbound

This paper cites Internlm: A multilingual language model with progressively enhanced capabilities.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Internlm: A multilingual language model with progressively enhanced capabilities

Reference 39

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This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 40

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This paper cites Llama: Open and efficient foundation lan- guage models, 2023.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Llama: Open and efficient foundation lan- guage models, 2023

Reference 41

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Observation f4c395af-992d-4b2d-8ee1-7929f4c64265 · outbound

This paper cites Attention is all you need.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Attention is all you need

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:29:37.971621Z

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Observation 80156f8a-e8b0-46f5-a4df-54627187a56f · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 43

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This paper cites Reinforcement Learning for Reasoning in Large Language Models with One Training Example.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Reference 44

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Observation eb3d2064-f864-4b87-a8e6-f53f13e38818 · outbound

This paper cites Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Reference 45

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This paper cites Earthgpt: A universal multi-modal large lan- guage model for multi-sensor image comprehension in re- mote sensing domain.

Few-Shot Vision-Language Reasoning for Satellite Imagery via Verifiable Rewards Earthgpt: A universal multi-modal large lan- guage model for multi-sensor image comprehension in re- mote sensing domain

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:29:37.956630Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.