VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes | Paper Citation Record

Observation a9710184-b82d-4262-ab7b-456adb33bd58 · outbound

This paper cites Danish, Muzammal Naseer, Abhijit Das, Salman Khan, and Fahad S.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Danish, Muzammal Naseer, Abhijit Das, Salman Khan, and Fahad S

Reference 1

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This paper cites Rs-llava: A large vision-language model for joint captioning and question answering in remote sensing imagery.Remote Sensing, 16(9), 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Rs-llava: A large vision-language model for joint captioning and question answering in remote sensing imagery.Remote Sensing, 16(9), 2024

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This paper cites Vhm: Versatile and honest vision language model for remote sensing image analysis.Proceedings of the AAAI Conference on Artificial Intelligence, 39(6):6381–6388, Apr.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Vhm: Versatile and honest vision language model for remote sensing image analysis.Proceedings of the AAAI Conference on Artificial Intelligence, 39(6):6381–6388, Apr

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This paper cites Earthdial: Turning multi-sensory earth observations to interactive dialogues.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Earthdial: Turning multi-sensory earth observations to interactive dialogues

Reference 6

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Observation eb13fd66-ec77-4e0e-a773-5ca8a8147867 · outbound

This paper cites Geopixel: Pixel grounding large multimodal model in remote sensing.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Geopixel: Pixel grounding large multimodal model in remote sensing

Reference 7

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Observation 9e45e72d-487d-4df1-86e7-3471ebacfc41 · outbound

This paper cites Towards faithful reasoning in remote sensing: A perceptually- grounded geospatial chain-of-thought for vision-language models.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Towards faithful reasoning in remote sensing: A perceptually- grounded geospatial chain-of-thought for vision-language models

Reference 8

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This paper cites Re- motereasoner: Towards unifying geospatial reasoning workflow.Proceedings of the AAAI Conference on Artificial Intelligence, 40(14):11883–11891, Mar.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Re- motereasoner: Towards unifying geospatial reasoning workflow.Proceedings of the AAAI Conference on Artificial Intelligence, 40(14):11883–11891, Mar

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Observation 920aacfd-8dd2-4054-998d-e81e7d93774d · outbound

This paper cites Rsgpt: A remote sensing vision language model and benchmark.ISPRS Journal of Photogrammetry and Remote Sensing, 224:272–286, 2025.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Rsgpt: A remote sensing vision language model and benchmark.ISPRS Journal of Photogrammetry and Remote Sensing, 224:272–286, 2025

Reference 10

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This paper cites Hrvqa: A visual question answering benchmark for high-resolution aerial images.ISPRS Journal of Photogrammetry and Remote Sensing, 214:65–81, 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Hrvqa: A visual question answering benchmark for high-resolution aerial images.ISPRS Journal of Photogrammetry and Remote Sensing, 214:65–81, 2024

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Observation 33aa3ca8-0cac-45d9-a8f0-e0c702d2337e · outbound

This paper cites Earthvqa: Towards queryable earth via relational reasoning-based remote sensing visual question answering.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Earthvqa: Towards queryable earth via relational reasoning-based remote sensing visual question answering

Reference 12

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Observation 54ce4f99-4263-4a5d-bca1-310c8fbfa380 · outbound

This paper cites Rsvlm-qa: A benchmark dataset for remote sensing vision language model-based question answering.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Rsvlm-qa: A benchmark dataset for remote sensing vision language model-based question answering

Reference 13

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Observation b620d4cc-ec0c-41cb-aeda-32cedbf8fb97 · outbound

This paper cites Vrsbench: A versatile vision-language benchmark dataset for remote sensing image understanding.Advances in Neural Information Processing Systems, 37:3229–3242, 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Vrsbench: A versatile vision-language benchmark dataset for remote sensing image understanding.Advances in Neural Information Processing Systems, 37:3229–3242, 2024

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This paper cites Geobench-vlm: Benchmarking vision-language models for geospatial tasks.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Geobench-vlm: Benchmarking vision-language models for geospatial tasks

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This paper cites CHOICE: Benchmarking the remote sensing capabilities of large vision-language models.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes CHOICE: Benchmarking the remote sensing capabilities of large vision-language models

Reference 16

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VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Unresolved cited work

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Observation 554f7a26-98cf-4b78-bf78-90c9896d8468 · outbound

This paper cites VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing

Reference 18

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Observation aa922583-856b-4b3b-a1c4-0ec955207f24 · outbound

This paper cites Geo3dvqa: Evaluating vision-language models for 3d geospatial reasoning from aerial imagery.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Geo3dvqa: Evaluating vision-language models for 3d geospatial reasoning from aerial imagery

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Observation 5742272d-782e-463c-a7f9-918d39bbf814 · outbound

This paper cites A survey of image classification methods and techniques for improving classification performance.International journal of Remote sensing, 28(5):823–870, 2007.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes A survey of image classification methods and techniques for improving classification performance.International journal of Remote sensing, 28(5):823–870, 2007

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Observation 9f5ef635-d6af-48da-aa1e-124baa8bfade · outbound

This paper cites Lidar data fusion to improve forest attribute estimates: A review.Current Forestry Reports, 10(4):281–297, 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Lidar data fusion to improve forest attribute estimates: A review.Current Forestry Reports, 10(4):281–297, 2024

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Observation 0d5c8e59-a882-4ee7-8bcc-8350c791b956 · outbound

This paper cites Fine classification of urban tree species based on uav-based rgb imagery and lidar data.Forests, 15(2):390, 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Fine classification of urban tree species based on uav-based rgb imagery and lidar data.Forests, 15(2):390, 2024

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Observation 82a2188c-661d-4f06-8992-96dbdcab3b89 · outbound

This paper cites A deep-learning-based tree species classification for natural secondary forests using unmanned aerial vehicle hyperspectral images and lidar.Ecological Indicators, 159:111608, 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes A deep-learning-based tree species classification for natural secondary forests using unmanned aerial vehicle hyperspectral images and lidar.Ecological Indicators, 159:111608, 2024

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Observation 2a5ad11d-977f-4868-ac61-3fea4c923fc0 · outbound

This paper cites Mapping urban tree species by integrating canopy height model with multi-temporal sentinel-2 data.Remote Sensing, 17(5):790, 2025.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Mapping urban tree species by integrating canopy height model with multi-temporal sentinel-2 data.Remote Sensing, 17(5):790, 2025

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Observation 000c3e6c-9c99-4641-bcab-b8568d184721 · outbound

This paper cites Object-based tree species classification using airborne hyperspectral images and lidar data.Forests, 11(1):32, 2019.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Object-based tree species classification using airborne hyperspectral images and lidar data.Forests, 11(1):32, 2019

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This paper cites Remote sensing vision-language foundation models without annotations via ground remote alignment.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Remote sensing vision-language foundation models without annotations via ground remote alignment

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Observation aca24033-253c-4c41-95f3-d9daf28d9b49 · outbound

This paper cites Remoteclip: A vision language foundation model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing, 62:1–16, 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Remoteclip: A vision language foundation model for remote sensing.IEEE Transactions on Geoscience and Remote Sensing, 62:1–16, 2024

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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, pages 1–1, 2024.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes 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, pages 1–1, 2024

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This paper cites Skyeyegpt: Unifying remote sensing vision-language tasks via instruction tuning with large language model.ISPRS Journal of Photogrammetry and Remote Sensing, 221:64–77, 2025.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Skyeyegpt: Unifying remote sensing vision-language tasks via instruction tuning with large language model.ISPRS Journal of Photogrammetry and Remote Sensing, 221:64–77, 2025

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

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Lhrs-bot: Empowering remote sensing with vgi-enhanced large multimodal language model

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VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Unresolved cited work

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This paper cites Geollava-8k: Scaling remote-sensing multimodal large language models to 8k resolution.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Geollava-8k: Scaling remote-sensing multimodal large language models to 8k resolution

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This paper cites Terramind: Large-scale generative multimodality for earth observation.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Terramind: Large-scale generative multimodality for earth observation

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This paper cites Geoeyes: On-demand visual focusing for evidence-grounded understanding of ultra-high-resolution re- mote sensing imagery.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Geoeyes: On-demand visual focusing for evidence-grounded understanding of ultra-high-resolution re- mote sensing imagery

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This paper cites Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change Detection.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change Detection

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Observation 55f06c66-96e7-41a9-8ace-4dffebf7d04b · outbound

This paper cites Can Large Multimodal Models Understand Agricultural Scenes? Benchmarking with AgroMind.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Can Large Multimodal Models Understand Agricultural Scenes? Benchmarking with AgroMind

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This paper cites Canopy height model and naip imagery pairs across conus.Scientific Data, 12(1):322, 2025.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Canopy height model and naip imagery pairs across conus.Scientific Data, 12(1):322, 2025

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VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Unresolved cited work

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VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Openai gpt-5 system card, 2025

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This paper cites Qwen3.5: Accelerating productivity with native multimodal agents, February 2026.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Qwen3.5: Accelerating productivity with native multimodal agents, February 2026

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This paper cites Internvl3.5: Advancing open-source multimodal models in versatility, reasoning, and efficiency, 2025.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Internvl3.5: Advancing open-source multimodal models in versatility, reasoning, and efficiency, 2025

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This paper cites Mistralai/mistral-small-3.1-24b-instruct-2503 · hugging face.

VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Mistralai/mistral-small-3.1-24b-instruct-2503 · hugging face

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VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Phi-4 technical report, 2024

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VertiCue-Bench: Diagnosing Whether MLLMs Use Height Cues to Resolve 2D Ambiguity in Remote Sensing Natural Scenes Gemma 3 technical report, 2025

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