{"url":"/dataset/superrs-vqa-highrs-vqa","name":"SuperRS-VQA, HighRS-VQA","full_name":null,"description_markdown":"We introduce SuperRS-VQA (avg. 8,376×8,376) and HighRS-VQA (avg. 2,000×1,912), the highest-resolution vision-language datasets in RS to date, covering 22 real-world dialogue tasks","description_withheld":null,"homepage":"https://huggingface.co/datasets/initiacms/GeoLLaVA-Data","introduced_date":"2025-05-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/geollava-8k-scaling-remote-sensing-multimodal","title":"GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K Resolution","first_author":"Fengxiang Wang","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["SuperRS-VQA, HighRS-VQA"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}