{"url":"/dataset/geobench-vlm","name":"GEOBench-VLM","full_name":null,"description_markdown":"GEOBench-VLM, a comprehensive benchmark specifically designed to evaluate VLMs on geospatial tasks, including scene understanding, object counting, localization, fine-grained categorization, and temporal analysis. Our benchmark features over 10,000 manually verified instructions and covers a diverse set of variations in visual conditions, object type, and scale.","description_withheld":null,"homepage":"https://github.com/the-AI-Alliance/GEO-Bench-VLM/","introduced_date":"2024-11-28","introduced_date_note":null,"introduced_by":{"paper":"/paper/geobench-vlm-benchmarking-vision-language","title":"GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks","first_author":"Muhammad Sohail Danish","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GEOBench-VLM"],"data_loaders":[],"num_papers_in_archive":2,"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."}