{"url":"/dataset/as-v2","name":"AS-V2","full_name":"The All-Seeing Dataset v2","description_markdown":"We propose a novel task, termed Relation Conversation (ReC), which unifies the formulation of text generation, object localization, and relation comprehension. Based on the unified formulation, we construct the AS-V2 dataset, which consists of 127K high-quality relation conversation samples, to unlock the ReC capability for Multi-modal Large Language Models (MLLMs).","description_withheld":null,"homepage":"https://github.com/OpenGVLab/all-seeing","introduced_date":"2024-02-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-all-seeing-project-v2-towards-general","title":"The All-Seeing Project V2: Towards General Relation Comprehension of the Open World","first_author":"Weiyun Wang","url":null},"license":{"name":"Apache 2.0 license","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["AS-V2"],"data_loaders":[],"num_papers_in_archive":3,"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":"2026-09-25T09:33:49+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."}