{"url":"/dataset/vstar-1m","name":"VSTaR-1M","full_name":null,"description_markdown":"VSTaR-1M is a 1M instruction tuning dataset, created using Video-STaR, with the source datasets: \r\n* [Kinetics700](https://github.com/cvdfoundation/kinetics-dataset)\r\n* [STAR-benchmark](https://bobbywu.com/STAR/)\r\n* [FineDiving](https://finediving.ivg-research.xyz)\r\n\r\nThe videos for VSTaR-1M can be found in the links above. \r\n\r\nVSTaR-1M is built off of diverse task with the goal of enhancing video-language alignment in Large Video-Language Models (LVLMs).\r\n\r\n* kinetics700_tune_.json - Instruction tuning QA pairs for the Kinetics700 source dataset. Good for increasing diversity and for more fine-grained activity recognition.  \r\n* starb_tune_.json - Instruction tuning QA pairs for the STAR-benchmark source dataset. Good for temporal reasoning.\r\n* finediving_tune_.json - Instruction tuning QA pairs for the FineDiving source dataset. Example of adapting LVLMs for novel tasks (Olympic diving judge).","description_withheld":null,"homepage":"https://huggingface.co/datasets/orrzohar/Video-STaR","introduced_date":"2024-07-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/video-star-self-training-enables-video","title":"Video-STaR: Self-Training Enables Video Instruction Tuning with Any Supervision","first_author":"Orr Zohar","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"visual instruction following","url":"/task/visual-instruction-following","datasets_with_task":"/datasets/task/visual-instruction-following"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["VSTaR-1M"],"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."}