{"url":"/dataset/meta-world-benchmark","name":"Meta-World Benchmark","full_name":null,"description_markdown":"An open-source simulated benchmark for meta-reinforcement learning and multi-task learning consisting of 50 distinct robotic manipulation tasks.\r\n\r\nSource: [Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning](/paper/meta-world-a-benchmark-and-evaluation-for)","description_withheld":null,"homepage":"http://meta-world.github.io","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/meta-world-a-benchmark-and-evaluation-for","title":"Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning","first_author":"Tianhe Yu","url":null},"license":{"name":"Unknown","url":null},"modalities":[],"tasks":[{"name":"Meta-Learning","url":"/task/meta-learning","datasets_with_task":"/datasets/task/meta-learning"},{"name":"Multi-Task Learning","url":"/task/multi-task-learning","datasets_with_task":"/datasets/task/multi-task-learning"},{"name":"Meta Reinforcement Learning","url":"/task/meta-reinforcement-learning","datasets_with_task":"/datasets/task/meta-reinforcement-learning"}],"languages":[],"variants":["Meta-World Benchmark"],"data_loaders":[],"num_papers_in_archive":73,"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."}