{"url":"/dataset/alta-2023-shared-task","name":"ALTA 2023 Shared Task","full_name":"Discriminate between human-authored and synthetic text generated by Large Language Models (LLMs)","description_markdown":"This dataset is described in the [ALTA 2023 Shared Task](https://www.alta.asn.au/events/sharedtask2023/index.html) and associated [CodaLab competition](https://codalab.lisn.upsaclay.fr/competitions/14327).\r\n\r\nThe goal of this task is to build automatic detection systems that can discriminate between human-authored and synthetic text generated by Large Language Models (LLMs). The generated synthetic text will come from a variety of sources, including different domain sources (e.g., law, medical) and different LLMs (e.g., T5, GPT-X). The performance of the models will be evaluated based on their accuracy, robustness in detecting synthetic text.","description_withheld":null,"homepage":"https://www.alta.asn.au/events/sharedtask2023/index.html","introduced_date":"2023-07-04","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ALTA 2023 Shared Task"],"data_loaders":[],"num_papers_in_archive":0,"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."}