{"url":"/dataset/concept-1k","name":"Concept-1K","full_name":"Concept-1K","description_markdown":"Concept-1K contains 1023 novel concepts from six domains, including economy, culture, science and technology, environment, education, and health and medical. \r\nIt has 16653 training-test QA pairs corresponding to 16653 knowledge points from 1023 concepts.\r\nIt is proposed for evaluating the forgetting in large language models and the effectiveness of incremental learning algorithms.","description_withheld":null,"homepage":"https://github.com/zzz47zzz/pretrained-lm-for-incremental-learning","introduced_date":"2024-02-13","introduced_date_note":null,"introduced_by":{"paper":"/paper/concept-1k-a-novel-benchmark-for-instance","title":"Can LLMs Learn New Concepts Incrementally without Forgetting?","first_author":"Junhao Zheng","url":null},"license":{"name":"CC BY","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Incremental Learning","url":"/task/incremental-learning","datasets_with_task":"/datasets/task/incremental-learning"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Concept-1K"],"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."}