{"url":"/dataset/nian","name":"NIAN","full_name":"Needle in a Needlestack","description_markdown":"The **Needle in a Needlestack** (NIAN) is a new benchmark designed to measure how well Language Learning Models (LLMs) pay attention to the information in their context window¹. \r\n\r\nIn this benchmark, a prompt is created that includes thousands of limericks, and the prompt asks a question about one limerick at a specific location¹. The goal is to test the ability of LLMs to locate and understand specific information within a large context. \r\n\r\nFor example, a prompt might include around 2500 limericks, and the LLM is asked a question about a limerick at a certain position¹. The LLM's task is to correctly answer the question by paying attention to the right part of the context.\r\n\r\n(1) GPT-4o’s Memory Breakthrough! (NIAN code) | needle-in-a-needlestack. http://nian.llmonpy.ai/.\r\n(2) [P] Needle in a Needlestack (NIAN) | allainews.com. https://allainews.com/item/p-needle-in-a-needlestack-nian-2024-05-16/.\r\n(3) GitHub - llmonpy/needle-in-a-needlestack. https://github.com/llmonpy/needle-in-a-needlestack/.","description_withheld":null,"homepage":"https://github.com/llmonpy/needle-in-a-needlestack","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Information Retrieval","url":"/task/information-retrieval","datasets_with_task":"/datasets/task/information-retrieval"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["NIAN"],"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."}