{"url":"/sota/intent-detection-on-hwu64","task":{"name":"Intent Detection","url":"/task/intent-detection","note":null},"dataset":{"name":"HWU64","url":"/dataset/hwu64"},"category":"Natural Language Processing","categories":["Natural Language Processing"],"category_note":null,"description":"**Intent Detection** is a task of determining the underlying purpose or goal behind a user's search query given a context. The task plays a significant role in search and recommendations. \r\nA traditional approach for intent detection implies using an intent detector model to classify user search query into predefined intent categories, given a context.\r\nOne of the key challenges of the task implies identifying user intents for cold-start sessions, i.e., search sessions initiated by a non-logged-in\r\nor unrecognized user.\r\n\r\n<span class=\"description-source\">Source: [Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers](https://arxiv.org/abs/2012.08777)</span>\r\n<span class=\"description-source\">","description_from":"task","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","rank":"the archive's row order at snapshot; not re-ranked","rows_end_at":"2025-07-28","rows_withheld_as_spam":0,"metric_values":"the archive's strings, untouched"},"metrics":["Accuracy (%)"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"Accuracy (%)":"higher"}},"counts":{"rows":1,"rows_with_code":0,"rows_with_paper_page":1,"rows_dated":1,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"RoBERTa-Large + ICDA","metrics":{"Accuracy (%)":"92.57"},"uses_additional_data":false,"paper_date":"2023-02-10","paper":"/paper/selective-in-context-data-augmentation-for","paper_url":"https://arxiv.org/abs/2302.05096v1","paper_title":"Selective In-Context Data Augmentation for Intent Detection using Pointwise V-Information","code":null,"n_code_links":0,"syntology":null}],"since_archive":{"present":false,"note":"No Syntology-extracted rows are published in this build."},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per row: N of M harvested code samples from that row's paper executed on a synthesized fixture; the other M-N are unverified. Not a reproduction of the row's number; not a correctness claim. n_pointer_only_licence counts samples the site points at rather than redistributes (a licence axis, independent of ran/unverified).","rows_with_graph_line":0,"rows_with_any_sample_ran":0,"distinct_papers_with_graph_line":0,"distinct_papers_with_any_sample_ran":0,"samples_over_distinct_papers":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"row-weighted: a paper behind several rows is counted once per row; inflated relative to samples_over_distinct_papers by design, kept for readers summing the per-row syntology blocks"}}}