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With margin loss, we can learn discriminative deep features by forcing the network to maximize inter-class variance and to minimize intra-class variance. Then, we feed the feature vectors to the density-based novelty detection algorithm, local outlier factor (LOF), to detect unknown intents. Experiments on two benchmark datasets show that our method can yield consistent improvements compared with the baseline methods.","url_abs":"https://arxiv.org/abs/1906.00434v1","url_pdf":"https://arxiv.org/pdf/1906.00434v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"190600434","repo_url":"https://github.com/thuiar/DeepUnkID","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"intent-detection","task_name":"Intent Detection"},{"task_slug":"novelty-detection","task_name":"Novelty Detection"},{"task_slug":"open-intent-detection","task_name":"Open Intent Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/open-intent-detection-on-atis-25-known","task":"Open Intent Detection","dataset":"ATIS (25% known)","model":"LMCL","rank_in_archive_order":1,"of":1,"metrics":{"F1":"0.696"},"uses_additional_data":false},{"leaderboard":"/sota/open-intent-detection-on-atis-50-known","task":"Open Intent Detection","dataset":"ATIS (50% known)","model":"LMCL","rank_in_archive_order":1,"of":1,"metrics":{"F1":"0.396"},"uses_additional_data":false},{"leaderboard":"/sota/open-intent-detection-on-snips-25-known","task":"Open Intent Detection","dataset":"SNIPS (25% known)","model":"LMCL","rank_in_archive_order":1,"of":1,"metrics":{"F1":"0.792"},"uses_additional_data":false},{"leaderboard":"/sota/open-intent-detection-on-snips-50-known","task":"Open Intent Detection","dataset":"SNIPS (50% known)","model":"LMCL","rank_in_archive_order":1,"of":1,"metrics":{"F1":"0.841"},"uses_additional_data":false},{"leaderboard":"/sota/open-intent-detection-on-snips-75-known","task":"Open Intent Detection","dataset":"SNIPS (75% known)","model":"LMCL","rank_in_archive_order":1,"of":1,"metrics":{"F1":"0.788"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1906.00434","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.00434"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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