{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:AN2FTSSCRUXGK75XO2UVSFYIJD","short_pith_number":"pith:AN2FTSSC","schema_version":"1.0","canonical_sha256":"037459ca428d2e657fb776a959170848c8ff589b0004dacbfe2c353147297fd1","source":{"kind":"arxiv","id":"2201.02609","version":2},"attestation_state":"computed","paper":{"title":"Generalized Category Discovery","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Andrea Vedaldi, Andrew Zisserman, Kai Han, Sagar Vaze","submitted_at":"2022-01-07T18:58:35Z","abstract_excerpt":"In this paper, we consider a highly general image recognition setting wherein, given a labelled and unlabelled set of images, the task is to categorize all images in the unlabelled set. Here, the unlabelled images may come from labelled classes or from novel ones. Existing recognition methods are not able to deal with this setting, because they make several restrictive assumptions, such as the unlabelled instances only coming from known - or unknown - classes, and the number of unknown classes being known a-priori. We address the more unconstrained setting, naming it 'Generalized Category Disc"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2201.02609","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-01-07T18:58:35Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"f5332e0bf9539a585aa61c579dce8376caa923265f9aec48738069cb5f0cba5c","abstract_canon_sha256":"413d4b3d94db9ff049d38f547fd56a83d744520f44f1868e84a84e70653db140"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:32:54.570554Z","signature_b64":"JkrmTNElm9T0fOYrW0jjbptToMS4Tn9AbxQ53w7/L0B1AJwMQzxz1s4bORsow3AnRxAM+lksMHysV3BRZZLXAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"037459ca428d2e657fb776a959170848c8ff589b0004dacbfe2c353147297fd1","last_reissued_at":"2026-07-05T04:32:54.570120Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:32:54.570120Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Generalized Category Discovery","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Andrea Vedaldi, Andrew Zisserman, Kai Han, Sagar Vaze","submitted_at":"2022-01-07T18:58:35Z","abstract_excerpt":"In this paper, we consider a highly general image recognition setting wherein, given a labelled and unlabelled set of images, the task is to categorize all images in the unlabelled set. Here, the unlabelled images may come from labelled classes or from novel ones. Existing recognition methods are not able to deal with this setting, because they make several restrictive assumptions, such as the unlabelled instances only coming from known - or unknown - classes, and the number of unknown classes being known a-priori. We address the more unconstrained setting, naming it 'Generalized Category Disc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2201.02609","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2201.02609/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2201.02609","created_at":"2026-07-05T04:32:54.570173+00:00"},{"alias_kind":"arxiv_version","alias_value":"2201.02609v2","created_at":"2026-07-05T04:32:54.570173+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2201.02609","created_at":"2026-07-05T04:32:54.570173+00:00"},{"alias_kind":"pith_short_12","alias_value":"AN2FTSSCRUXG","created_at":"2026-07-05T04:32:54.570173+00:00"},{"alias_kind":"pith_short_16","alias_value":"AN2FTSSCRUXGK75X","created_at":"2026-07-05T04:32:54.570173+00:00"},{"alias_kind":"pith_short_8","alias_value":"AN2FTSSC","created_at":"2026-07-05T04:32:54.570173+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD","json":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD.json","graph_json":"https://pith.science/api/pith-number/AN2FTSSCRUXGK75XO2UVSFYIJD/graph.json","events_json":"https://pith.science/api/pith-number/AN2FTSSCRUXGK75XO2UVSFYIJD/events.json","paper":"https://pith.science/paper/AN2FTSSC"},"agent_actions":{"view_html":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD","download_json":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD.json","view_paper":"https://pith.science/paper/AN2FTSSC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2201.02609&json=true","fetch_graph":"https://pith.science/api/pith-number/AN2FTSSCRUXGK75XO2UVSFYIJD/graph.json","fetch_events":"https://pith.science/api/pith-number/AN2FTSSCRUXGK75XO2UVSFYIJD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD/action/storage_attestation","attest_author":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD/action/author_attestation","sign_citation":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD/action/citation_signature","submit_replication":"https://pith.science/pith/AN2FTSSCRUXGK75XO2UVSFYIJD/action/replication_record"}},"created_at":"2026-07-05T04:32:54.570173+00:00","updated_at":"2026-07-05T04:32:54.570173+00:00"}