{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:KCUE5RY2BJLUPNET5PFEVIH6BT","short_pith_number":"pith:KCUE5RY2","schema_version":"1.0","canonical_sha256":"50a84ec71a0a5747b493ebca4aa0fe0cd1c56474ac7f5027f4bd51c20f45b308","source":{"kind":"arxiv","id":"1809.00852","version":2},"attestation_state":"computed","paper":{"title":"Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Huanhuan Yu, Menglei Hu, Songcan Chen","submitted_at":"2018-09-04T09:18:19Z","abstract_excerpt":"Unsupervised domain adaptation (UDA) aims to learn the unlabeled target domain by transferring the knowledge of the labeled source domain. To date, most of the existing works focus on the scenario of one source domain and one target domain (1S1T), and just a few works concern the scenario of multiple source domains and one target domain (mS1T). While, to the best of our knowledge, almost no work concerns the scenario of one source domain and multiple target domains (1SmT), in which these unlabeled target domains may not necessarily share the same categories, therefore, contrasting to mS1T, 1Sm"},"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":"1809.00852","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-04T09:18:19Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"44edb8213d6948de4b5d6ba30ca193ed0330fa5605c194fff7c5ad04233183f1","abstract_canon_sha256":"9a7e8fa1b5dc84630f473daaa0898eecf67385a42da133079b1df2532d8a04d0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:05:36.841302Z","signature_b64":"q77onqdpkbhIkUvt14Ufg6bjTt6wEM+fB6Scdav9Q/BfTNg+YqCUnLA9aha6k+9yg5ipdYlPDNIbfIOJ14yiDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"50a84ec71a0a5747b493ebca4aa0fe0cd1c56474ac7f5027f4bd51c20f45b308","last_reissued_at":"2026-05-18T00:05:36.840865Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:05:36.840865Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Huanhuan Yu, Menglei Hu, Songcan Chen","submitted_at":"2018-09-04T09:18:19Z","abstract_excerpt":"Unsupervised domain adaptation (UDA) aims to learn the unlabeled target domain by transferring the knowledge of the labeled source domain. To date, most of the existing works focus on the scenario of one source domain and one target domain (1S1T), and just a few works concern the scenario of multiple source domains and one target domain (mS1T). While, to the best of our knowledge, almost no work concerns the scenario of one source domain and multiple target domains (1SmT), in which these unlabeled target domains may not necessarily share the same categories, therefore, contrasting to mS1T, 1Sm"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.00852","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":""},"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":"1809.00852","created_at":"2026-05-18T00:05:36.840933+00:00"},{"alias_kind":"arxiv_version","alias_value":"1809.00852v2","created_at":"2026-05-18T00:05:36.840933+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.00852","created_at":"2026-05-18T00:05:36.840933+00:00"},{"alias_kind":"pith_short_12","alias_value":"KCUE5RY2BJLU","created_at":"2026-05-18T12:32:33.847187+00:00"},{"alias_kind":"pith_short_16","alias_value":"KCUE5RY2BJLUPNET","created_at":"2026-05-18T12:32:33.847187+00:00"},{"alias_kind":"pith_short_8","alias_value":"KCUE5RY2","created_at":"2026-05-18T12:32:33.847187+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/KCUE5RY2BJLUPNET5PFEVIH6BT","json":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT.json","graph_json":"https://pith.science/api/pith-number/KCUE5RY2BJLUPNET5PFEVIH6BT/graph.json","events_json":"https://pith.science/api/pith-number/KCUE5RY2BJLUPNET5PFEVIH6BT/events.json","paper":"https://pith.science/paper/KCUE5RY2"},"agent_actions":{"view_html":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT","download_json":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT.json","view_paper":"https://pith.science/paper/KCUE5RY2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1809.00852&json=true","fetch_graph":"https://pith.science/api/pith-number/KCUE5RY2BJLUPNET5PFEVIH6BT/graph.json","fetch_events":"https://pith.science/api/pith-number/KCUE5RY2BJLUPNET5PFEVIH6BT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT/action/storage_attestation","attest_author":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT/action/author_attestation","sign_citation":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT/action/citation_signature","submit_replication":"https://pith.science/pith/KCUE5RY2BJLUPNET5PFEVIH6BT/action/replication_record"}},"created_at":"2026-05-18T00:05:36.840933+00:00","updated_at":"2026-05-18T00:05:36.840933+00:00"}