{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:JWKDKVUWWL3PY4QVLOYQGGXQFT","short_pith_number":"pith:JWKDKVUW","schema_version":"1.0","canonical_sha256":"4d94355696b2f6fc72155bb1031af02ce8cdace0110007be809c8448d1710237","source":{"kind":"arxiv","id":"1707.01922","version":5},"attestation_state":"computed","paper":{"title":"Zero-Shot Deep Domain Adaptation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jan Ernst, Kuan-Chuan Peng, Ziyan Wu","submitted_at":"2017-07-06T18:09:36Z","abstract_excerpt":"Domain adaptation is an important tool to transfer knowledge about a task (e.g. classification) learned in a source domain to a second, or target domain. Current approaches assume that task-relevant target-domain data is available during training. We demonstrate how to perform domain adaptation when no such task-relevant target-domain data is available. To tackle this issue, we propose zero-shot deep domain adaptation (ZDDA), which uses privileged information from task-irrelevant dual-domain pairs. ZDDA learns a source-domain representation which is not only tailored for the task of interest b"},"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":"1707.01922","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-06T18:09:36Z","cross_cats_sorted":[],"title_canon_sha256":"7a616bd55237a0d84eb6896544a297df0d3481eee60b2f4947070fa9280a727c","abstract_canon_sha256":"8a60a53f73db53abb22d3db07dc545408356b9ed9acfd4c4544b848f0c39606c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:04.154017Z","signature_b64":"qT3SF4dbGQs5pTlqSLe7J4D3JYlb7jI0i8LGdsXr2lM+ftIKeI9gWKUukcgQxsd/2q7fGVVA66iYWdUK6757Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d94355696b2f6fc72155bb1031af02ce8cdace0110007be809c8448d1710237","last_reissued_at":"2026-05-18T00:10:04.153213Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:04.153213Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Zero-Shot Deep Domain Adaptation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jan Ernst, Kuan-Chuan Peng, Ziyan Wu","submitted_at":"2017-07-06T18:09:36Z","abstract_excerpt":"Domain adaptation is an important tool to transfer knowledge about a task (e.g. classification) learned in a source domain to a second, or target domain. Current approaches assume that task-relevant target-domain data is available during training. We demonstrate how to perform domain adaptation when no such task-relevant target-domain data is available. To tackle this issue, we propose zero-shot deep domain adaptation (ZDDA), which uses privileged information from task-irrelevant dual-domain pairs. ZDDA learns a source-domain representation which is not only tailored for the task of interest b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.01922","kind":"arxiv","version":5},"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":"1707.01922","created_at":"2026-05-18T00:10:04.153366+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.01922v5","created_at":"2026-05-18T00:10:04.153366+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.01922","created_at":"2026-05-18T00:10:04.153366+00:00"},{"alias_kind":"pith_short_12","alias_value":"JWKDKVUWWL3P","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_16","alias_value":"JWKDKVUWWL3PY4QV","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_8","alias_value":"JWKDKVUW","created_at":"2026-05-18T12:31:24.725408+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/JWKDKVUWWL3PY4QVLOYQGGXQFT","json":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT.json","graph_json":"https://pith.science/api/pith-number/JWKDKVUWWL3PY4QVLOYQGGXQFT/graph.json","events_json":"https://pith.science/api/pith-number/JWKDKVUWWL3PY4QVLOYQGGXQFT/events.json","paper":"https://pith.science/paper/JWKDKVUW"},"agent_actions":{"view_html":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT","download_json":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT.json","view_paper":"https://pith.science/paper/JWKDKVUW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.01922&json=true","fetch_graph":"https://pith.science/api/pith-number/JWKDKVUWWL3PY4QVLOYQGGXQFT/graph.json","fetch_events":"https://pith.science/api/pith-number/JWKDKVUWWL3PY4QVLOYQGGXQFT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT/action/storage_attestation","attest_author":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT/action/author_attestation","sign_citation":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT/action/citation_signature","submit_replication":"https://pith.science/pith/JWKDKVUWWL3PY4QVLOYQGGXQFT/action/replication_record"}},"created_at":"2026-05-18T00:10:04.153366+00:00","updated_at":"2026-05-18T00:10:04.153366+00:00"}