{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:YA64W3EX4YPCFRJ3LLS63SSBKP","short_pith_number":"pith:YA64W3EX","schema_version":"1.0","canonical_sha256":"c03dcb6c97e61e22c53b5ae5edca4153c92a6c90604d031c75f892bb99887a4a","source":{"kind":"arxiv","id":"1603.08754","version":1},"attestation_state":"computed","paper":{"title":"Multi-Cue Zero-Shot Learning with Strong Supervision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bernt Schiele, Mario Fritz, Mateusz Malinowski, Zeynep Akata","submitted_at":"2016-03-29T13:04:21Z","abstract_excerpt":"Scaling up visual category recognition to large numbers of classes remains challenging. A promising research direction is zero-shot learning, which does not require any training data to recognize new classes, but rather relies on some form of auxiliary information describing the new classes. Ultimately, this may allow to use textbook knowledge that humans employ to learn about new classes by transferring knowledge from classes they know well. The most successful zero-shot learning approaches currently require a particular type of auxiliary information -- namely attribute annotations performed "},"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":"1603.08754","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-03-29T13:04:21Z","cross_cats_sorted":[],"title_canon_sha256":"0ac22eb83fb0e8a052af646efd959e0709b6c8d66de3b3c5e06e6ae0c420e614","abstract_canon_sha256":"6c861a4854569491d8c1dec7d83c378ff86a89ece3209b5b7a21bce4f9f5a071"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:22.929069Z","signature_b64":"Z9Hoe68zuTkxMqBeI2uv8/BB9BApWK6vFoFAu6ClJHDUgTlDrDiH+h+VSLpCsyE+pPcewEPSjcFQWsnvGWDUDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c03dcb6c97e61e22c53b5ae5edca4153c92a6c90604d031c75f892bb99887a4a","last_reissued_at":"2026-05-18T01:17:22.928684Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:22.928684Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multi-Cue Zero-Shot Learning with Strong Supervision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bernt Schiele, Mario Fritz, Mateusz Malinowski, Zeynep Akata","submitted_at":"2016-03-29T13:04:21Z","abstract_excerpt":"Scaling up visual category recognition to large numbers of classes remains challenging. A promising research direction is zero-shot learning, which does not require any training data to recognize new classes, but rather relies on some form of auxiliary information describing the new classes. Ultimately, this may allow to use textbook knowledge that humans employ to learn about new classes by transferring knowledge from classes they know well. The most successful zero-shot learning approaches currently require a particular type of auxiliary information -- namely attribute annotations performed "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.08754","kind":"arxiv","version":1},"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":"1603.08754","created_at":"2026-05-18T01:17:22.928742+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.08754v1","created_at":"2026-05-18T01:17:22.928742+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.08754","created_at":"2026-05-18T01:17:22.928742+00:00"},{"alias_kind":"pith_short_12","alias_value":"YA64W3EX4YPC","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_16","alias_value":"YA64W3EX4YPCFRJ3","created_at":"2026-05-18T12:30:53.716459+00:00"},{"alias_kind":"pith_short_8","alias_value":"YA64W3EX","created_at":"2026-05-18T12:30:53.716459+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/YA64W3EX4YPCFRJ3LLS63SSBKP","json":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP.json","graph_json":"https://pith.science/api/pith-number/YA64W3EX4YPCFRJ3LLS63SSBKP/graph.json","events_json":"https://pith.science/api/pith-number/YA64W3EX4YPCFRJ3LLS63SSBKP/events.json","paper":"https://pith.science/paper/YA64W3EX"},"agent_actions":{"view_html":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP","download_json":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP.json","view_paper":"https://pith.science/paper/YA64W3EX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.08754&json=true","fetch_graph":"https://pith.science/api/pith-number/YA64W3EX4YPCFRJ3LLS63SSBKP/graph.json","fetch_events":"https://pith.science/api/pith-number/YA64W3EX4YPCFRJ3LLS63SSBKP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP/action/storage_attestation","attest_author":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP/action/author_attestation","sign_citation":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP/action/citation_signature","submit_replication":"https://pith.science/pith/YA64W3EX4YPCFRJ3LLS63SSBKP/action/replication_record"}},"created_at":"2026-05-18T01:17:22.928742+00:00","updated_at":"2026-05-18T01:17:22.928742+00:00"}