{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:ATDCJ4OLJEN7H6TB4356DPOXCN","short_pith_number":"pith:ATDCJ4OL","schema_version":"1.0","canonical_sha256":"04c624f1cb491bf3fa61e6fbe1bdd7135b1d3b7144d38fc00ad8ef332b5b0033","source":{"kind":"arxiv","id":"1908.07388","version":1},"attestation_state":"computed","paper":{"title":"Cross-modal Zero-shot Hashing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Carlotta Domeniconi, Guoxian Yu, Jun Wang, Xiangliang Zhang, Xuanwu Liu, Zhao Li","submitted_at":"2019-08-19T07:14:41Z","abstract_excerpt":"Hashing has been widely studied for big data retrieval due to its low storage cost and fast query speed. Zero-shot hashing (ZSH) aims to learn a hashing model that is trained using only samples from seen categories, but can generalize well to samples of unseen categories. ZSH generally uses category attributes to seek a semantic embedding space to transfer knowledge from seen categories to unseen ones. As a result, it may perform poorly when labeled data are insufficient. ZSH methods are mainly designed for single-modality data, which prevents their application to the widely spread multi-modal"},"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":"1908.07388","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-19T07:14:41Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"62b96abf6eaaa11582433278530ed2ded7208c539eec186da79bf6040b5a5d9c","abstract_canon_sha256":"06726d893eabd47afe2ce127fec7d525dc00cfc63f325a0e4e67c2dbdf6126e1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:58:33.907761Z","signature_b64":"hUT+oSMi2dTnCcu/wuAeBTAEV1ngHcwpRJwmo8+IHumOvs6QCp4U0MRoQ8tKp9FGVmup/qKhilPuuqO/02lNBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"04c624f1cb491bf3fa61e6fbe1bdd7135b1d3b7144d38fc00ad8ef332b5b0033","last_reissued_at":"2026-07-04T23:58:33.907430Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:58:33.907430Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Cross-modal Zero-shot Hashing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Carlotta Domeniconi, Guoxian Yu, Jun Wang, Xiangliang Zhang, Xuanwu Liu, Zhao Li","submitted_at":"2019-08-19T07:14:41Z","abstract_excerpt":"Hashing has been widely studied for big data retrieval due to its low storage cost and fast query speed. Zero-shot hashing (ZSH) aims to learn a hashing model that is trained using only samples from seen categories, but can generalize well to samples of unseen categories. ZSH generally uses category attributes to seek a semantic embedding space to transfer knowledge from seen categories to unseen ones. As a result, it may perform poorly when labeled data are insufficient. ZSH methods are mainly designed for single-modality data, which prevents their application to the widely spread multi-modal"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.07388","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.07388/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":"1908.07388","created_at":"2026-07-04T23:58:33.907484+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.07388v1","created_at":"2026-07-04T23:58:33.907484+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.07388","created_at":"2026-07-04T23:58:33.907484+00:00"},{"alias_kind":"pith_short_12","alias_value":"ATDCJ4OLJEN7","created_at":"2026-07-04T23:58:33.907484+00:00"},{"alias_kind":"pith_short_16","alias_value":"ATDCJ4OLJEN7H6TB","created_at":"2026-07-04T23:58:33.907484+00:00"},{"alias_kind":"pith_short_8","alias_value":"ATDCJ4OL","created_at":"2026-07-04T23:58:33.907484+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/ATDCJ4OLJEN7H6TB4356DPOXCN","json":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN.json","graph_json":"https://pith.science/api/pith-number/ATDCJ4OLJEN7H6TB4356DPOXCN/graph.json","events_json":"https://pith.science/api/pith-number/ATDCJ4OLJEN7H6TB4356DPOXCN/events.json","paper":"https://pith.science/paper/ATDCJ4OL"},"agent_actions":{"view_html":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN","download_json":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN.json","view_paper":"https://pith.science/paper/ATDCJ4OL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.07388&json=true","fetch_graph":"https://pith.science/api/pith-number/ATDCJ4OLJEN7H6TB4356DPOXCN/graph.json","fetch_events":"https://pith.science/api/pith-number/ATDCJ4OLJEN7H6TB4356DPOXCN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN/action/storage_attestation","attest_author":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN/action/author_attestation","sign_citation":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN/action/citation_signature","submit_replication":"https://pith.science/pith/ATDCJ4OLJEN7H6TB4356DPOXCN/action/replication_record"}},"created_at":"2026-07-04T23:58:33.907484+00:00","updated_at":"2026-07-04T23:58:33.907484+00:00"}