{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:2GNVNCPXLBGY64CJ42AJ6OMNC2","short_pith_number":"pith:2GNVNCPX","schema_version":"1.0","canonical_sha256":"d19b5689f7584d8f7049e6809f398d16a76ef3cee978777c8a50479d99897b89","source":{"kind":"arxiv","id":"2305.04072","version":1},"attestation_state":"computed","paper":{"title":"Keyword-Based Diverse Image Retrieval by Semantics-aware Contrastive Learning and Transformer","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Dongliang Liao, Huanzhong Duan, Jinpeng Wang, Minyi Zhao, Shuigeng Zhou, Yiru Wang","submitted_at":"2023-05-06T15:26:05Z","abstract_excerpt":"In addition to relevance, diversity is an important yet less studied performance metric of cross-modal image retrieval systems, which is critical to user experience. Existing solutions for diversity-aware image retrieval either explicitly post-process the raw retrieval results from standard retrieval systems or try to learn multi-vector representations of images to represent their diverse semantics. However, neither of them is good enough to balance relevance and diversity. On the one hand, standard retrieval systems are usually biased to common semantics and seldom exploit diversity-aware reg"},"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":"2305.04072","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IR","submitted_at":"2023-05-06T15:26:05Z","cross_cats_sorted":[],"title_canon_sha256":"078c8b3cfb0c0ea56a3e2c49e63f2b0290cbc57d942326011fa111cd0a6346e4","abstract_canon_sha256":"b47a8787454853d8ca32cbe8b5dc79cc83bac5aaab8babb10dcbe3b871739269"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:07:44.530413Z","signature_b64":"aH2ELA0fUxAHZVU+4GTej1XaP5/E/Ia7FYx5KDx2orKUFyF7kULjYBzUcP4cFxSnOSEFgzVnQDv5t7C7rYqwDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d19b5689f7584d8f7049e6809f398d16a76ef3cee978777c8a50479d99897b89","last_reissued_at":"2026-07-05T06:07:44.529970Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:07:44.529970Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Keyword-Based Diverse Image Retrieval by Semantics-aware Contrastive Learning and Transformer","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Dongliang Liao, Huanzhong Duan, Jinpeng Wang, Minyi Zhao, Shuigeng Zhou, Yiru Wang","submitted_at":"2023-05-06T15:26:05Z","abstract_excerpt":"In addition to relevance, diversity is an important yet less studied performance metric of cross-modal image retrieval systems, which is critical to user experience. Existing solutions for diversity-aware image retrieval either explicitly post-process the raw retrieval results from standard retrieval systems or try to learn multi-vector representations of images to represent their diverse semantics. However, neither of them is good enough to balance relevance and diversity. On the one hand, standard retrieval systems are usually biased to common semantics and seldom exploit diversity-aware reg"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.04072","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/2305.04072/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":"2305.04072","created_at":"2026-07-05T06:07:44.530036+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.04072v1","created_at":"2026-07-05T06:07:44.530036+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.04072","created_at":"2026-07-05T06:07:44.530036+00:00"},{"alias_kind":"pith_short_12","alias_value":"2GNVNCPXLBGY","created_at":"2026-07-05T06:07:44.530036+00:00"},{"alias_kind":"pith_short_16","alias_value":"2GNVNCPXLBGY64CJ","created_at":"2026-07-05T06:07:44.530036+00:00"},{"alias_kind":"pith_short_8","alias_value":"2GNVNCPX","created_at":"2026-07-05T06:07:44.530036+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/2GNVNCPXLBGY64CJ42AJ6OMNC2","json":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2.json","graph_json":"https://pith.science/api/pith-number/2GNVNCPXLBGY64CJ42AJ6OMNC2/graph.json","events_json":"https://pith.science/api/pith-number/2GNVNCPXLBGY64CJ42AJ6OMNC2/events.json","paper":"https://pith.science/paper/2GNVNCPX"},"agent_actions":{"view_html":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2","download_json":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2.json","view_paper":"https://pith.science/paper/2GNVNCPX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.04072&json=true","fetch_graph":"https://pith.science/api/pith-number/2GNVNCPXLBGY64CJ42AJ6OMNC2/graph.json","fetch_events":"https://pith.science/api/pith-number/2GNVNCPXLBGY64CJ42AJ6OMNC2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2/action/storage_attestation","attest_author":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2/action/author_attestation","sign_citation":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2/action/citation_signature","submit_replication":"https://pith.science/pith/2GNVNCPXLBGY64CJ42AJ6OMNC2/action/replication_record"}},"created_at":"2026-07-05T06:07:44.530036+00:00","updated_at":"2026-07-05T06:07:44.530036+00:00"}