{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:SKPMNCWSDKYIPJEETIRO4MX773","short_pith_number":"pith:SKPMNCWS","schema_version":"1.0","canonical_sha256":"929ec68ad21ab087a4849a22ee32fffee50180caac9d0c1c75e0d28449fb188d","source":{"kind":"arxiv","id":"2109.02344","version":2},"attestation_state":"computed","paper":{"title":"Information Theory-Guided Heuristic Progressive Multi-View Coding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Bing Su, Changwen Zheng, Farid Razzak, Hang Gao, Hui Xiong, Jiangmeng Li, Jie Hu, Wenwen Qiang","submitted_at":"2021-09-06T10:32:24Z","abstract_excerpt":"Multi-view representation learning captures comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning (CL) to learn representations, regarded as a pairwise manner, which is still scalable: view-specific noise is not filtered in learning view-shared representations; the fake negative pairs, where the negative terms are actually within the same class as the positive, and the real negative pairs are coequally treated; and evenly measuring the similarities between terms might interfere with optimization. Importantly, few works research t"},"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":"2109.02344","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-09-06T10:32:24Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"329feae5b135757e180447fceea7e55878e547ddbde12d8b5dc53f62b0af5b57","abstract_canon_sha256":"2864d29bdf30a34f756becc0428f20ba1f33fd754d78d81f2c468478e20a5562"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:43:16.688630Z","signature_b64":"BYrshaZmwS2lwBMyY/nMytuby4OJnjgFwU5gzaj9tZlUAnz9jHJc1VLCCzx6INGC3BAyoCGS/SOltaYD4MaIAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"929ec68ad21ab087a4849a22ee32fffee50180caac9d0c1c75e0d28449fb188d","last_reissued_at":"2026-07-05T06:43:16.688154Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:43:16.688154Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Information Theory-Guided Heuristic Progressive Multi-View Coding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CV","authors_text":"Bing Su, Changwen Zheng, Farid Razzak, Hang Gao, Hui Xiong, Jiangmeng Li, Jie Hu, Wenwen Qiang","submitted_at":"2021-09-06T10:32:24Z","abstract_excerpt":"Multi-view representation learning captures comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning (CL) to learn representations, regarded as a pairwise manner, which is still scalable: view-specific noise is not filtered in learning view-shared representations; the fake negative pairs, where the negative terms are actually within the same class as the positive, and the real negative pairs are coequally treated; and evenly measuring the similarities between terms might interfere with optimization. Importantly, few works research t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.02344","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2109.02344/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":"2109.02344","created_at":"2026-07-05T06:43:16.688210+00:00"},{"alias_kind":"arxiv_version","alias_value":"2109.02344v2","created_at":"2026-07-05T06:43:16.688210+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.02344","created_at":"2026-07-05T06:43:16.688210+00:00"},{"alias_kind":"pith_short_12","alias_value":"SKPMNCWSDKYI","created_at":"2026-07-05T06:43:16.688210+00:00"},{"alias_kind":"pith_short_16","alias_value":"SKPMNCWSDKYIPJEE","created_at":"2026-07-05T06:43:16.688210+00:00"},{"alias_kind":"pith_short_8","alias_value":"SKPMNCWS","created_at":"2026-07-05T06:43:16.688210+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/SKPMNCWSDKYIPJEETIRO4MX773","json":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773.json","graph_json":"https://pith.science/api/pith-number/SKPMNCWSDKYIPJEETIRO4MX773/graph.json","events_json":"https://pith.science/api/pith-number/SKPMNCWSDKYIPJEETIRO4MX773/events.json","paper":"https://pith.science/paper/SKPMNCWS"},"agent_actions":{"view_html":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773","download_json":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773.json","view_paper":"https://pith.science/paper/SKPMNCWS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2109.02344&json=true","fetch_graph":"https://pith.science/api/pith-number/SKPMNCWSDKYIPJEETIRO4MX773/graph.json","fetch_events":"https://pith.science/api/pith-number/SKPMNCWSDKYIPJEETIRO4MX773/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773/action/storage_attestation","attest_author":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773/action/author_attestation","sign_citation":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773/action/citation_signature","submit_replication":"https://pith.science/pith/SKPMNCWSDKYIPJEETIRO4MX773/action/replication_record"}},"created_at":"2026-07-05T06:43:16.688210+00:00","updated_at":"2026-07-05T06:43:16.688210+00:00"}