{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:Q4AVAAXGAU7H6FQAMAQJHPMHXO","short_pith_number":"pith:Q4AVAAXG","schema_version":"1.0","canonical_sha256":"87015002e6053e7f1600602093bd87bb977cf119f743d8d4f5d5b4116ec172d9","source":{"kind":"arxiv","id":"2409.16774","version":1},"attestation_state":"computed","paper":{"title":"MixPolyp: Integrating Mask, Box and Scribble Supervision for Enhanced Polyp Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haoyang Li, Jun Wei, Shuguang Cui, Song Wu, Yiwen Hu, Yuncheng Jiang, Zhen Li","submitted_at":"2024-09-25T09:34:44Z","abstract_excerpt":"Limited by the expensive labeling, polyp segmentation models are plagued by data shortages. To tackle this, we propose the mixed supervised polyp segmentation paradigm (MixPolyp). Unlike traditional models relying on a single type of annotation, MixPolyp combines diverse annotation types (mask, box, and scribble) within a single model, thereby expanding the range of available data and reducing labeling costs. To achieve this, MixPolyp introduces three novel supervision losses to handle various annotations: Subspace Projection loss (L_SP), Binary Minimum Entropy loss (L_BME), and Linear Regular"},"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":"2409.16774","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-25T09:34:44Z","cross_cats_sorted":[],"title_canon_sha256":"f682f78b08a5059de3458b93671b2a060940410459c768a77fdc156543f2743f","abstract_canon_sha256":"4a8050863ef4e27ad7bcb8015c87018772c847e7e1e18ca5ae40271213923045"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:11:39.101178Z","signature_b64":"glgci4OYgqqyVOZGE2osY22BwvS9O1/lERgikVusD9dX5JIwPGePYx02RIsvs1WAIGa1/YSW2B1JgpSd9twHCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"87015002e6053e7f1600602093bd87bb977cf119f743d8d4f5d5b4116ec172d9","last_reissued_at":"2026-07-05T09:11:39.100711Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:11:39.100711Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MixPolyp: Integrating Mask, Box and Scribble Supervision for Enhanced Polyp Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haoyang Li, Jun Wei, Shuguang Cui, Song Wu, Yiwen Hu, Yuncheng Jiang, Zhen Li","submitted_at":"2024-09-25T09:34:44Z","abstract_excerpt":"Limited by the expensive labeling, polyp segmentation models are plagued by data shortages. To tackle this, we propose the mixed supervised polyp segmentation paradigm (MixPolyp). Unlike traditional models relying on a single type of annotation, MixPolyp combines diverse annotation types (mask, box, and scribble) within a single model, thereby expanding the range of available data and reducing labeling costs. To achieve this, MixPolyp introduces three novel supervision losses to handle various annotations: Subspace Projection loss (L_SP), Binary Minimum Entropy loss (L_BME), and Linear Regular"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.16774","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/2409.16774/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":"2409.16774","created_at":"2026-07-05T09:11:39.100769+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.16774v1","created_at":"2026-07-05T09:11:39.100769+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.16774","created_at":"2026-07-05T09:11:39.100769+00:00"},{"alias_kind":"pith_short_12","alias_value":"Q4AVAAXGAU7H","created_at":"2026-07-05T09:11:39.100769+00:00"},{"alias_kind":"pith_short_16","alias_value":"Q4AVAAXGAU7H6FQA","created_at":"2026-07-05T09:11:39.100769+00:00"},{"alias_kind":"pith_short_8","alias_value":"Q4AVAAXG","created_at":"2026-07-05T09:11:39.100769+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/Q4AVAAXGAU7H6FQAMAQJHPMHXO","json":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO.json","graph_json":"https://pith.science/api/pith-number/Q4AVAAXGAU7H6FQAMAQJHPMHXO/graph.json","events_json":"https://pith.science/api/pith-number/Q4AVAAXGAU7H6FQAMAQJHPMHXO/events.json","paper":"https://pith.science/paper/Q4AVAAXG"},"agent_actions":{"view_html":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO","download_json":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO.json","view_paper":"https://pith.science/paper/Q4AVAAXG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.16774&json=true","fetch_graph":"https://pith.science/api/pith-number/Q4AVAAXGAU7H6FQAMAQJHPMHXO/graph.json","fetch_events":"https://pith.science/api/pith-number/Q4AVAAXGAU7H6FQAMAQJHPMHXO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO/action/storage_attestation","attest_author":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO/action/author_attestation","sign_citation":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO/action/citation_signature","submit_replication":"https://pith.science/pith/Q4AVAAXGAU7H6FQAMAQJHPMHXO/action/replication_record"}},"created_at":"2026-07-05T09:11:39.100769+00:00","updated_at":"2026-07-05T09:11:39.100769+00:00"}