{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:3HAVB5MHP7NBRFTYCAPFWTLI3H","short_pith_number":"pith:3HAVB5MH","schema_version":"1.0","canonical_sha256":"d9c150f5877fda189678101e5b4d68d9c6bd990c882b6281b1ab9d019ac743e4","source":{"kind":"arxiv","id":"2504.11995","version":1},"attestation_state":"computed","paper":{"title":"A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Muhammad Hussain, Rahima Khanam","submitted_at":"2025-04-16T11:40:55Z","abstract_excerpt":"The YOLO (You Only Look Once) series has been a leading framework in real-time object detection, consistently improving the balance between speed and accuracy. However, integrating attention mechanisms into YOLO has been challenging due to their high computational overhead. YOLOv12 introduces a novel approach that successfully incorporates attention-based enhancements while preserving real-time performance. This paper provides a comprehensive review of YOLOv12's architectural innovations, including Area Attention for computationally efficient self-attention, Residual Efficient Layer Aggregatio"},"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":"2504.11995","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-16T11:40:55Z","cross_cats_sorted":[],"title_canon_sha256":"bc9b049dd43231fcab6583b4e06b65aaf5f81775479ee9aeea89eced42dc7f89","abstract_canon_sha256":"f673d8d9ce40e86f8827a88d8e8f98efb547d9c999af0550623e6eaba08c00d3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:50:00.938813Z","signature_b64":"nqMenJIO2zdBsUqLAyj+9IfUlP4EIhdoQ41L7n0NfjhQwhjUZ5azyyw+GRu6iwoESPw33x0NHppRKZTM33RoBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d9c150f5877fda189678101e5b4d68d9c6bd990c882b6281b1ab9d019ac743e4","last_reissued_at":"2026-07-05T10:50:00.938380Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:50:00.938380Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Review of YOLOv12: Attention-Based Enhancements vs. Previous Versions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Muhammad Hussain, Rahima Khanam","submitted_at":"2025-04-16T11:40:55Z","abstract_excerpt":"The YOLO (You Only Look Once) series has been a leading framework in real-time object detection, consistently improving the balance between speed and accuracy. However, integrating attention mechanisms into YOLO has been challenging due to their high computational overhead. YOLOv12 introduces a novel approach that successfully incorporates attention-based enhancements while preserving real-time performance. This paper provides a comprehensive review of YOLOv12's architectural innovations, including Area Attention for computationally efficient self-attention, Residual Efficient Layer Aggregatio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.11995","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/2504.11995/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":"2504.11995","created_at":"2026-07-05T10:50:00.938438+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.11995v1","created_at":"2026-07-05T10:50:00.938438+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.11995","created_at":"2026-07-05T10:50:00.938438+00:00"},{"alias_kind":"pith_short_12","alias_value":"3HAVB5MHP7NB","created_at":"2026-07-05T10:50:00.938438+00:00"},{"alias_kind":"pith_short_16","alias_value":"3HAVB5MHP7NBRFTY","created_at":"2026-07-05T10:50:00.938438+00:00"},{"alias_kind":"pith_short_8","alias_value":"3HAVB5MH","created_at":"2026-07-05T10:50:00.938438+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/3HAVB5MHP7NBRFTYCAPFWTLI3H","json":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H.json","graph_json":"https://pith.science/api/pith-number/3HAVB5MHP7NBRFTYCAPFWTLI3H/graph.json","events_json":"https://pith.science/api/pith-number/3HAVB5MHP7NBRFTYCAPFWTLI3H/events.json","paper":"https://pith.science/paper/3HAVB5MH"},"agent_actions":{"view_html":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H","download_json":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H.json","view_paper":"https://pith.science/paper/3HAVB5MH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.11995&json=true","fetch_graph":"https://pith.science/api/pith-number/3HAVB5MHP7NBRFTYCAPFWTLI3H/graph.json","fetch_events":"https://pith.science/api/pith-number/3HAVB5MHP7NBRFTYCAPFWTLI3H/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H/action/storage_attestation","attest_author":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H/action/author_attestation","sign_citation":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H/action/citation_signature","submit_replication":"https://pith.science/pith/3HAVB5MHP7NBRFTYCAPFWTLI3H/action/replication_record"}},"created_at":"2026-07-05T10:50:00.938438+00:00","updated_at":"2026-07-05T10:50:00.938438+00:00"}