{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:U7UKCDF2Q3OZ72PGGRPGDAKONL","short_pith_number":"pith:U7UKCDF2","canonical_record":{"source":{"id":"2408.15857","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-28T15:18:46Z","cross_cats_sorted":[],"title_canon_sha256":"56d7f64e53589999280094f5663afa3d350c22857f368168f133df9a40e8862a","abstract_canon_sha256":"d68bc807b073959c5cec6203b4b8af3fcc6f33b6070c39dbcebe092b88acce89"},"schema_version":"1.0"},"canonical_sha256":"a7e8a10cba86dd9fe9e6345e61814e6ad472cf3b1c4cc3f6a6f5bb444f0d9d2a","source":{"kind":"arxiv","id":"2408.15857","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.15857","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"arxiv_version","alias_value":"2408.15857v1","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.15857","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"pith_short_12","alias_value":"U7UKCDF2Q3OZ","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"pith_short_16","alias_value":"U7UKCDF2Q3OZ72PG","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"pith_short_8","alias_value":"U7UKCDF2","created_at":"2026-07-05T09:00:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:U7UKCDF2Q3OZ72PGGRPGDAKONL","target":"record","payload":{"canonical_record":{"source":{"id":"2408.15857","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-28T15:18:46Z","cross_cats_sorted":[],"title_canon_sha256":"56d7f64e53589999280094f5663afa3d350c22857f368168f133df9a40e8862a","abstract_canon_sha256":"d68bc807b073959c5cec6203b4b8af3fcc6f33b6070c39dbcebe092b88acce89"},"schema_version":"1.0"},"canonical_sha256":"a7e8a10cba86dd9fe9e6345e61814e6ad472cf3b1c4cc3f6a6f5bb444f0d9d2a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:00:18.593530Z","signature_b64":"+dE2IA+59iF4EyKrCGD04e6Gg1KKHMrNzMuHZXSAYawjDQndy9kuHe0qjhZ+CAKvhqXqshtbluAtKINDeZ9wAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7e8a10cba86dd9fe9e6345e61814e6ad472cf3b1c4cc3f6a6f5bb444f0d9d2a","last_reissued_at":"2026-07-05T09:00:18.593052Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:00:18.593052Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.15857","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:00:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WpcmPmqFC+XFiG2azWGygDiNwOVmoNbVZkRTiNUS04uI0JczVkL/STLrm0QHd6Fle7sSjHoxp7CQH9XQEJEHDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:48:28.031457Z"},"content_sha256":"f9e54b987083bd54b984546a9f143143adb9b0640748239a681355a301972244","schema_version":"1.0","event_id":"sha256:f9e54b987083bd54b984546a9f143143adb9b0640748239a681355a301972244"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:U7UKCDF2Q3OZ72PGGRPGDAKONL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"What is YOLOv8: An In-Depth Exploration of the Internal Features of the Next-Generation Object Detector","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Muhammad Yaseen","submitted_at":"2024-08-28T15:18:46Z","abstract_excerpt":"This study presents a detailed analysis of the YOLOv8 object detection model, focusing on its architecture, training techniques, and performance improvements over previous iterations like YOLOv5. Key innovations, including the CSPNet backbone for enhanced feature extraction, the FPN+PAN neck for superior multi-scale object detection, and the transition to an anchor-free approach, are thoroughly examined. The paper reviews YOLOv8's performance across benchmarks like Microsoft COCO and Roboflow 100, highlighting its high accuracy and real-time capabilities across diverse hardware platforms. Addi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.15857","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/2408.15857/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:00:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+Jn+oR7gEU8wFsGRbqHyAKC+pxqKgEHlzIQ3FaQhuUDqX8zP/DXTfVXuKKDjrzvrUzFoE2NyZ8BXvBs1l8nvBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:48:28.032021Z"},"content_sha256":"b99dd393930685fcb1ab03403f20800d6b1d051bb1d8c4f4cb24a684c4c216df","schema_version":"1.0","event_id":"sha256:b99dd393930685fcb1ab03403f20800d6b1d051bb1d8c4f4cb24a684c4c216df"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U7UKCDF2Q3OZ72PGGRPGDAKONL/bundle.json","state_url":"https://pith.science/pith/U7UKCDF2Q3OZ72PGGRPGDAKONL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U7UKCDF2Q3OZ72PGGRPGDAKONL/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T15:48:28Z","links":{"resolver":"https://pith.science/pith/U7UKCDF2Q3OZ72PGGRPGDAKONL","bundle":"https://pith.science/pith/U7UKCDF2Q3OZ72PGGRPGDAKONL/bundle.json","state":"https://pith.science/pith/U7UKCDF2Q3OZ72PGGRPGDAKONL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U7UKCDF2Q3OZ72PGGRPGDAKONL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:U7UKCDF2Q3OZ72PGGRPGDAKONL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"d68bc807b073959c5cec6203b4b8af3fcc6f33b6070c39dbcebe092b88acce89","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-28T15:18:46Z","title_canon_sha256":"56d7f64e53589999280094f5663afa3d350c22857f368168f133df9a40e8862a"},"schema_version":"1.0","source":{"id":"2408.15857","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.15857","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"arxiv_version","alias_value":"2408.15857v1","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.15857","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"pith_short_12","alias_value":"U7UKCDF2Q3OZ","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"pith_short_16","alias_value":"U7UKCDF2Q3OZ72PG","created_at":"2026-07-05T09:00:18Z"},{"alias_kind":"pith_short_8","alias_value":"U7UKCDF2","created_at":"2026-07-05T09:00:18Z"}],"graph_snapshots":[{"event_id":"sha256:b99dd393930685fcb1ab03403f20800d6b1d051bb1d8c4f4cb24a684c4c216df","target":"graph","created_at":"2026-07-05T09:00:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2408.15857/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study presents a detailed analysis of the YOLOv8 object detection model, focusing on its architecture, training techniques, and performance improvements over previous iterations like YOLOv5. Key innovations, including the CSPNet backbone for enhanced feature extraction, the FPN+PAN neck for superior multi-scale object detection, and the transition to an anchor-free approach, are thoroughly examined. The paper reviews YOLOv8's performance across benchmarks like Microsoft COCO and Roboflow 100, highlighting its high accuracy and real-time capabilities across diverse hardware platforms. Addi","authors_text":"Muhammad Yaseen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-28T15:18:46Z","title":"What is YOLOv8: An In-Depth Exploration of the Internal Features of the Next-Generation Object Detector"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.15857","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:f9e54b987083bd54b984546a9f143143adb9b0640748239a681355a301972244","target":"record","created_at":"2026-07-05T09:00:18Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"d68bc807b073959c5cec6203b4b8af3fcc6f33b6070c39dbcebe092b88acce89","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-28T15:18:46Z","title_canon_sha256":"56d7f64e53589999280094f5663afa3d350c22857f368168f133df9a40e8862a"},"schema_version":"1.0","source":{"id":"2408.15857","kind":"arxiv","version":1}},"canonical_sha256":"a7e8a10cba86dd9fe9e6345e61814e6ad472cf3b1c4cc3f6a6f5bb444f0d9d2a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a7e8a10cba86dd9fe9e6345e61814e6ad472cf3b1c4cc3f6a6f5bb444f0d9d2a","first_computed_at":"2026-07-05T09:00:18.593052Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:00:18.593052Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+dE2IA+59iF4EyKrCGD04e6Gg1KKHMrNzMuHZXSAYawjDQndy9kuHe0qjhZ+CAKvhqXqshtbluAtKINDeZ9wAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:00:18.593530Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.15857","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f9e54b987083bd54b984546a9f143143adb9b0640748239a681355a301972244","sha256:b99dd393930685fcb1ab03403f20800d6b1d051bb1d8c4f4cb24a684c4c216df"],"state_sha256":"31f09e575cf2f6677c50eed6caaa764f5abfc3c06894e7a4aa7d62bfe00a7b1a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GX+j+oGpOEWFIg6iZtztZISHM5cG9qE8GCPu6MY/IjE913fS+VVJIJhoh4HTXC8N++XiNPu19dns5o7W+mEECQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:48:28.036389Z","bundle_sha256":"394a16d0ef6bafe3d8d6dab2c58b098a891e0204587b053faba8cb7ec79ddd29"}}