{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4WWEGNLV5I3CWPKTPX2G3HP7EE","short_pith_number":"pith:4WWEGNLV","canonical_record":{"source":{"id":"2508.07028","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-09T15:53:19Z","cross_cats_sorted":[],"title_canon_sha256":"c70e687023a4b18543dad64046c48804a8f81b60929a855dcc7b917bf94f30a0","abstract_canon_sha256":"fb8909a0795901e98ac1d63e67ab96de49d459cf60266f7a3b1122d82ec67149"},"schema_version":"1.0"},"canonical_sha256":"e5ac433575ea362b3d537df46d9dff212c44487d58611c1dfcc4c39012d697f6","source":{"kind":"arxiv","id":"2508.07028","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.07028","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"arxiv_version","alias_value":"2508.07028v1","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.07028","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"pith_short_12","alias_value":"4WWEGNLV5I3C","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"pith_short_16","alias_value":"4WWEGNLV5I3CWPKT","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"pith_short_8","alias_value":"4WWEGNLV","created_at":"2026-07-05T11:51:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4WWEGNLV5I3CWPKTPX2G3HP7EE","target":"record","payload":{"canonical_record":{"source":{"id":"2508.07028","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-09T15:53:19Z","cross_cats_sorted":[],"title_canon_sha256":"c70e687023a4b18543dad64046c48804a8f81b60929a855dcc7b917bf94f30a0","abstract_canon_sha256":"fb8909a0795901e98ac1d63e67ab96de49d459cf60266f7a3b1122d82ec67149"},"schema_version":"1.0"},"canonical_sha256":"e5ac433575ea362b3d537df46d9dff212c44487d58611c1dfcc4c39012d697f6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:51:39.580807Z","signature_b64":"YvYmrLxJgEK554BnoNxIWmHlBnqgmfC4IeNzOK2HX3WhBBmztRV4wKDpx+OFQ1BTbg/3FcQZhRJWvp2KqSpmAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e5ac433575ea362b3d537df46d9dff212c44487d58611c1dfcc4c39012d697f6","last_reissued_at":"2026-07-05T11:51:39.580340Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:51:39.580340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.07028","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":"2026-07-05T11:51:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXS5m0bTVJGGrD21KFcZE8VH942KJPJy3ftfposVCbzC7qdid8H4mv1FVec1wRGcX+6SBSnEiiE3D2amJZeJBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:29:59.155193Z"},"content_sha256":"022394915f6dc15e68f0b2663cf3b87184b8e65db076c189dc57973d5b7db120","schema_version":"1.0","event_id":"sha256:022394915f6dc15e68f0b2663cf3b87184b8e65db076c189dc57973d5b7db120"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4WWEGNLV5I3CWPKTPX2G3HP7EE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changsheng Fang, Dayang Wang, Debesh Jha, Hengyong Yu, Juntong Fan, Shuyi Fan, Tieyong Zeng","submitted_at":"2025-08-09T15:53:19Z","abstract_excerpt":"Accurate endoscopic image segmentation on the polyps is critical for early colorectal cancer detection. However, this task remains challenging due to low contrast with surrounding mucosa, specular highlights, and indistinct boundaries. To address these challenges, we propose FOCUS-Med, which stands for Fusion of spatial and structural graph with attentional context-aware polyp segmentation in endoscopic medical imaging. FOCUS-Med integrates a Dual Graph Convolutional Network (Dual-GCN) module to capture contextual spatial and topological structural dependencies. This graph-based representation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.07028","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/2508.07028/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":"2026-07-05T11:51:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V8x0KyW7YVu40+N+9vp7EgeSO3Tlw7d+9lo+3XpNKLjjGOwh9DKhiW6HqAy5CcGAU6uyYXxuBS2in0sBXt9IBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:29:59.156219Z"},"content_sha256":"3864dd53dbf269bde1d7ae8c81ebe009dda10be3bfc1298719f035dd8abad22e","schema_version":"1.0","event_id":"sha256:3864dd53dbf269bde1d7ae8c81ebe009dda10be3bfc1298719f035dd8abad22e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4WWEGNLV5I3CWPKTPX2G3HP7EE/bundle.json","state_url":"https://pith.science/pith/4WWEGNLV5I3CWPKTPX2G3HP7EE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4WWEGNLV5I3CWPKTPX2G3HP7EE/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":"2026-08-09T06:29:59Z","links":{"resolver":"https://pith.science/pith/4WWEGNLV5I3CWPKTPX2G3HP7EE","bundle":"https://pith.science/pith/4WWEGNLV5I3CWPKTPX2G3HP7EE/bundle.json","state":"https://pith.science/pith/4WWEGNLV5I3CWPKTPX2G3HP7EE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4WWEGNLV5I3CWPKTPX2G3HP7EE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4WWEGNLV5I3CWPKTPX2G3HP7EE","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":"fb8909a0795901e98ac1d63e67ab96de49d459cf60266f7a3b1122d82ec67149","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-09T15:53:19Z","title_canon_sha256":"c70e687023a4b18543dad64046c48804a8f81b60929a855dcc7b917bf94f30a0"},"schema_version":"1.0","source":{"id":"2508.07028","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.07028","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"arxiv_version","alias_value":"2508.07028v1","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.07028","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"pith_short_12","alias_value":"4WWEGNLV5I3C","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"pith_short_16","alias_value":"4WWEGNLV5I3CWPKT","created_at":"2026-07-05T11:51:39Z"},{"alias_kind":"pith_short_8","alias_value":"4WWEGNLV","created_at":"2026-07-05T11:51:39Z"}],"graph_snapshots":[{"event_id":"sha256:3864dd53dbf269bde1d7ae8c81ebe009dda10be3bfc1298719f035dd8abad22e","target":"graph","created_at":"2026-07-05T11:51:39Z","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/2508.07028/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate endoscopic image segmentation on the polyps is critical for early colorectal cancer detection. However, this task remains challenging due to low contrast with surrounding mucosa, specular highlights, and indistinct boundaries. To address these challenges, we propose FOCUS-Med, which stands for Fusion of spatial and structural graph with attentional context-aware polyp segmentation in endoscopic medical imaging. FOCUS-Med integrates a Dual Graph Convolutional Network (Dual-GCN) module to capture contextual spatial and topological structural dependencies. This graph-based representation","authors_text":"Changsheng Fang, Dayang Wang, Debesh Jha, Hengyong Yu, Juntong Fan, Shuyi Fan, Tieyong Zeng","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-09T15:53:19Z","title":"Large Language Model Evaluated Stand-alone Attention-Assisted Graph Neural Network with Spatial and Structural Information Interaction for Precise Endoscopic Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.07028","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":"sha256:022394915f6dc15e68f0b2663cf3b87184b8e65db076c189dc57973d5b7db120","target":"record","created_at":"2026-07-05T11:51:39Z","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":"fb8909a0795901e98ac1d63e67ab96de49d459cf60266f7a3b1122d82ec67149","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-09T15:53:19Z","title_canon_sha256":"c70e687023a4b18543dad64046c48804a8f81b60929a855dcc7b917bf94f30a0"},"schema_version":"1.0","source":{"id":"2508.07028","kind":"arxiv","version":1}},"canonical_sha256":"e5ac433575ea362b3d537df46d9dff212c44487d58611c1dfcc4c39012d697f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e5ac433575ea362b3d537df46d9dff212c44487d58611c1dfcc4c39012d697f6","first_computed_at":"2026-07-05T11:51:39.580340Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:51:39.580340Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YvYmrLxJgEK554BnoNxIWmHlBnqgmfC4IeNzOK2HX3WhBBmztRV4wKDpx+OFQ1BTbg/3FcQZhRJWvp2KqSpmAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:51:39.580807Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.07028","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:022394915f6dc15e68f0b2663cf3b87184b8e65db076c189dc57973d5b7db120","sha256:3864dd53dbf269bde1d7ae8c81ebe009dda10be3bfc1298719f035dd8abad22e"],"state_sha256":"a179d585bf1817816d120f36df46da347a538aa7b3dd765f6126b96f01211b5a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+/uefCvuKhpxmN3dvwMj4yhBi/ZfyoGtvmEtmAgUccs7AH0X8HZDDlLppIMaYNV4IbnrbwPQ6tNa3zaGN0+hAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T06:29:59.163771Z","bundle_sha256":"2310ae7b50e1ce859dccadc7ea30f7af592483a07707453f59a11a93d941817d"}}