{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:CIBCSHBNEE34JFXLBZS56K6OTV","short_pith_number":"pith:CIBCSHBN","canonical_record":{"source":{"id":"2503.18227","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-23T22:06:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2999ee5151407b3857b781ec4ba3df9bcb186266f074d414824577b06c696400","abstract_canon_sha256":"2d39ca387eb9fab9287299bdfcaf6dabe027834c37dcf7b54826d7739b7db1d8"},"schema_version":"1.0"},"canonical_sha256":"1202291c2d2137c496eb0e65df2bce9d5134d59aec8d6685f4bd80d0ef98a35a","source":{"kind":"arxiv","id":"2503.18227","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.18227","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"arxiv_version","alias_value":"2503.18227v3","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18227","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"pith_short_12","alias_value":"CIBCSHBNEE34","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"pith_short_16","alias_value":"CIBCSHBNEE34JFXL","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"pith_short_8","alias_value":"CIBCSHBN","created_at":"2026-07-05T10:39:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:CIBCSHBNEE34JFXLBZS56K6OTV","target":"record","payload":{"canonical_record":{"source":{"id":"2503.18227","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-23T22:06:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2999ee5151407b3857b781ec4ba3df9bcb186266f074d414824577b06c696400","abstract_canon_sha256":"2d39ca387eb9fab9287299bdfcaf6dabe027834c37dcf7b54826d7739b7db1d8"},"schema_version":"1.0"},"canonical_sha256":"1202291c2d2137c496eb0e65df2bce9d5134d59aec8d6685f4bd80d0ef98a35a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:39:28.191065Z","signature_b64":"XzHrMhuVcB8wz21BA4Thh41ZB6zuRrCpq/zpgo4uSgPsb0kaU0xyHTf049a3nTO2yrt9ntXRX9/EEtHZfw6UDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1202291c2d2137c496eb0e65df2bce9d5134d59aec8d6685f4bd80d0ef98a35a","last_reissued_at":"2026-07-05T10:39:28.190587Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:39:28.190587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.18227","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:39:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CsB1UJxSaFplVe2aOsh9qr2HW1vAsorDDS9Gr5PuDBuov7iTXXvey3pd5SmAXZi3Z+wbZBTeSAgXn8x8QtnnCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T07:57:48.012341Z"},"content_sha256":"162426404252c307a88a74d6b2a68c9ce7a402b3fdb31a079b1a074baea1d1e0","schema_version":"1.0","event_id":"sha256:162426404252c307a88a74d6b2a68c9ce7a402b3fdb31a079b1a074baea1d1e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:CIBCSHBNEE34JFXLBZS56K6OTV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PG-SAM: Prior-Guided SAM with Medical for Multi-organ Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chengzhi Liu, Feilong Tang, Imran Razzak, Jionglong Su, Ming Hu, Yiheng Zhong, Yingzhen Hu, Zelin Peng, Zihong Luo, Zongyuan Ge","submitted_at":"2025-03-23T22:06:07Z","abstract_excerpt":"Segment Anything Model (SAM) demonstrates powerful zero-shot capabilities; however, its accuracy and robustness significantly decrease when applied to medical image segmentation. Existing methods address this issue through modality fusion, integrating textual and image information to provide more detailed priors. In this study, we argue that the granularity of text and the domain gap affect the accuracy of the priors. Furthermore, the discrepancy between high-level abstract semantics and pixel-level boundary details in images can introduce noise into the fusion process. To address this, we pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18227","kind":"arxiv","version":3},"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/2503.18227/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":"2026-07-05T10:39:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V+cfcbGr8Y0gru5zOjekmTfXrAch5VkJ7OX7k96vjJvq8wcNKu8KUrfDhyA02tTYSGjVD9Bbpxmt190B+Vb+Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T07:57:48.012870Z"},"content_sha256":"a6fe979835d78867d7f1aa2e86fd2b653fd0893f40bc31cf793c75a2d4bd50f3","schema_version":"1.0","event_id":"sha256:a6fe979835d78867d7f1aa2e86fd2b653fd0893f40bc31cf793c75a2d4bd50f3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CIBCSHBNEE34JFXLBZS56K6OTV/bundle.json","state_url":"https://pith.science/pith/CIBCSHBNEE34JFXLBZS56K6OTV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CIBCSHBNEE34JFXLBZS56K6OTV/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":"2026-08-19T07:57:48Z","links":{"resolver":"https://pith.science/pith/CIBCSHBNEE34JFXLBZS56K6OTV","bundle":"https://pith.science/pith/CIBCSHBNEE34JFXLBZS56K6OTV/bundle.json","state":"https://pith.science/pith/CIBCSHBNEE34JFXLBZS56K6OTV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CIBCSHBNEE34JFXLBZS56K6OTV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CIBCSHBNEE34JFXLBZS56K6OTV","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":"2d39ca387eb9fab9287299bdfcaf6dabe027834c37dcf7b54826d7739b7db1d8","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-23T22:06:07Z","title_canon_sha256":"2999ee5151407b3857b781ec4ba3df9bcb186266f074d414824577b06c696400"},"schema_version":"1.0","source":{"id":"2503.18227","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.18227","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"arxiv_version","alias_value":"2503.18227v3","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18227","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"pith_short_12","alias_value":"CIBCSHBNEE34","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"pith_short_16","alias_value":"CIBCSHBNEE34JFXL","created_at":"2026-07-05T10:39:28Z"},{"alias_kind":"pith_short_8","alias_value":"CIBCSHBN","created_at":"2026-07-05T10:39:28Z"}],"graph_snapshots":[{"event_id":"sha256:a6fe979835d78867d7f1aa2e86fd2b653fd0893f40bc31cf793c75a2d4bd50f3","target":"graph","created_at":"2026-07-05T10:39:28Z","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/2503.18227/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Segment Anything Model (SAM) demonstrates powerful zero-shot capabilities; however, its accuracy and robustness significantly decrease when applied to medical image segmentation. Existing methods address this issue through modality fusion, integrating textual and image information to provide more detailed priors. In this study, we argue that the granularity of text and the domain gap affect the accuracy of the priors. Furthermore, the discrepancy between high-level abstract semantics and pixel-level boundary details in images can introduce noise into the fusion process. To address this, we pro","authors_text":"Chengzhi Liu, Feilong Tang, Imran Razzak, Jionglong Su, Ming Hu, Yiheng Zhong, Yingzhen Hu, Zelin Peng, Zihong Luo, Zongyuan Ge","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-23T22:06:07Z","title":"PG-SAM: Prior-Guided SAM with Medical for Multi-organ Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18227","kind":"arxiv","version":3},"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":"sha256:162426404252c307a88a74d6b2a68c9ce7a402b3fdb31a079b1a074baea1d1e0","target":"record","created_at":"2026-07-05T10:39:28Z","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":"2d39ca387eb9fab9287299bdfcaf6dabe027834c37dcf7b54826d7739b7db1d8","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-23T22:06:07Z","title_canon_sha256":"2999ee5151407b3857b781ec4ba3df9bcb186266f074d414824577b06c696400"},"schema_version":"1.0","source":{"id":"2503.18227","kind":"arxiv","version":3}},"canonical_sha256":"1202291c2d2137c496eb0e65df2bce9d5134d59aec8d6685f4bd80d0ef98a35a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1202291c2d2137c496eb0e65df2bce9d5134d59aec8d6685f4bd80d0ef98a35a","first_computed_at":"2026-07-05T10:39:28.190587Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:39:28.190587Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XzHrMhuVcB8wz21BA4Thh41ZB6zuRrCpq/zpgo4uSgPsb0kaU0xyHTf049a3nTO2yrt9ntXRX9/EEtHZfw6UDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:39:28.191065Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.18227","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:162426404252c307a88a74d6b2a68c9ce7a402b3fdb31a079b1a074baea1d1e0","sha256:a6fe979835d78867d7f1aa2e86fd2b653fd0893f40bc31cf793c75a2d4bd50f3"],"state_sha256":"f2d5e10c84a4a7d8ee54ff294f0dfec83ae7d05ed4720aa48d80f1f91092ec2b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u2xAvJPa0+QRlTlia67cjF9cvvNPFgnClwelIzImkI3nq93fxyulrSbBA2N3uL95LAVvj/m6ube805804pOtCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T07:57:48.016906Z","bundle_sha256":"61f76241bed29f2b74c2e442636f4ee1d564da1ce5a92bbe84ae3fb270aa3c88"}}