{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:TRD7YYAF6NFC6S6PPE5O4X4FJM","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":"d417fa3731ec9043ecfbbbc55f32bef36ecefc58425b5483848bab7ad9983e8c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-22T07:11:53Z","title_canon_sha256":"7a72e6b3df230253d14d42fa4dda3e63d8632874697d30c56e36a58981cec6a4"},"schema_version":"1.0","source":{"id":"2304.11332","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.11332","created_at":"2026-07-05T06:23:03Z"},{"alias_kind":"arxiv_version","alias_value":"2304.11332v2","created_at":"2026-07-05T06:23:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.11332","created_at":"2026-07-05T06:23:03Z"},{"alias_kind":"pith_short_12","alias_value":"TRD7YYAF6NFC","created_at":"2026-07-05T06:23:03Z"},{"alias_kind":"pith_short_16","alias_value":"TRD7YYAF6NFC6S6P","created_at":"2026-07-05T06:23:03Z"},{"alias_kind":"pith_short_8","alias_value":"TRD7YYAF","created_at":"2026-07-05T06:23:03Z"}],"graph_snapshots":[{"event_id":"sha256:43f401ccfd5449ccd93eb75bbe71414158a954a6b3b3d0808b922b8ac753db85","target":"graph","created_at":"2026-07-05T06:23:03Z","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/2304.11332/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Segment Anything Model (SAM) is a recently developed large model for general-purpose segmentation for computer vision tasks. SAM was trained using 11 million images with over 1 billion masks and can produce segmentation results for a wide range of objects in natural scene images. SAM can be viewed as a general perception model for segmentation (partitioning images into semantically meaningful regions). Thus, how to utilize such a large foundation model for medical image segmentation is an emerging research target. This paper shows that although SAM does not immediately give high-quality se","authors_text":"Danny Z. Chen, Peixian Liang, Shuo Wang, Tao Zhou, Yizhe Zhang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-22T07:11:53Z","title":"Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.11332","kind":"arxiv","version":2},"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":"sha256:1c4d6f50e248559251f9ba6fa806eca1e996f7fd63da5f770d71833dd1baefe2","target":"record","created_at":"2026-07-05T06:23:03Z","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":"d417fa3731ec9043ecfbbbc55f32bef36ecefc58425b5483848bab7ad9983e8c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-22T07:11:53Z","title_canon_sha256":"7a72e6b3df230253d14d42fa4dda3e63d8632874697d30c56e36a58981cec6a4"},"schema_version":"1.0","source":{"id":"2304.11332","kind":"arxiv","version":2}},"canonical_sha256":"9c47fc6005f34a2f4bcf793aee5f854b334b4d05ea0ed9791e9870a3613d7a1d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c47fc6005f34a2f4bcf793aee5f854b334b4d05ea0ed9791e9870a3613d7a1d","first_computed_at":"2026-07-05T06:23:03.560023Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:23:03.560023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"II/K0MQfyAknZjyrCZQUX5kp9AsRkYvRA0G4MgzeuRuMPNe+76wv5y99qGLqDjV3rbAvmVLMSINyWhrSnD31Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T06:23:03.560585Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.11332","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c4d6f50e248559251f9ba6fa806eca1e996f7fd63da5f770d71833dd1baefe2","sha256:43f401ccfd5449ccd93eb75bbe71414158a954a6b3b3d0808b922b8ac753db85"],"state_sha256":"2a88bcf95d45ada2a49d4bd145dffa24e1bacde173787cc1bf5bfb43d2f930e0"}