{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:D4P3HLOYTQEJPNV7EKU6PEEJW7","short_pith_number":"pith:D4P3HLOY","canonical_record":{"source":{"id":"2402.15759","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T08:10:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f18bf7f16daa9a24f33ee3d2f8efa60ad81a0b4441e137d09dd1c50aaf53a824","abstract_canon_sha256":"04fb36984c6cde47a8f3efc02a468a9c476d15ad6d5ac13cc986585b801d5e90"},"schema_version":"1.0"},"canonical_sha256":"1f1fb3add89c0897b6bf22a9e79089b7e148a56c684f1afda93beee1c0ece626","source":{"kind":"arxiv","id":"2402.15759","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.15759","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"arxiv_version","alias_value":"2402.15759v2","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.15759","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"pith_short_12","alias_value":"D4P3HLOYTQEJ","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"pith_short_16","alias_value":"D4P3HLOYTQEJPNV7","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"pith_short_8","alias_value":"D4P3HLOY","created_at":"2026-07-05T09:19:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:D4P3HLOYTQEJPNV7EKU6PEEJW7","target":"record","payload":{"canonical_record":{"source":{"id":"2402.15759","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T08:10:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f18bf7f16daa9a24f33ee3d2f8efa60ad81a0b4441e137d09dd1c50aaf53a824","abstract_canon_sha256":"04fb36984c6cde47a8f3efc02a468a9c476d15ad6d5ac13cc986585b801d5e90"},"schema_version":"1.0"},"canonical_sha256":"1f1fb3add89c0897b6bf22a9e79089b7e148a56c684f1afda93beee1c0ece626","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:19:54.375031Z","signature_b64":"qDMTq0m4rKfD2UMiCf9hHKm3VOwFVk0dDD5glH0HOzi/uOZWeJOPhW19cGe4wKC4NYYeRjBaHYpCzy9T+oNeDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1f1fb3add89c0897b6bf22a9e79089b7e148a56c684f1afda93beee1c0ece626","last_reissued_at":"2026-07-05T09:19:54.374551Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:19:54.374551Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.15759","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:19:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zr7NQIET4XusHIXoNIRXzX8Q6I37cqBa+esJtGdC7e3QmQsRFnP0edWZ9oehYi14Dj3fVd5NOncGjnTqqWC4Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:43:48.187582Z"},"content_sha256":"973f071955666532fc68ef0408c3ea0da2b7455fb26b13e96d8bfafc2cee32de","schema_version":"1.0","event_id":"sha256:973f071955666532fc68ef0408c3ea0da2b7455fb26b13e96d8bfafc2cee32de"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:D4P3HLOYTQEJPNV7EKU6PEEJW7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Abdullaev Bakhrom Ismoilovich, Bekchanov Habibullo, Defu Tang, Dongjie Cheng, Jun Gao, Kang Li, Le Zhang, LinJing Wei, Qicheng Lao, Urazboev Gayrat, Yuldashov Elyorbek, Zekun Jiang, Ziyuan Qin","submitted_at":"2024-02-24T08:10:54Z","abstract_excerpt":"This study presents a novel multimodal medical image zero-shot segmentation algorithm named the text-visual-prompt segment anything model (TV-SAM) without any manual annotations. The TV-SAM incorporates and integrates the large language model GPT-4, the vision language model GLIP, and the SAM to autonomously generate descriptive text prompts and visual bounding box prompts from medical images, thereby enhancing the SAM's capability for zero-shot segmentation. Comprehensive evaluations are implemented on seven public datasets encompassing eight imaging modalities to demonstrate that TV-SAM can "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.15759","kind":"arxiv","version":2},"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/2402.15759/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":"2026-07-05T09:19:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XZN1AX4inUSHyZVAg+ddtknMzC2zQ4sWio48Yn/zeJXsxWilp7BcAtAy1m1xhXDDy/FTkrKMpxlqJ/HWLj0VCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:43:48.188283Z"},"content_sha256":"e8b43ae5e1538fc2116e700155c33da5d25f0336a8c8c23b917c5c765b673bd4","schema_version":"1.0","event_id":"sha256:e8b43ae5e1538fc2116e700155c33da5d25f0336a8c8c23b917c5c765b673bd4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D4P3HLOYTQEJPNV7EKU6PEEJW7/bundle.json","state_url":"https://pith.science/pith/D4P3HLOYTQEJPNV7EKU6PEEJW7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D4P3HLOYTQEJPNV7EKU6PEEJW7/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":"2026-08-09T15:43:48Z","links":{"resolver":"https://pith.science/pith/D4P3HLOYTQEJPNV7EKU6PEEJW7","bundle":"https://pith.science/pith/D4P3HLOYTQEJPNV7EKU6PEEJW7/bundle.json","state":"https://pith.science/pith/D4P3HLOYTQEJPNV7EKU6PEEJW7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D4P3HLOYTQEJPNV7EKU6PEEJW7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:D4P3HLOYTQEJPNV7EKU6PEEJW7","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":"04fb36984c6cde47a8f3efc02a468a9c476d15ad6d5ac13cc986585b801d5e90","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T08:10:54Z","title_canon_sha256":"f18bf7f16daa9a24f33ee3d2f8efa60ad81a0b4441e137d09dd1c50aaf53a824"},"schema_version":"1.0","source":{"id":"2402.15759","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.15759","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"arxiv_version","alias_value":"2402.15759v2","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.15759","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"pith_short_12","alias_value":"D4P3HLOYTQEJ","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"pith_short_16","alias_value":"D4P3HLOYTQEJPNV7","created_at":"2026-07-05T09:19:54Z"},{"alias_kind":"pith_short_8","alias_value":"D4P3HLOY","created_at":"2026-07-05T09:19:54Z"}],"graph_snapshots":[{"event_id":"sha256:e8b43ae5e1538fc2116e700155c33da5d25f0336a8c8c23b917c5c765b673bd4","target":"graph","created_at":"2026-07-05T09:19:54Z","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/2402.15759/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study presents a novel multimodal medical image zero-shot segmentation algorithm named the text-visual-prompt segment anything model (TV-SAM) without any manual annotations. The TV-SAM incorporates and integrates the large language model GPT-4, the vision language model GLIP, and the SAM to autonomously generate descriptive text prompts and visual bounding box prompts from medical images, thereby enhancing the SAM's capability for zero-shot segmentation. Comprehensive evaluations are implemented on seven public datasets encompassing eight imaging modalities to demonstrate that TV-SAM can ","authors_text":"Abdullaev Bakhrom Ismoilovich, Bekchanov Habibullo, Defu Tang, Dongjie Cheng, Jun Gao, Kang Li, Le Zhang, LinJing Wei, Qicheng Lao, Urazboev Gayrat, Yuldashov Elyorbek, Zekun Jiang, Ziyuan Qin","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T08:10:54Z","title":"TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.15759","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":"sha256:973f071955666532fc68ef0408c3ea0da2b7455fb26b13e96d8bfafc2cee32de","target":"record","created_at":"2026-07-05T09:19:54Z","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":"04fb36984c6cde47a8f3efc02a468a9c476d15ad6d5ac13cc986585b801d5e90","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-24T08:10:54Z","title_canon_sha256":"f18bf7f16daa9a24f33ee3d2f8efa60ad81a0b4441e137d09dd1c50aaf53a824"},"schema_version":"1.0","source":{"id":"2402.15759","kind":"arxiv","version":2}},"canonical_sha256":"1f1fb3add89c0897b6bf22a9e79089b7e148a56c684f1afda93beee1c0ece626","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f1fb3add89c0897b6bf22a9e79089b7e148a56c684f1afda93beee1c0ece626","first_computed_at":"2026-07-05T09:19:54.374551Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:19:54.374551Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qDMTq0m4rKfD2UMiCf9hHKm3VOwFVk0dDD5glH0HOzi/uOZWeJOPhW19cGe4wKC4NYYeRjBaHYpCzy9T+oNeDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:19:54.375031Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.15759","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:973f071955666532fc68ef0408c3ea0da2b7455fb26b13e96d8bfafc2cee32de","sha256:e8b43ae5e1538fc2116e700155c33da5d25f0336a8c8c23b917c5c765b673bd4"],"state_sha256":"2bb07ccc89439d70d56726dbdcd4b89defd53a11d81e152a0b3128beb9ab8771"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/Ear3Qt+BJCqbeR4XocMiYwc8lrfDG58dr+ChTJyz+7OuqHiBsV7WuCUlsij+MYtd6UAz/Kj0zYJf/FWgDQeCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:43:48.192833Z","bundle_sha256":"0d91c65f59c0f4501e5466f82a29c1b29e466e7232a42184dd79f5320dc822a9"}}