{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:LPVNB3XX73GMXXFZR4MVKJSPWM","short_pith_number":"pith:LPVNB3XX","canonical_record":{"source":{"id":"2411.09933","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T04:16:50Z","cross_cats_sorted":["cs.AI","cs.CL","cs.NE"],"title_canon_sha256":"5bfccad93da4eca22585c027d3b06cc878dfd4636cfd7afdb3ecd3814e68d85d","abstract_canon_sha256":"7c019d01e7d56146361f45e9e52d8c7554cdd622ca65d68168d0812f590ddcbb"},"schema_version":"1.0"},"canonical_sha256":"5bead0eef7fecccbdcb98f1955264fb33d4f11b86fa86f826f33b6f6d71b34e2","source":{"kind":"arxiv","id":"2411.09933","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.09933","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"arxiv_version","alias_value":"2411.09933v1","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.09933","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"pith_short_12","alias_value":"LPVNB3XX73GM","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"pith_short_16","alias_value":"LPVNB3XX73GMXXFZ","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"pith_short_8","alias_value":"LPVNB3XX","created_at":"2026-07-05T09:35:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:LPVNB3XX73GMXXFZR4MVKJSPWM","target":"record","payload":{"canonical_record":{"source":{"id":"2411.09933","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T04:16:50Z","cross_cats_sorted":["cs.AI","cs.CL","cs.NE"],"title_canon_sha256":"5bfccad93da4eca22585c027d3b06cc878dfd4636cfd7afdb3ecd3814e68d85d","abstract_canon_sha256":"7c019d01e7d56146361f45e9e52d8c7554cdd622ca65d68168d0812f590ddcbb"},"schema_version":"1.0"},"canonical_sha256":"5bead0eef7fecccbdcb98f1955264fb33d4f11b86fa86f826f33b6f6d71b34e2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:35:55.903553Z","signature_b64":"6xPybz2EgynfOV1xyako5wqppxHKF2+wgUMiNlS7+ODelXoirlv6v/PV3xx86ZH5itBFMJ7guQq0rlml/22TCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5bead0eef7fecccbdcb98f1955264fb33d4f11b86fa86f826f33b6f6d71b34e2","last_reissued_at":"2026-07-05T09:35:55.902968Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:35:55.902968Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.09933","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":"2026-07-05T09:35:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"63dQl2YyPu9vBhWCCu0Ki5zLI2f3tnKjXdLJyqPb9l3KeoZIiDfsuthqdXgunY4nVe8pct+wsplE/xE4aT3qCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:36:29.223047Z"},"content_sha256":"44de6acaa1893ae750cf157af57dfcae7fe1649285374ca2d2aa2d843b2635e5","schema_version":"1.0","event_id":"sha256:44de6acaa1893ae750cf157af57dfcae7fe1649285374ca2d2aa2d843b2635e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:LPVNB3XX73GMXXFZR4MVKJSPWM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"JRadiEvo: A Japanese Radiology Report Generation Model Enhanced by Evolutionary Optimization of Model Merging","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.NE"],"primary_cat":"cs.CV","authors_text":"Junichiro Takahashi, Kaito Baba, Risa Kishikawa, Ryota Yagi, Satoshi Kodera","submitted_at":"2024-11-15T04:16:50Z","abstract_excerpt":"With the rapid advancement of large language models (LLMs), foundational models (FMs) have seen significant advancements. Healthcare is one of the most crucial application areas for these FMs, given the significant time and effort required for physicians to analyze large volumes of patient data. Recent efforts have focused on adapting multimodal FMs to the medical domain through techniques like instruction-tuning, leading to the development of medical foundation models (MFMs). However, these approaches typically require large amounts of training data to effectively adapt models to the medical "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.09933","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/2411.09933/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":"2026-07-05T09:35:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gJ2VZ0KnY+LVssjh7B0sLo2qwNUdOviW/qo66+CyENS8XrfnVE+Q7BdM/NJBmNxIMfW4zxrlPHVuQuvYUwIJCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:36:29.224613Z"},"content_sha256":"173024d6b08f38dc38413faa5ee2059b2d11fb96ff45ab8b90eaf761b6ee0cf3","schema_version":"1.0","event_id":"sha256:173024d6b08f38dc38413faa5ee2059b2d11fb96ff45ab8b90eaf761b6ee0cf3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LPVNB3XX73GMXXFZR4MVKJSPWM/bundle.json","state_url":"https://pith.science/pith/LPVNB3XX73GMXXFZR4MVKJSPWM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LPVNB3XX73GMXXFZR4MVKJSPWM/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":"2026-08-05T15:36:29Z","links":{"resolver":"https://pith.science/pith/LPVNB3XX73GMXXFZR4MVKJSPWM","bundle":"https://pith.science/pith/LPVNB3XX73GMXXFZR4MVKJSPWM/bundle.json","state":"https://pith.science/pith/LPVNB3XX73GMXXFZR4MVKJSPWM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LPVNB3XX73GMXXFZR4MVKJSPWM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:LPVNB3XX73GMXXFZR4MVKJSPWM","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":"7c019d01e7d56146361f45e9e52d8c7554cdd622ca65d68168d0812f590ddcbb","cross_cats_sorted":["cs.AI","cs.CL","cs.NE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T04:16:50Z","title_canon_sha256":"5bfccad93da4eca22585c027d3b06cc878dfd4636cfd7afdb3ecd3814e68d85d"},"schema_version":"1.0","source":{"id":"2411.09933","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.09933","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"arxiv_version","alias_value":"2411.09933v1","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.09933","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"pith_short_12","alias_value":"LPVNB3XX73GM","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"pith_short_16","alias_value":"LPVNB3XX73GMXXFZ","created_at":"2026-07-05T09:35:55Z"},{"alias_kind":"pith_short_8","alias_value":"LPVNB3XX","created_at":"2026-07-05T09:35:55Z"}],"graph_snapshots":[{"event_id":"sha256:173024d6b08f38dc38413faa5ee2059b2d11fb96ff45ab8b90eaf761b6ee0cf3","target":"graph","created_at":"2026-07-05T09:35:55Z","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/2411.09933/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the rapid advancement of large language models (LLMs), foundational models (FMs) have seen significant advancements. Healthcare is one of the most crucial application areas for these FMs, given the significant time and effort required for physicians to analyze large volumes of patient data. Recent efforts have focused on adapting multimodal FMs to the medical domain through techniques like instruction-tuning, leading to the development of medical foundation models (MFMs). However, these approaches typically require large amounts of training data to effectively adapt models to the medical ","authors_text":"Junichiro Takahashi, Kaito Baba, Risa Kishikawa, Ryota Yagi, Satoshi Kodera","cross_cats":["cs.AI","cs.CL","cs.NE"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T04:16:50Z","title":"JRadiEvo: A Japanese Radiology Report Generation Model Enhanced by Evolutionary Optimization of Model Merging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.09933","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":"sha256:44de6acaa1893ae750cf157af57dfcae7fe1649285374ca2d2aa2d843b2635e5","target":"record","created_at":"2026-07-05T09:35:55Z","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":"7c019d01e7d56146361f45e9e52d8c7554cdd622ca65d68168d0812f590ddcbb","cross_cats_sorted":["cs.AI","cs.CL","cs.NE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-11-15T04:16:50Z","title_canon_sha256":"5bfccad93da4eca22585c027d3b06cc878dfd4636cfd7afdb3ecd3814e68d85d"},"schema_version":"1.0","source":{"id":"2411.09933","kind":"arxiv","version":1}},"canonical_sha256":"5bead0eef7fecccbdcb98f1955264fb33d4f11b86fa86f826f33b6f6d71b34e2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5bead0eef7fecccbdcb98f1955264fb33d4f11b86fa86f826f33b6f6d71b34e2","first_computed_at":"2026-07-05T09:35:55.902968Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:35:55.902968Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6xPybz2EgynfOV1xyako5wqppxHKF2+wgUMiNlS7+ODelXoirlv6v/PV3xx86ZH5itBFMJ7guQq0rlml/22TCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:35:55.903553Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.09933","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:44de6acaa1893ae750cf157af57dfcae7fe1649285374ca2d2aa2d843b2635e5","sha256:173024d6b08f38dc38413faa5ee2059b2d11fb96ff45ab8b90eaf761b6ee0cf3"],"state_sha256":"c8a42c47d4d3866fa022efc069239eb2b3ac7902c64749279a6e6e629ec60585"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dOMC9gW6H4uAP8w5wyXdXa4qJTFXkS0O5R+Reddr74tbHbOoiq5/Hrvtv8GQ63oE7baXflHPDjFxKwIoq1/KAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T15:36:29.233715Z","bundle_sha256":"10a866d76b1961bb9bc087f1935a004caaef97d4020a3560c972a9391e289c5f"}}