{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:HLS6BVGT3EOEV6D5BQXWCFCHHM","short_pith_number":"pith:HLS6BVGT","canonical_record":{"source":{"id":"2607.13860","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T14:05:58Z","cross_cats_sorted":[],"title_canon_sha256":"6c1c77640437c50a414c275e11fd32b408597fc5960bf105acf7dd78bea67723","abstract_canon_sha256":"3f1da998791003b606065449cb51098d0e252c5234282bc54aefe97d154c3e0d"},"schema_version":"1.0"},"canonical_sha256":"3ae5e0d4d3d91c4af87d0c2f6114473b1184fce42e6a6037f67e7943a2ab0817","source":{"kind":"arxiv","id":"2607.13860","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.13860","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"arxiv_version","alias_value":"2607.13860v1","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.13860","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"pith_short_12","alias_value":"HLS6BVGT3EOE","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"pith_short_16","alias_value":"HLS6BVGT3EOEV6D5","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"pith_short_8","alias_value":"HLS6BVGT","created_at":"2026-07-16T01:23:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:HLS6BVGT3EOEV6D5BQXWCFCHHM","target":"record","payload":{"canonical_record":{"source":{"id":"2607.13860","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T14:05:58Z","cross_cats_sorted":[],"title_canon_sha256":"6c1c77640437c50a414c275e11fd32b408597fc5960bf105acf7dd78bea67723","abstract_canon_sha256":"3f1da998791003b606065449cb51098d0e252c5234282bc54aefe97d154c3e0d"},"schema_version":"1.0"},"canonical_sha256":"3ae5e0d4d3d91c4af87d0c2f6114473b1184fce42e6a6037f67e7943a2ab0817","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-16T01:23:10.307285Z","signature_b64":"JBVz1LUFq4uaMmwuwWnWsvc3XmlsfS8ZV31hI83SpM7gRQo64Ahmg8CVL/E7rK6zua4ifl9pDCFpnKYucOcQAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ae5e0d4d3d91c4af87d0c2f6114473b1184fce42e6a6037f67e7943a2ab0817","last_reissued_at":"2026-07-16T01:23:10.306418Z","signature_status":"signed_v1","first_computed_at":"2026-07-16T01:23:10.306418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.13860","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":"2026-07-16T01:23:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DgeUOlK6FonWlDhTFTA3bEPxGUvsLkL+ynpwdq83Ky6xrXpDNDGr8GPqvtGNtgBXeuk+mbAox/Wf8vA3N9+cBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:13:22.322434Z"},"content_sha256":"cefb5e6477a6bc4ada6afce695c8a6ba92ff59accb1ae32f6de4282880dbddf0","schema_version":"1.0","event_id":"sha256:cefb5e6477a6bc4ada6afce695c8a6ba92ff59accb1ae32f6de4282880dbddf0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:HLS6BVGT3EOEV6D5BQXWCFCHHM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Binyang Li, Hangui Lin, Yan Li, Yan Shu, Yaru Zhao, Yiqiong Zhang, Zeshang Li, Zhuoyuan Fu","submitted_at":"2026-07-15T14:05:58Z","abstract_excerpt":"While Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in 2D medical image understanding, their extension to 3D volumetric imaging remains hindered by prohibitive annotation costs and dataset opacity. Current data formats, predominantly consisting of rigid Visual Question Answering (VQA) pairs or unstructured final clinical reports, typically fail to capture explicit clinical reasoning. To address this limitation, we introduce a large-scale structured reasoning dataset constructed via a novel slice-wise data synthesis paradigm. Inspired by the genuine diagnostic wo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.13860","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/2607.13860/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":"2026-07-16T01:23:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2zZXG3XL5bc0LPCnQb39/3trfRH2UgHOw/+d0GL/irS7PoaPBomj2Bx0mIH+0vhqmUPodCO2O5bDDvEilbRlDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:13:22.323341Z"},"content_sha256":"15538d4dd886c616350bc60584c2baae73fd8ed482343119ad9f1a605b8c3582","schema_version":"1.0","event_id":"sha256:15538d4dd886c616350bc60584c2baae73fd8ed482343119ad9f1a605b8c3582"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HLS6BVGT3EOEV6D5BQXWCFCHHM/bundle.json","state_url":"https://pith.science/pith/HLS6BVGT3EOEV6D5BQXWCFCHHM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HLS6BVGT3EOEV6D5BQXWCFCHHM/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":"2026-08-04T13:13:22Z","links":{"resolver":"https://pith.science/pith/HLS6BVGT3EOEV6D5BQXWCFCHHM","bundle":"https://pith.science/pith/HLS6BVGT3EOEV6D5BQXWCFCHHM/bundle.json","state":"https://pith.science/pith/HLS6BVGT3EOEV6D5BQXWCFCHHM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HLS6BVGT3EOEV6D5BQXWCFCHHM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:HLS6BVGT3EOEV6D5BQXWCFCHHM","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":"3f1da998791003b606065449cb51098d0e252c5234282bc54aefe97d154c3e0d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T14:05:58Z","title_canon_sha256":"6c1c77640437c50a414c275e11fd32b408597fc5960bf105acf7dd78bea67723"},"schema_version":"1.0","source":{"id":"2607.13860","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.13860","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"arxiv_version","alias_value":"2607.13860v1","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.13860","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"pith_short_12","alias_value":"HLS6BVGT3EOE","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"pith_short_16","alias_value":"HLS6BVGT3EOEV6D5","created_at":"2026-07-16T01:23:10Z"},{"alias_kind":"pith_short_8","alias_value":"HLS6BVGT","created_at":"2026-07-16T01:23:10Z"}],"graph_snapshots":[{"event_id":"sha256:15538d4dd886c616350bc60584c2baae73fd8ed482343119ad9f1a605b8c3582","target":"graph","created_at":"2026-07-16T01:23:10Z","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/2607.13860/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in 2D medical image understanding, their extension to 3D volumetric imaging remains hindered by prohibitive annotation costs and dataset opacity. Current data formats, predominantly consisting of rigid Visual Question Answering (VQA) pairs or unstructured final clinical reports, typically fail to capture explicit clinical reasoning. To address this limitation, we introduce a large-scale structured reasoning dataset constructed via a novel slice-wise data synthesis paradigm. Inspired by the genuine diagnostic wo","authors_text":"Binyang Li, Hangui Lin, Yan Li, Yan Shu, Yaru Zhao, Yiqiong Zhang, Zeshang Li, Zhuoyuan Fu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T14:05:58Z","title":"Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.13860","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:cefb5e6477a6bc4ada6afce695c8a6ba92ff59accb1ae32f6de4282880dbddf0","target":"record","created_at":"2026-07-16T01:23:10Z","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":"3f1da998791003b606065449cb51098d0e252c5234282bc54aefe97d154c3e0d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T14:05:58Z","title_canon_sha256":"6c1c77640437c50a414c275e11fd32b408597fc5960bf105acf7dd78bea67723"},"schema_version":"1.0","source":{"id":"2607.13860","kind":"arxiv","version":1}},"canonical_sha256":"3ae5e0d4d3d91c4af87d0c2f6114473b1184fce42e6a6037f67e7943a2ab0817","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3ae5e0d4d3d91c4af87d0c2f6114473b1184fce42e6a6037f67e7943a2ab0817","first_computed_at":"2026-07-16T01:23:10.306418Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-16T01:23:10.306418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JBVz1LUFq4uaMmwuwWnWsvc3XmlsfS8ZV31hI83SpM7gRQo64Ahmg8CVL/E7rK6zua4ifl9pDCFpnKYucOcQAQ==","signature_status":"signed_v1","signed_at":"2026-07-16T01:23:10.307285Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.13860","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cefb5e6477a6bc4ada6afce695c8a6ba92ff59accb1ae32f6de4282880dbddf0","sha256:15538d4dd886c616350bc60584c2baae73fd8ed482343119ad9f1a605b8c3582"],"state_sha256":"dfa0884304749948adcfd32a4c1bff16619865a463948fe064728d15e3730049"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UYpVzDRU4y8IwxIhwqFTY5M55nIYMmwp75+Shs1OCkSpx2iOitsUYz3lCYEvYixxOhmFMY7xmNvO3ej+QmouDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T13:13:22.331365Z","bundle_sha256":"33fa3f62f7d256326794874753ae8a7e4e5c7e258c66860af908e7c1a93972d2"}}