{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QKFG4FPBJYSCYLN62YZPQPNO4A","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":"c4effe2aebc5c9ff003610a81be7c3bef4229a10989f78f0d71e045f9b6ebaea","cross_cats_sorted":["cs.CY","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T20:07:25Z","title_canon_sha256":"ea6c50781f307032aedc43517607ffe6d6c1dd5fa235981a4b153f23832f539f"},"schema_version":"1.0","source":{"id":"2506.03360","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.03360","created_at":"2026-07-05T11:15:48Z"},{"alias_kind":"arxiv_version","alias_value":"2506.03360v1","created_at":"2026-07-05T11:15:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.03360","created_at":"2026-07-05T11:15:48Z"},{"alias_kind":"pith_short_12","alias_value":"QKFG4FPBJYSC","created_at":"2026-07-05T11:15:48Z"},{"alias_kind":"pith_short_16","alias_value":"QKFG4FPBJYSCYLN6","created_at":"2026-07-05T11:15:48Z"},{"alias_kind":"pith_short_8","alias_value":"QKFG4FPB","created_at":"2026-07-05T11:15:48Z"}],"graph_snapshots":[{"event_id":"sha256:14d1f7eaba36771e7f4f936390031b0481cc3473283e238c934ccdc9167a193c","target":"graph","created_at":"2026-07-05T11:15:48Z","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/2506.03360/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Rapid, fine-grained disaster damage assessment is essential for effective emergency response, yet remains challenging due to limited ground sensors and delays in official reporting. Social media provides a rich, real-time source of human-centric observations, but its multimodal and unstructured nature presents challenges for traditional analytical methods. In this study, we propose a structured Multimodal, Multilingual, and Multidimensional (3M) pipeline that leverages multimodal large language models (MLLMs) to assess disaster impacts. We evaluate three foundation models across two major eart","authors_text":"Jingxiao Liu, Juan Li, Lingyao Li, Qingyuan Feng, Wenyue Hua, Yuki Miura, Zihui Ma","cross_cats":["cs.CY","cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T20:07:25Z","title":"A Multimodal, Multilingual, and Multidimensional Pipeline for Fine-grained Crowdsourcing Earthquake Damage Evaluation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.03360","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":"sha256:68d45ea2ade3b27f146977cf79a73161815260437a80e5b91ab578540194444d","target":"record","created_at":"2026-07-05T11:15:48Z","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":"c4effe2aebc5c9ff003610a81be7c3bef4229a10989f78f0d71e045f9b6ebaea","cross_cats_sorted":["cs.CY","cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T20:07:25Z","title_canon_sha256":"ea6c50781f307032aedc43517607ffe6d6c1dd5fa235981a4b153f23832f539f"},"schema_version":"1.0","source":{"id":"2506.03360","kind":"arxiv","version":1}},"canonical_sha256":"828a6e15e14e242c2dbed632f83daee035a9fbeaf07604b9a5ac50bdbb6cecb9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"828a6e15e14e242c2dbed632f83daee035a9fbeaf07604b9a5ac50bdbb6cecb9","first_computed_at":"2026-07-05T11:15:48.289838Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:15:48.289838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hnVmIOhzbsmvPlwY6dOjnRqT5EBGi6HIMl3HRt3NNb5iB1qpRCFIUcYntVgbIEhr/d/DFi4mlLMfpJ7P/sN2Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:15:48.290382Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.03360","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68d45ea2ade3b27f146977cf79a73161815260437a80e5b91ab578540194444d","sha256:14d1f7eaba36771e7f4f936390031b0481cc3473283e238c934ccdc9167a193c"],"state_sha256":"8427f7348c8d4741ac1cd11805e832491d2298995695dd228761c018d36fa0cb"}