{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:I7XDHQXFWZI7VROAS7MTR4FPVS","short_pith_number":"pith:I7XDHQXF","canonical_record":{"source":{"id":"2311.02597","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-11-05T08:34:26Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"31b6951e38b0726880d4a0e7c29f2ce5eefa2fff5cc11f602c83c60a9f2ea048","abstract_canon_sha256":"0c4e2877194352d44e7f119d9dca480d9172af127907492bda60545912c55e34"},"schema_version":"1.0"},"canonical_sha256":"47ee33c2e5b651fac5c097d938f0afac9cabbb297b6f4d5d2727e2414c5853ae","source":{"kind":"arxiv","id":"2311.02597","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.02597","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"arxiv_version","alias_value":"2311.02597v1","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.02597","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"pith_short_12","alias_value":"I7XDHQXFWZI7","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"pith_short_16","alias_value":"I7XDHQXFWZI7VROA","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"pith_short_8","alias_value":"I7XDHQXF","created_at":"2026-07-05T07:09:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:I7XDHQXFWZI7VROAS7MTR4FPVS","target":"record","payload":{"canonical_record":{"source":{"id":"2311.02597","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-11-05T08:34:26Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"31b6951e38b0726880d4a0e7c29f2ce5eefa2fff5cc11f602c83c60a9f2ea048","abstract_canon_sha256":"0c4e2877194352d44e7f119d9dca480d9172af127907492bda60545912c55e34"},"schema_version":"1.0"},"canonical_sha256":"47ee33c2e5b651fac5c097d938f0afac9cabbb297b6f4d5d2727e2414c5853ae","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:09:33.540910Z","signature_b64":"Vp3si+qr33LNAF7Mhy+ke9CSWn7QmogDYpVXmJ5eCGMaouZ6nRydgssHlQ2FPpaXhHXnOUNnd7S/K1cqjkSaCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"47ee33c2e5b651fac5c097d938f0afac9cabbb297b6f4d5d2727e2414c5853ae","last_reissued_at":"2026-07-05T07:09:33.540400Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:09:33.540400Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.02597","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":"2026-07-05T07:09:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fATqM+cWzc/b9HD3wtdo813lDuNU46smYj0LziiylsYyisOKglDIfaPuPkAeScYQjt2pknmOqIfcoDDKtDRMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:59:11.742314Z"},"content_sha256":"9784c9ebd4b8acca25a463792099800b773aea157b17b4e95bdcddc02329fdae","schema_version":"1.0","event_id":"sha256:9784c9ebd4b8acca25a463792099800b773aea157b17b4e95bdcddc02329fdae"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:I7XDHQXFWZI7VROAS7MTR4FPVS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FloodBrain: Flood Disaster Reporting by Web-based Retrieval Augmented Generation with an LLM","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Grace Colverd, Leonard Silverberg, Noah Kasmanoff, Paul Darm","submitted_at":"2023-11-05T08:34:26Z","abstract_excerpt":"Fast disaster impact reporting is crucial in planning humanitarian assistance. Large Language Models (LLMs) are well known for their ability to write coherent text and fulfill a variety of tasks relevant to impact reporting, such as question answering or text summarization. However, LLMs are constrained by the knowledge within their training data and are prone to generating inaccurate, or \"hallucinated\", information. To address this, we introduce a sophisticated pipeline embodied in our tool FloodBrain (floodbrain.com), specialized in generating flood disaster impact reports by extracting and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.02597","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/2311.02597/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":"2026-07-05T07:09:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kh3wv1IbhpDiiG1UD8199JVWiZkEy7Jz1PPMofbhUF9ML8iXJxoMfLY1lVhCsIzm4OG2QfIb83SOUHPBk1MXDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T14:59:11.742637Z"},"content_sha256":"bb6560d7f058f76b320f34fc58760faf83b6e8b3a795c96bc87da2b2a5fbcfa7","schema_version":"1.0","event_id":"sha256:bb6560d7f058f76b320f34fc58760faf83b6e8b3a795c96bc87da2b2a5fbcfa7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I7XDHQXFWZI7VROAS7MTR4FPVS/bundle.json","state_url":"https://pith.science/pith/I7XDHQXFWZI7VROAS7MTR4FPVS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I7XDHQXFWZI7VROAS7MTR4FPVS/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":"2026-08-18T14:59:11Z","links":{"resolver":"https://pith.science/pith/I7XDHQXFWZI7VROAS7MTR4FPVS","bundle":"https://pith.science/pith/I7XDHQXFWZI7VROAS7MTR4FPVS/bundle.json","state":"https://pith.science/pith/I7XDHQXFWZI7VROAS7MTR4FPVS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I7XDHQXFWZI7VROAS7MTR4FPVS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:I7XDHQXFWZI7VROAS7MTR4FPVS","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":"0c4e2877194352d44e7f119d9dca480d9172af127907492bda60545912c55e34","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-11-05T08:34:26Z","title_canon_sha256":"31b6951e38b0726880d4a0e7c29f2ce5eefa2fff5cc11f602c83c60a9f2ea048"},"schema_version":"1.0","source":{"id":"2311.02597","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.02597","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"arxiv_version","alias_value":"2311.02597v1","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.02597","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"pith_short_12","alias_value":"I7XDHQXFWZI7","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"pith_short_16","alias_value":"I7XDHQXFWZI7VROA","created_at":"2026-07-05T07:09:33Z"},{"alias_kind":"pith_short_8","alias_value":"I7XDHQXF","created_at":"2026-07-05T07:09:33Z"}],"graph_snapshots":[{"event_id":"sha256:bb6560d7f058f76b320f34fc58760faf83b6e8b3a795c96bc87da2b2a5fbcfa7","target":"graph","created_at":"2026-07-05T07:09:33Z","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/2311.02597/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fast disaster impact reporting is crucial in planning humanitarian assistance. Large Language Models (LLMs) are well known for their ability to write coherent text and fulfill a variety of tasks relevant to impact reporting, such as question answering or text summarization. However, LLMs are constrained by the knowledge within their training data and are prone to generating inaccurate, or \"hallucinated\", information. To address this, we introduce a sophisticated pipeline embodied in our tool FloodBrain (floodbrain.com), specialized in generating flood disaster impact reports by extracting and ","authors_text":"Grace Colverd, Leonard Silverberg, Noah Kasmanoff, Paul Darm","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-11-05T08:34:26Z","title":"FloodBrain: Flood Disaster Reporting by Web-based Retrieval Augmented Generation with an LLM"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.02597","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":"sha256:9784c9ebd4b8acca25a463792099800b773aea157b17b4e95bdcddc02329fdae","target":"record","created_at":"2026-07-05T07:09:33Z","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":"0c4e2877194352d44e7f119d9dca480d9172af127907492bda60545912c55e34","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2023-11-05T08:34:26Z","title_canon_sha256":"31b6951e38b0726880d4a0e7c29f2ce5eefa2fff5cc11f602c83c60a9f2ea048"},"schema_version":"1.0","source":{"id":"2311.02597","kind":"arxiv","version":1}},"canonical_sha256":"47ee33c2e5b651fac5c097d938f0afac9cabbb297b6f4d5d2727e2414c5853ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"47ee33c2e5b651fac5c097d938f0afac9cabbb297b6f4d5d2727e2414c5853ae","first_computed_at":"2026-07-05T07:09:33.540400Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:09:33.540400Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Vp3si+qr33LNAF7Mhy+ke9CSWn7QmogDYpVXmJ5eCGMaouZ6nRydgssHlQ2FPpaXhHXnOUNnd7S/K1cqjkSaCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:09:33.540910Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.02597","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9784c9ebd4b8acca25a463792099800b773aea157b17b4e95bdcddc02329fdae","sha256:bb6560d7f058f76b320f34fc58760faf83b6e8b3a795c96bc87da2b2a5fbcfa7"],"state_sha256":"c6ff9248681e9faa513c0e9db92f375d96fb6a32bb5d6c572f2c9bf4d89b2316"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l9jBrhjgdcZSmjN4UteEv1BQcPt73BQpHPdXysN89CSQPoFTj2f0IcKjOi8wt0wi9nquMBKSpiprM2pnKNuBCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T14:59:11.746857Z","bundle_sha256":"e619a1633e07c62231c94ca55a86254f050394eae9747011e2bc22416b39f7b2"}}