{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:265M5SIS6CNSVNDNKX47ULKGPZ","short_pith_number":"pith:265M5SIS","canonical_record":{"source":{"id":"2409.16452","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-09-24T20:44:30Z","cross_cats_sorted":[],"title_canon_sha256":"b29ece0cb27dbb9265c05e30abadecc7b5caa8e63ade5a25121cf0b5f11a0fd2","abstract_canon_sha256":"848eddf8d2c07e9bb121e014d3ce74062148aaadf70f56362d5a3a12c7a37595"},"schema_version":"1.0"},"canonical_sha256":"d7bacec912f09b2ab46d55f9fa2d467e6f5280de338742ebb077110ddd57d56a","source":{"kind":"arxiv","id":"2409.16452","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.16452","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"arxiv_version","alias_value":"2409.16452v2","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.16452","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"pith_short_12","alias_value":"265M5SIS6CNS","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"pith_short_16","alias_value":"265M5SIS6CNSVNDN","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"pith_short_8","alias_value":"265M5SIS","created_at":"2026-07-05T11:03:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:265M5SIS6CNSVNDNKX47ULKGPZ","target":"record","payload":{"canonical_record":{"source":{"id":"2409.16452","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-09-24T20:44:30Z","cross_cats_sorted":[],"title_canon_sha256":"b29ece0cb27dbb9265c05e30abadecc7b5caa8e63ade5a25121cf0b5f11a0fd2","abstract_canon_sha256":"848eddf8d2c07e9bb121e014d3ce74062148aaadf70f56362d5a3a12c7a37595"},"schema_version":"1.0"},"canonical_sha256":"d7bacec912f09b2ab46d55f9fa2d467e6f5280de338742ebb077110ddd57d56a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:03:52.055524Z","signature_b64":"eKBNkVVXMk4KyqVYkbO3zS0Tj66j9YyV3dHJZzHt2VvPlzX3TzFamYya1HgUQsQjMRSrU0QzHgnB1XWNiKn6BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d7bacec912f09b2ab46d55f9fa2d467e6f5280de338742ebb077110ddd57d56a","last_reissued_at":"2026-07-05T11:03:52.055043Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:03:52.055043Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.16452","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":"2026-07-05T11:03:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fDT26/tlEMRq7/lebfnftMPBHDaSJ6JQl7G/hQ5u9MbPnZW4XxHnhC8hth1hxkuhSdnPlrbBMTMac//WPNrmBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T19:32:10.520837Z"},"content_sha256":"a6124421d93c9e6dc0ae7aa9c17fd617f2635aae334594e8e52432cddbb73e12","schema_version":"1.0","event_id":"sha256:a6124421d93c9e6dc0ae7aa9c17fd617f2635aae334594e8e52432cddbb73e12"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:265M5SIS6CNSVNDNKX47ULKGPZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FMDLlama: Financial Misinformation Detection based on Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jimin Huang, Kailai Yang, Qianqian Xie, Sophia Ananiadou, Xin Zhang, Zhiwei Liu","submitted_at":"2024-09-24T20:44:30Z","abstract_excerpt":"The emergence of social media has made the spread of misinformation easier. In the financial domain, the accuracy of information is crucial for various aspects of financial market, which has made financial misinformation detection (FMD) an urgent problem that needs to be addressed. Large language models (LLMs) have demonstrated outstanding performance in various fields. However, current studies mostly rely on traditional methods and have not explored the application of LLMs in the field of FMD. The main reason is the lack of FMD instruction tuning datasets and evaluation benchmarks. In this pa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.16452","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/2409.16452/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":"2026-07-05T11:03:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dkSbu8ROdo0e+MpTSIFdSHAV0XyY9UBFMuOdkRGtf4t0MdVhLiMQnlXf2GZjZwvCmntTMmjipdEqMgMR8WM4CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T19:32:10.521752Z"},"content_sha256":"91d15f660b9acb1fabc5a197f467fe757096d962b2bc2b0df38258aa83bca4dd","schema_version":"1.0","event_id":"sha256:91d15f660b9acb1fabc5a197f467fe757096d962b2bc2b0df38258aa83bca4dd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/265M5SIS6CNSVNDNKX47ULKGPZ/bundle.json","state_url":"https://pith.science/pith/265M5SIS6CNSVNDNKX47ULKGPZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/265M5SIS6CNSVNDNKX47ULKGPZ/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":"2026-08-18T19:32:10Z","links":{"resolver":"https://pith.science/pith/265M5SIS6CNSVNDNKX47ULKGPZ","bundle":"https://pith.science/pith/265M5SIS6CNSVNDNKX47ULKGPZ/bundle.json","state":"https://pith.science/pith/265M5SIS6CNSVNDNKX47ULKGPZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/265M5SIS6CNSVNDNKX47ULKGPZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:265M5SIS6CNSVNDNKX47ULKGPZ","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":"848eddf8d2c07e9bb121e014d3ce74062148aaadf70f56362d5a3a12c7a37595","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-09-24T20:44:30Z","title_canon_sha256":"b29ece0cb27dbb9265c05e30abadecc7b5caa8e63ade5a25121cf0b5f11a0fd2"},"schema_version":"1.0","source":{"id":"2409.16452","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.16452","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"arxiv_version","alias_value":"2409.16452v2","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.16452","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"pith_short_12","alias_value":"265M5SIS6CNS","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"pith_short_16","alias_value":"265M5SIS6CNSVNDN","created_at":"2026-07-05T11:03:52Z"},{"alias_kind":"pith_short_8","alias_value":"265M5SIS","created_at":"2026-07-05T11:03:52Z"}],"graph_snapshots":[{"event_id":"sha256:91d15f660b9acb1fabc5a197f467fe757096d962b2bc2b0df38258aa83bca4dd","target":"graph","created_at":"2026-07-05T11:03:52Z","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/2409.16452/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The emergence of social media has made the spread of misinformation easier. In the financial domain, the accuracy of information is crucial for various aspects of financial market, which has made financial misinformation detection (FMD) an urgent problem that needs to be addressed. Large language models (LLMs) have demonstrated outstanding performance in various fields. However, current studies mostly rely on traditional methods and have not explored the application of LLMs in the field of FMD. The main reason is the lack of FMD instruction tuning datasets and evaluation benchmarks. In this pa","authors_text":"Jimin Huang, Kailai Yang, Qianqian Xie, Sophia Ananiadou, Xin Zhang, Zhiwei Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-09-24T20:44:30Z","title":"FMDLlama: Financial Misinformation Detection based on Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.16452","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:a6124421d93c9e6dc0ae7aa9c17fd617f2635aae334594e8e52432cddbb73e12","target":"record","created_at":"2026-07-05T11:03:52Z","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":"848eddf8d2c07e9bb121e014d3ce74062148aaadf70f56362d5a3a12c7a37595","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-09-24T20:44:30Z","title_canon_sha256":"b29ece0cb27dbb9265c05e30abadecc7b5caa8e63ade5a25121cf0b5f11a0fd2"},"schema_version":"1.0","source":{"id":"2409.16452","kind":"arxiv","version":2}},"canonical_sha256":"d7bacec912f09b2ab46d55f9fa2d467e6f5280de338742ebb077110ddd57d56a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7bacec912f09b2ab46d55f9fa2d467e6f5280de338742ebb077110ddd57d56a","first_computed_at":"2026-07-05T11:03:52.055043Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:03:52.055043Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eKBNkVVXMk4KyqVYkbO3zS0Tj66j9YyV3dHJZzHt2VvPlzX3TzFamYya1HgUQsQjMRSrU0QzHgnB1XWNiKn6BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:03:52.055524Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.16452","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a6124421d93c9e6dc0ae7aa9c17fd617f2635aae334594e8e52432cddbb73e12","sha256:91d15f660b9acb1fabc5a197f467fe757096d962b2bc2b0df38258aa83bca4dd"],"state_sha256":"a7616ea64840679172a0b759d56bee139c88e0f919d35cffc999b0f6252e0a7f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r559OiSXrux9MARHQZtrtk8X3cPGvoQI53J3vjngoJmyvGYsSwOhq3KShg9KIPZ7huSwcBlau77kiy0GlK2cDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T19:32:10.527341Z","bundle_sha256":"5cb7609624a0509a106b3bd6508ee10b9f568530d059168d347a45580f7ef853"}}