{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:JEL2OHUR6E2ETWSR64EVPLUHBH","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":"d5308c4e85c6794a6f2ec4b3081fc7f6a0074a14c544986d1fa2c35cf165d053","cross_cats_sorted":["cs.AI","cs.CY","cs.IR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-09T07:10:19Z","title_canon_sha256":"9392c5b98e9c33fd3842ff608c6834be0c2dce56ae1e0f48afd890d9ddd80ed5"},"schema_version":"1.0","source":{"id":"2309.04704","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.04704","created_at":"2026-07-05T06:49:07Z"},{"alias_kind":"arxiv_version","alias_value":"2309.04704v1","created_at":"2026-07-05T06:49:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.04704","created_at":"2026-07-05T06:49:07Z"},{"alias_kind":"pith_short_12","alias_value":"JEL2OHUR6E2E","created_at":"2026-07-05T06:49:07Z"},{"alias_kind":"pith_short_16","alias_value":"JEL2OHUR6E2ETWSR","created_at":"2026-07-05T06:49:07Z"},{"alias_kind":"pith_short_8","alias_value":"JEL2OHUR","created_at":"2026-07-05T06:49:07Z"}],"graph_snapshots":[{"event_id":"sha256:1d321e64dd616f36c9c865f555e8245db6ad0df7d018c7ade5640e9c02b91040","target":"graph","created_at":"2026-07-05T06:49:07Z","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/2309.04704/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The paper considers the possibility of fine-tuning Llama 2 large language model (LLM) for the disinformation analysis and fake news detection. For fine-tuning, the PEFT/LoRA based approach was used. In the study, the model was fine-tuned for the following tasks: analysing a text on revealing disinformation and propaganda narratives, fact checking, fake news detection, manipulation analytics, extracting named entities with their sentiments. The obtained results show that the fine-tuned Llama 2 model can perform a deep analysis of texts and reveal complex styles and narratives. Extracted sentime","authors_text":"Bohdan M. Pavlyshenko","cross_cats":["cs.AI","cs.CY","cs.IR","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-09T07:10:19Z","title":"Analysis of Disinformation and Fake News Detection Using Fine-Tuned Large Language Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.04704","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:c35f7701a182d70e230eff0d2d9d1e7cf525c6575cd92e0d9ff7427bd5873072","target":"record","created_at":"2026-07-05T06:49:07Z","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":"d5308c4e85c6794a6f2ec4b3081fc7f6a0074a14c544986d1fa2c35cf165d053","cross_cats_sorted":["cs.AI","cs.CY","cs.IR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-09T07:10:19Z","title_canon_sha256":"9392c5b98e9c33fd3842ff608c6834be0c2dce56ae1e0f48afd890d9ddd80ed5"},"schema_version":"1.0","source":{"id":"2309.04704","kind":"arxiv","version":1}},"canonical_sha256":"4917a71e91f13449da51f70957ae8709d79184ce68686772ac3e07c2279bd84a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4917a71e91f13449da51f70957ae8709d79184ce68686772ac3e07c2279bd84a","first_computed_at":"2026-07-05T06:49:07.625688Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:49:07.625688Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4Jf2mwN7gOCBDfCxVdNia3LDY7xQ6eOMzc8NNZK1Vi0zvKHzeQJmeCw22SUEWc1j0zZxpjFLDCLfiORp4hQ5Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:49:07.626097Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.04704","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c35f7701a182d70e230eff0d2d9d1e7cf525c6575cd92e0d9ff7427bd5873072","sha256:1d321e64dd616f36c9c865f555e8245db6ad0df7d018c7ade5640e9c02b91040"],"state_sha256":"05669bc4a2a7f51a3b6bc909dd74769f62f48c7e1f187ca8f3583ed41e54b505"}