{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:BDB3XOQMFNBBTD2TSGVQTTAIEA","short_pith_number":"pith:BDB3XOQM","canonical_record":{"source":{"id":"2507.05157","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-07T16:13:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ee186af27f6ccd3a9d5a8f87a33d4544f79da52fd1460b62977651d7eced2b1e","abstract_canon_sha256":"3fa0fb8d9fb6bbc8fabc1ea80d35980334fc8148714e4fac8b04b85ee7536177"},"schema_version":"1.0"},"canonical_sha256":"08c3bbba0c2b42198f5391ab09cc082008fc18fb2915686530c9ce84709cd9a0","source":{"kind":"arxiv","id":"2507.05157","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.05157","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"arxiv_version","alias_value":"2507.05157v1","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.05157","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"pith_short_12","alias_value":"BDB3XOQMFNBB","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"BDB3XOQMFNBBTD2T","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"BDB3XOQM","created_at":"2026-07-05T11:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:BDB3XOQMFNBBTD2TSGVQTTAIEA","target":"record","payload":{"canonical_record":{"source":{"id":"2507.05157","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-07T16:13:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"ee186af27f6ccd3a9d5a8f87a33d4544f79da52fd1460b62977651d7eced2b1e","abstract_canon_sha256":"3fa0fb8d9fb6bbc8fabc1ea80d35980334fc8148714e4fac8b04b85ee7536177"},"schema_version":"1.0"},"canonical_sha256":"08c3bbba0c2b42198f5391ab09cc082008fc18fb2915686530c9ce84709cd9a0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:33:10.007794Z","signature_b64":"WTKs6aprTDHYr6lPiSwxY/ohgW4CTCGBrlMg/o2z7RvDmTYBHgw7bI3dV0O2L1zvlvtZgIKZVJIK9IzPFzkkAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08c3bbba0c2b42198f5391ab09cc082008fc18fb2915686530c9ce84709cd9a0","last_reissued_at":"2026-07-05T11:33:10.007324Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:33:10.007324Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.05157","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":"2026-07-05T11:33:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zE32aZ2rna/VliEABw4d7JLBuVFrI06Fb/o7kJS8p3XGEI6IoOzMrNTNr3R0kGI3yuxvxsUJPFFmA3kK7G1ZDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:42:39.133144Z"},"content_sha256":"303ee46939ec546d3518b709e6407f618dec1e292fdc2a5533f9574eec299503","schema_version":"1.0","event_id":"sha256:303ee46939ec546d3518b709e6407f618dec1e292fdc2a5533f9574eec299503"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:BDB3XOQMFNBBTD2TSGVQTTAIEA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Abdul Rahman, Budhaditya Roy, Chinnappa Guggilla, Edward Bowen, Trupti Ramdas Chavan","submitted_at":"2025-07-07T16:13:13Z","abstract_excerpt":"Large Language Models (LLMs) possess an extraordinary capability to produce text that is not only coherent and contextually relevant but also strikingly similar to human writing. They adapt to various styles and genres, producing content that is both grammatically correct and semantically meaningful. Recently, LLMs have been misused to create highly realistic phishing emails, spread fake news, generate code to automate cyber crime, and write fraudulent scientific articles. Additionally, in many real-world applications, the generated content including style and topic and the generator model are"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.05157","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/2507.05157/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":"2026-07-05T11:33:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CFgAHP3XkKTAW0meL9OR6VbIoVxG5PEi15BwlivAhi3R/z1ZxZ+iO2hYs27BjtKuVhKFBvvLLN5lkjhVU0ueAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:42:39.133655Z"},"content_sha256":"ddca7f2db39663e90df3bdaef37f4511a5b92745dd96152977e921a9d49e1f9b","schema_version":"1.0","event_id":"sha256:ddca7f2db39663e90df3bdaef37f4511a5b92745dd96152977e921a9d49e1f9b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BDB3XOQMFNBBTD2TSGVQTTAIEA/bundle.json","state_url":"https://pith.science/pith/BDB3XOQMFNBBTD2TSGVQTTAIEA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BDB3XOQMFNBBTD2TSGVQTTAIEA/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":"2026-08-04T13:42:39Z","links":{"resolver":"https://pith.science/pith/BDB3XOQMFNBBTD2TSGVQTTAIEA","bundle":"https://pith.science/pith/BDB3XOQMFNBBTD2TSGVQTTAIEA/bundle.json","state":"https://pith.science/pith/BDB3XOQMFNBBTD2TSGVQTTAIEA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BDB3XOQMFNBBTD2TSGVQTTAIEA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BDB3XOQMFNBBTD2TSGVQTTAIEA","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":"3fa0fb8d9fb6bbc8fabc1ea80d35980334fc8148714e4fac8b04b85ee7536177","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-07T16:13:13Z","title_canon_sha256":"ee186af27f6ccd3a9d5a8f87a33d4544f79da52fd1460b62977651d7eced2b1e"},"schema_version":"1.0","source":{"id":"2507.05157","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.05157","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"arxiv_version","alias_value":"2507.05157v1","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.05157","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"pith_short_12","alias_value":"BDB3XOQMFNBB","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"BDB3XOQMFNBBTD2T","created_at":"2026-07-05T11:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"BDB3XOQM","created_at":"2026-07-05T11:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:ddca7f2db39663e90df3bdaef37f4511a5b92745dd96152977e921a9d49e1f9b","target":"graph","created_at":"2026-07-05T11:33:10Z","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/2507.05157/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) possess an extraordinary capability to produce text that is not only coherent and contextually relevant but also strikingly similar to human writing. They adapt to various styles and genres, producing content that is both grammatically correct and semantically meaningful. Recently, LLMs have been misused to create highly realistic phishing emails, spread fake news, generate code to automate cyber crime, and write fraudulent scientific articles. Additionally, in many real-world applications, the generated content including style and topic and the generator model are","authors_text":"Abdul Rahman, Budhaditya Roy, Chinnappa Guggilla, Edward Bowen, Trupti Ramdas Chavan","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-07T16:13:13Z","title":"AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.05157","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":"sha256:303ee46939ec546d3518b709e6407f618dec1e292fdc2a5533f9574eec299503","target":"record","created_at":"2026-07-05T11:33:10Z","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":"3fa0fb8d9fb6bbc8fabc1ea80d35980334fc8148714e4fac8b04b85ee7536177","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-07T16:13:13Z","title_canon_sha256":"ee186af27f6ccd3a9d5a8f87a33d4544f79da52fd1460b62977651d7eced2b1e"},"schema_version":"1.0","source":{"id":"2507.05157","kind":"arxiv","version":1}},"canonical_sha256":"08c3bbba0c2b42198f5391ab09cc082008fc18fb2915686530c9ce84709cd9a0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"08c3bbba0c2b42198f5391ab09cc082008fc18fb2915686530c9ce84709cd9a0","first_computed_at":"2026-07-05T11:33:10.007324Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:33:10.007324Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WTKs6aprTDHYr6lPiSwxY/ohgW4CTCGBrlMg/o2z7RvDmTYBHgw7bI3dV0O2L1zvlvtZgIKZVJIK9IzPFzkkAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:33:10.007794Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.05157","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:303ee46939ec546d3518b709e6407f618dec1e292fdc2a5533f9574eec299503","sha256:ddca7f2db39663e90df3bdaef37f4511a5b92745dd96152977e921a9d49e1f9b"],"state_sha256":"085a9eeb8bfd19f5b4f391b6c2fd77d7d5e18ad370e514436b9df145e4db35e8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JBUEVA8xLxxDL1OxHF7FIvouiPFCkPFXRh0DHFcCulq0qW5tp6bpo40LFp+o0lb7D99iZz83aVxbUIlxMTnqDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T13:42:39.137654Z","bundle_sha256":"6230eae25a89156e1be128413fb6dba107ac6c03eacaf0d55cda91b7065ec10d"}}