{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:HIM3VY6NU6HLBBW6Z2W2VN5PTX","short_pith_number":"pith:HIM3VY6N","canonical_record":{"source":{"id":"2504.16913","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-23T17:39:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"721c7e8db218b279324162b1de655ee5e471548e2eae1735f263d02894946212","abstract_canon_sha256":"78fdf83ef077f7a8177f3218b75f95a983b81bda073061cbf8cac941290156da"},"schema_version":"1.0"},"canonical_sha256":"3a19bae3cda78eb086deceadaab7af9dfb8c03b5966bf22c7a3c7aa7bb1adf8f","source":{"kind":"arxiv","id":"2504.16913","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.16913","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"arxiv_version","alias_value":"2504.16913v1","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16913","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"pith_short_12","alias_value":"HIM3VY6NU6HL","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"pith_short_16","alias_value":"HIM3VY6NU6HLBBW6","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"pith_short_8","alias_value":"HIM3VY6N","created_at":"2026-07-05T10:53:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:HIM3VY6NU6HLBBW6Z2W2VN5PTX","target":"record","payload":{"canonical_record":{"source":{"id":"2504.16913","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-23T17:39:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"721c7e8db218b279324162b1de655ee5e471548e2eae1735f263d02894946212","abstract_canon_sha256":"78fdf83ef077f7a8177f3218b75f95a983b81bda073061cbf8cac941290156da"},"schema_version":"1.0"},"canonical_sha256":"3a19bae3cda78eb086deceadaab7af9dfb8c03b5966bf22c7a3c7aa7bb1adf8f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:53:06.282103Z","signature_b64":"wajrP6hx/7q4ZJB+iIYQzNLKa1UbQjGVJoyX2L6154TdKspxryajlG4o74tdYCo9igwkRBKHnH5AfCbcYDVvCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a19bae3cda78eb086deceadaab7af9dfb8c03b5966bf22c7a3c7aa7bb1adf8f","last_reissued_at":"2026-07-05T10:53:06.281631Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:53:06.281631Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.16913","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":"2026-07-05T10:53:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BEWkiLXjbuIGDuHIzm6jfV9mDuOKmp+CWr40DlHSaSc9wjig39AxcPmpIyecTFESiNHrKZhLD3AgZulJyZ6mBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T20:26:26.183595Z"},"content_sha256":"d83edf03aaf878576de134753bd5443dd3752b0b90fb33cadd58d5ca54b63ff9","schema_version":"1.0","event_id":"sha256:d83edf03aaf878576de134753bd5443dd3752b0b90fb33cadd58d5ca54b63ff9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:HIM3VY6NU6HLBBW6Z2W2VN5PTX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tracing Thought: Using Chain-of-Thought Reasoning to Identify the LLM Behind AI-Generated Text","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Sanasam Ranbir Singh, Shifali Agrahari","submitted_at":"2025-04-23T17:39:49Z","abstract_excerpt":"In recent years, the detection of AI-generated text has become a critical area of research due to concerns about academic integrity, misinformation, and ethical AI deployment. This paper presents COT Fine-tuned, a novel framework for detecting AI-generated text and identifying the specific language model. responsible for generating the text. We propose a dual-task approach, where Task A involves classifying text as AI-generated or human-written, and Task B identifies the specific LLM behind the text. The key innovation of our method lies in the use of Chain-of-Thought reasoning, which enables "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16913","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/2504.16913/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":"2026-07-05T10:53:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6jjKOy9b0i8C93Q2rKqgr6LVslKyb4f6KW0lY1bQk7IoCHnDu3eHoJt8MCT9f/s5/zUMGgai0EPT8BGijaxODg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T20:26:26.184536Z"},"content_sha256":"8a578123acd08f694ae1de46aed28360dadd2ba1b1176c08ad88fdb7ebd1119e","schema_version":"1.0","event_id":"sha256:8a578123acd08f694ae1de46aed28360dadd2ba1b1176c08ad88fdb7ebd1119e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HIM3VY6NU6HLBBW6Z2W2VN5PTX/bundle.json","state_url":"https://pith.science/pith/HIM3VY6NU6HLBBW6Z2W2VN5PTX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HIM3VY6NU6HLBBW6Z2W2VN5PTX/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":"2026-08-04T20:26:26Z","links":{"resolver":"https://pith.science/pith/HIM3VY6NU6HLBBW6Z2W2VN5PTX","bundle":"https://pith.science/pith/HIM3VY6NU6HLBBW6Z2W2VN5PTX/bundle.json","state":"https://pith.science/pith/HIM3VY6NU6HLBBW6Z2W2VN5PTX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HIM3VY6NU6HLBBW6Z2W2VN5PTX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HIM3VY6NU6HLBBW6Z2W2VN5PTX","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":"78fdf83ef077f7a8177f3218b75f95a983b81bda073061cbf8cac941290156da","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-23T17:39:49Z","title_canon_sha256":"721c7e8db218b279324162b1de655ee5e471548e2eae1735f263d02894946212"},"schema_version":"1.0","source":{"id":"2504.16913","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.16913","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"arxiv_version","alias_value":"2504.16913v1","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16913","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"pith_short_12","alias_value":"HIM3VY6NU6HL","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"pith_short_16","alias_value":"HIM3VY6NU6HLBBW6","created_at":"2026-07-05T10:53:06Z"},{"alias_kind":"pith_short_8","alias_value":"HIM3VY6N","created_at":"2026-07-05T10:53:06Z"}],"graph_snapshots":[{"event_id":"sha256:8a578123acd08f694ae1de46aed28360dadd2ba1b1176c08ad88fdb7ebd1119e","target":"graph","created_at":"2026-07-05T10:53:06Z","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/2504.16913/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, the detection of AI-generated text has become a critical area of research due to concerns about academic integrity, misinformation, and ethical AI deployment. This paper presents COT Fine-tuned, a novel framework for detecting AI-generated text and identifying the specific language model. responsible for generating the text. We propose a dual-task approach, where Task A involves classifying text as AI-generated or human-written, and Task B identifies the specific LLM behind the text. The key innovation of our method lies in the use of Chain-of-Thought reasoning, which enables ","authors_text":"Sanasam Ranbir Singh, Shifali Agrahari","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-23T17:39:49Z","title":"Tracing Thought: Using Chain-of-Thought Reasoning to Identify the LLM Behind AI-Generated Text"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16913","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:d83edf03aaf878576de134753bd5443dd3752b0b90fb33cadd58d5ca54b63ff9","target":"record","created_at":"2026-07-05T10:53:06Z","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":"78fdf83ef077f7a8177f3218b75f95a983b81bda073061cbf8cac941290156da","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-23T17:39:49Z","title_canon_sha256":"721c7e8db218b279324162b1de655ee5e471548e2eae1735f263d02894946212"},"schema_version":"1.0","source":{"id":"2504.16913","kind":"arxiv","version":1}},"canonical_sha256":"3a19bae3cda78eb086deceadaab7af9dfb8c03b5966bf22c7a3c7aa7bb1adf8f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3a19bae3cda78eb086deceadaab7af9dfb8c03b5966bf22c7a3c7aa7bb1adf8f","first_computed_at":"2026-07-05T10:53:06.281631Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:53:06.281631Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wajrP6hx/7q4ZJB+iIYQzNLKa1UbQjGVJoyX2L6154TdKspxryajlG4o74tdYCo9igwkRBKHnH5AfCbcYDVvCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:53:06.282103Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.16913","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d83edf03aaf878576de134753bd5443dd3752b0b90fb33cadd58d5ca54b63ff9","sha256:8a578123acd08f694ae1de46aed28360dadd2ba1b1176c08ad88fdb7ebd1119e"],"state_sha256":"0cc90a00592f6cb7724d4a215f4ecffe27afa0556c0bdc769e4c7ac895583fd0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I/J4d+t6JgFcS079yAk7N0X9nrMLScTzjUjBjHqS75PMBPGp0LaD5oJcnzYDHR1rTIyuGVgioScmvp6SIgWwDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T20:26:26.189794Z","bundle_sha256":"2c19b1cc4042a881610cd3d689207b2f69ec7ea4156dccae686ea173faf95886"}}