{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OG3T7G3WU7LD52LCL7KELH7RSC","short_pith_number":"pith:OG3T7G3W","canonical_record":{"source":{"id":"2408.13296","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-23T14:48:02Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"b073ebf528ab715fc1db93c9225ba686e3e40b26a1d99eabed2f2a8b8a8bdef5","abstract_canon_sha256":"6fc604894d3d185e7293192cbe02b9c088542106d4fa0711e0d2aaf52468d0b0"},"schema_version":"1.0"},"canonical_sha256":"71b73f9b76a7d63ee9625fd4459ff190a8ff84c576b6295244c9b5f440ed1a16","source":{"kind":"arxiv","id":"2408.13296","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.13296","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"arxiv_version","alias_value":"2408.13296v3","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.13296","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"pith_short_12","alias_value":"OG3T7G3WU7LD","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"pith_short_16","alias_value":"OG3T7G3WU7LD52LC","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"pith_short_8","alias_value":"OG3T7G3W","created_at":"2026-07-05T09:28:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OG3T7G3WU7LD52LCL7KELH7RSC","target":"record","payload":{"canonical_record":{"source":{"id":"2408.13296","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-23T14:48:02Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"b073ebf528ab715fc1db93c9225ba686e3e40b26a1d99eabed2f2a8b8a8bdef5","abstract_canon_sha256":"6fc604894d3d185e7293192cbe02b9c088542106d4fa0711e0d2aaf52468d0b0"},"schema_version":"1.0"},"canonical_sha256":"71b73f9b76a7d63ee9625fd4459ff190a8ff84c576b6295244c9b5f440ed1a16","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:28:13.452054Z","signature_b64":"iBg8mvXHnmZAIjcvrxjtB3/+CfHUrllB1eHkXuiXzSwUJ7N+B8aNbR+NtfcjwdUSCk4HXn94YWnwSWyrCFCxAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71b73f9b76a7d63ee9625fd4459ff190a8ff84c576b6295244c9b5f440ed1a16","last_reissued_at":"2026-07-05T09:28:13.451582Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:28:13.451582Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.13296","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:28:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h6+t4dUypyQTtP2BimNBA/DR9IEAWEbxfl9+gc27gLi0svQR3cDmIWcFxcDf/ytZNE3VuFB63PMV0K3Y2/TyDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T16:24:54.706696Z"},"content_sha256":"b175ad3ac4a4c7e88a5213b5db190960d5cb22b118cf9f32fe1c6d102fb53ffc","schema_version":"1.0","event_id":"sha256:b175ad3ac4a4c7e88a5213b5db190960d5cb22b118cf9f32fe1c6d102fb53ffc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OG3T7G3WU7LD52LCL7KELH7RSC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.LG","authors_text":"Aafaq Khan, Ahtsham Zafar, Arsalan Shahid, Venkatesh Balavadhani Parthasarathy","submitted_at":"2024-08-23T14:48:02Z","abstract_excerpt":"This report examines the fine-tuning of Large Language Models (LLMs), integrating theoretical insights with practical applications. It outlines the historical evolution of LLMs from traditional Natural Language Processing (NLP) models to their pivotal role in AI. A comparison of fine-tuning methodologies, including supervised, unsupervised, and instruction-based approaches, highlights their applicability to different tasks. The report introduces a structured seven-stage pipeline for fine-tuning LLMs, spanning data preparation, model initialization, hyperparameter tuning, and model deployment. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.13296","kind":"arxiv","version":3},"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/2408.13296/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":"2026-07-05T09:28:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I1cK447yV7rE7UPUhBGBinwtE9p8aIU9OrTjXbZkrrf36/SLdvJERk3QUNVFEaGPSflEBrzdxt3ci4caE9GHCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T16:24:54.707019Z"},"content_sha256":"b6c55fe378db561b0121e9e146bbbd0989dad006788d12f1354bd569747a8849","schema_version":"1.0","event_id":"sha256:b6c55fe378db561b0121e9e146bbbd0989dad006788d12f1354bd569747a8849"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OG3T7G3WU7LD52LCL7KELH7RSC/bundle.json","state_url":"https://pith.science/pith/OG3T7G3WU7LD52LCL7KELH7RSC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OG3T7G3WU7LD52LCL7KELH7RSC/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":"2026-08-06T16:24:54Z","links":{"resolver":"https://pith.science/pith/OG3T7G3WU7LD52LCL7KELH7RSC","bundle":"https://pith.science/pith/OG3T7G3WU7LD52LCL7KELH7RSC/bundle.json","state":"https://pith.science/pith/OG3T7G3WU7LD52LCL7KELH7RSC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OG3T7G3WU7LD52LCL7KELH7RSC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OG3T7G3WU7LD52LCL7KELH7RSC","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":"6fc604894d3d185e7293192cbe02b9c088542106d4fa0711e0d2aaf52468d0b0","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-23T14:48:02Z","title_canon_sha256":"b073ebf528ab715fc1db93c9225ba686e3e40b26a1d99eabed2f2a8b8a8bdef5"},"schema_version":"1.0","source":{"id":"2408.13296","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.13296","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"arxiv_version","alias_value":"2408.13296v3","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.13296","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"pith_short_12","alias_value":"OG3T7G3WU7LD","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"pith_short_16","alias_value":"OG3T7G3WU7LD52LC","created_at":"2026-07-05T09:28:13Z"},{"alias_kind":"pith_short_8","alias_value":"OG3T7G3W","created_at":"2026-07-05T09:28:13Z"}],"graph_snapshots":[{"event_id":"sha256:b6c55fe378db561b0121e9e146bbbd0989dad006788d12f1354bd569747a8849","target":"graph","created_at":"2026-07-05T09:28:13Z","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/2408.13296/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This report examines the fine-tuning of Large Language Models (LLMs), integrating theoretical insights with practical applications. It outlines the historical evolution of LLMs from traditional Natural Language Processing (NLP) models to their pivotal role in AI. A comparison of fine-tuning methodologies, including supervised, unsupervised, and instruction-based approaches, highlights their applicability to different tasks. The report introduces a structured seven-stage pipeline for fine-tuning LLMs, spanning data preparation, model initialization, hyperparameter tuning, and model deployment. ","authors_text":"Aafaq Khan, Ahtsham Zafar, Arsalan Shahid, Venkatesh Balavadhani Parthasarathy","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-23T14:48:02Z","title":"The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.13296","kind":"arxiv","version":3},"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:b175ad3ac4a4c7e88a5213b5db190960d5cb22b118cf9f32fe1c6d102fb53ffc","target":"record","created_at":"2026-07-05T09:28:13Z","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":"6fc604894d3d185e7293192cbe02b9c088542106d4fa0711e0d2aaf52468d0b0","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-23T14:48:02Z","title_canon_sha256":"b073ebf528ab715fc1db93c9225ba686e3e40b26a1d99eabed2f2a8b8a8bdef5"},"schema_version":"1.0","source":{"id":"2408.13296","kind":"arxiv","version":3}},"canonical_sha256":"71b73f9b76a7d63ee9625fd4459ff190a8ff84c576b6295244c9b5f440ed1a16","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"71b73f9b76a7d63ee9625fd4459ff190a8ff84c576b6295244c9b5f440ed1a16","first_computed_at":"2026-07-05T09:28:13.451582Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:28:13.451582Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iBg8mvXHnmZAIjcvrxjtB3/+CfHUrllB1eHkXuiXzSwUJ7N+B8aNbR+NtfcjwdUSCk4HXn94YWnwSWyrCFCxAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:28:13.452054Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.13296","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b175ad3ac4a4c7e88a5213b5db190960d5cb22b118cf9f32fe1c6d102fb53ffc","sha256:b6c55fe378db561b0121e9e146bbbd0989dad006788d12f1354bd569747a8849"],"state_sha256":"523a099e0c8baa377be0fa8006fc2e621740ef2b3ff6c7ed5f63aa08ef4cfef3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"57nbkQXk+qDY6VWIVvZHRchIXNa0alH3l91fYcBAi8pK0H2VGnQYIoTNaLEXoaveMv2qK/ZUV6F8FZ2isI17Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T16:24:54.710437Z","bundle_sha256":"1c03a9adb21c1eeb63ff7e174a475c163b9cd4ece31a1b7097da48c8b1f01f44"}}