{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JZI2VGX5EIK2JULTD4ROEAFOHT","short_pith_number":"pith:JZI2VGX5","canonical_record":{"source":{"id":"2402.00905","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-02-01T03:10:26Z","cross_cats_sorted":[],"title_canon_sha256":"8b7bb747ad1d8e231faffdd437e749730cecf73fed5f6917f618495ebe6b47fd","abstract_canon_sha256":"19f44764276718dfd3fd7e9d4f2a21698576212228713645c7572ea8018367ea"},"schema_version":"1.0"},"canonical_sha256":"4e51aa9afd2215a4d1731f22e200ae3cf07e7a594e57563904768180db82c7ea","source":{"kind":"arxiv","id":"2402.00905","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00905","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00905v4","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00905","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"pith_short_12","alias_value":"JZI2VGX5EIK2","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"pith_short_16","alias_value":"JZI2VGX5EIK2JULT","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"pith_short_8","alias_value":"JZI2VGX5","created_at":"2026-07-05T08:32:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JZI2VGX5EIK2JULTD4ROEAFOHT","target":"record","payload":{"canonical_record":{"source":{"id":"2402.00905","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-02-01T03:10:26Z","cross_cats_sorted":[],"title_canon_sha256":"8b7bb747ad1d8e231faffdd437e749730cecf73fed5f6917f618495ebe6b47fd","abstract_canon_sha256":"19f44764276718dfd3fd7e9d4f2a21698576212228713645c7572ea8018367ea"},"schema_version":"1.0"},"canonical_sha256":"4e51aa9afd2215a4d1731f22e200ae3cf07e7a594e57563904768180db82c7ea","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:32:35.693155Z","signature_b64":"3vJ0YyqymT7eOw/ZoE9qeHKxm8J3mfusUoOygMz2uZYApWJGrsKjJ8yb1059W/kL6LmweiMACMj581Sib8OdAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e51aa9afd2215a4d1731f22e200ae3cf07e7a594e57563904768180db82c7ea","last_reissued_at":"2026-07-05T08:32:35.692663Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:32:35.692663Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.00905","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:32:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4LC7iJDtsvHIUYWYiS5NgiimFh/IWiK8MndH3x9fvAdUiAoyfYinM6gcYo4mYLgV8UvO2pmpXxtzqojsbYQQAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T08:35:59.560965Z"},"content_sha256":"2d9e6b5c6a637fa230e2a609bfa818b99a283bd92e2d347a572a6bedea47b240","schema_version":"1.0","event_id":"sha256:2d9e6b5c6a637fa230e2a609bfa818b99a283bd92e2d347a572a6bedea47b240"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JZI2VGX5EIK2JULTD4ROEAFOHT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Chakkrit Tantithamthavorn, Chanathip Pornprasit","submitted_at":"2024-02-01T03:10:26Z","abstract_excerpt":"Context: The rapid evolution of Large Language Models (LLMs) has sparked significant interest in leveraging their capabilities for automating code review processes. Prior studies often focus on developing LLMs for code review automation, yet require expensive resources, which is infeasible for organizations with limited budgets and resources. Thus, fine-tuning and prompt engineering are the two common approaches to leveraging LLMs for code review automation. Objective: We aim to investigate the performance of LLMs-based code review automation based on two contexts, i.e., when LLMs are leverage"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00905","kind":"arxiv","version":4},"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/2402.00905/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":"2026-07-05T08:32:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pb8n7TdXOV8ayrEBg9m3y33ZMH2qBGdAZV7niJQ9320nbbepbKQRdE9UgOXsQAntHmqFmwjtrDFXTLYlqFX+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T08:35:59.561754Z"},"content_sha256":"d7511b8709f60227d8a5f77cfeec8597086c59e44591fdd00cefb81cde4c6f16","schema_version":"1.0","event_id":"sha256:d7511b8709f60227d8a5f77cfeec8597086c59e44591fdd00cefb81cde4c6f16"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JZI2VGX5EIK2JULTD4ROEAFOHT/bundle.json","state_url":"https://pith.science/pith/JZI2VGX5EIK2JULTD4ROEAFOHT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JZI2VGX5EIK2JULTD4ROEAFOHT/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":"2026-08-09T08:35:59Z","links":{"resolver":"https://pith.science/pith/JZI2VGX5EIK2JULTD4ROEAFOHT","bundle":"https://pith.science/pith/JZI2VGX5EIK2JULTD4ROEAFOHT/bundle.json","state":"https://pith.science/pith/JZI2VGX5EIK2JULTD4ROEAFOHT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JZI2VGX5EIK2JULTD4ROEAFOHT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JZI2VGX5EIK2JULTD4ROEAFOHT","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":"19f44764276718dfd3fd7e9d4f2a21698576212228713645c7572ea8018367ea","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-02-01T03:10:26Z","title_canon_sha256":"8b7bb747ad1d8e231faffdd437e749730cecf73fed5f6917f618495ebe6b47fd"},"schema_version":"1.0","source":{"id":"2402.00905","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00905","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00905v4","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00905","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"pith_short_12","alias_value":"JZI2VGX5EIK2","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"pith_short_16","alias_value":"JZI2VGX5EIK2JULT","created_at":"2026-07-05T08:32:35Z"},{"alias_kind":"pith_short_8","alias_value":"JZI2VGX5","created_at":"2026-07-05T08:32:35Z"}],"graph_snapshots":[{"event_id":"sha256:d7511b8709f60227d8a5f77cfeec8597086c59e44591fdd00cefb81cde4c6f16","target":"graph","created_at":"2026-07-05T08:32:35Z","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/2402.00905/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Context: The rapid evolution of Large Language Models (LLMs) has sparked significant interest in leveraging their capabilities for automating code review processes. Prior studies often focus on developing LLMs for code review automation, yet require expensive resources, which is infeasible for organizations with limited budgets and resources. Thus, fine-tuning and prompt engineering are the two common approaches to leveraging LLMs for code review automation. Objective: We aim to investigate the performance of LLMs-based code review automation based on two contexts, i.e., when LLMs are leverage","authors_text":"Chakkrit Tantithamthavorn, Chanathip Pornprasit","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-02-01T03:10:26Z","title":"Fine-Tuning and Prompt Engineering for Large Language Models-based Code Review Automation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00905","kind":"arxiv","version":4},"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":"sha256:2d9e6b5c6a637fa230e2a609bfa818b99a283bd92e2d347a572a6bedea47b240","target":"record","created_at":"2026-07-05T08:32:35Z","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":"19f44764276718dfd3fd7e9d4f2a21698576212228713645c7572ea8018367ea","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2024-02-01T03:10:26Z","title_canon_sha256":"8b7bb747ad1d8e231faffdd437e749730cecf73fed5f6917f618495ebe6b47fd"},"schema_version":"1.0","source":{"id":"2402.00905","kind":"arxiv","version":4}},"canonical_sha256":"4e51aa9afd2215a4d1731f22e200ae3cf07e7a594e57563904768180db82c7ea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4e51aa9afd2215a4d1731f22e200ae3cf07e7a594e57563904768180db82c7ea","first_computed_at":"2026-07-05T08:32:35.692663Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:32:35.692663Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3vJ0YyqymT7eOw/ZoE9qeHKxm8J3mfusUoOygMz2uZYApWJGrsKjJ8yb1059W/kL6LmweiMACMj581Sib8OdAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:32:35.693155Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.00905","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2d9e6b5c6a637fa230e2a609bfa818b99a283bd92e2d347a572a6bedea47b240","sha256:d7511b8709f60227d8a5f77cfeec8597086c59e44591fdd00cefb81cde4c6f16"],"state_sha256":"27e0f60255794a28249bba0d0b0c1ee9b891e0d5f75ce158207a400d86d47cb3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1KXNW8NuB/9z8WjTI17pu2PBN6FiT666VF+K205DnRvtANeoQ5+18gvHJJCq5+07Q1CUSPORqH0RYbrjFyCPAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T08:35:59.567719Z","bundle_sha256":"9999cd3f225038bfe22ed8b501ef598fee54e26877624be8ab5cf9aebac96d97"}}