{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:IGQ4SMZP5BT3TFUILG7P55NOPO","short_pith_number":"pith:IGQ4SMZP","canonical_record":{"source":{"id":"2311.07957","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-11-14T07:20:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e59e8784c8f5d736cc9aafc4dfe32862068fc8d18d3a2440857d8bd7ef71e1d1","abstract_canon_sha256":"a05a2f863acfa847c04dfc34165762721d000635c1a5c6f785b61de869cffb6e"},"schema_version":"1.0"},"canonical_sha256":"41a1c9332fe867b9968859befef5ae7bb7586befd14f976823233519f53818ae","source":{"kind":"arxiv","id":"2311.07957","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.07957","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"arxiv_version","alias_value":"2311.07957v2","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.07957","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"pith_short_12","alias_value":"IGQ4SMZP5BT3","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"pith_short_16","alias_value":"IGQ4SMZP5BT3TFUI","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"pith_short_8","alias_value":"IGQ4SMZP","created_at":"2026-07-05T07:38:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:IGQ4SMZP5BT3TFUILG7P55NOPO","target":"record","payload":{"canonical_record":{"source":{"id":"2311.07957","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-11-14T07:20:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e59e8784c8f5d736cc9aafc4dfe32862068fc8d18d3a2440857d8bd7ef71e1d1","abstract_canon_sha256":"a05a2f863acfa847c04dfc34165762721d000635c1a5c6f785b61de869cffb6e"},"schema_version":"1.0"},"canonical_sha256":"41a1c9332fe867b9968859befef5ae7bb7586befd14f976823233519f53818ae","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:38:32.511194Z","signature_b64":"+nvbz1ShZ9BpWVZVhcy0sOYXl46Uw7XToASCYfDd8/vQKNE2bmrDoASjPl9sJYivnx/wtKF6A64W50nmPIf+Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"41a1c9332fe867b9968859befef5ae7bb7586befd14f976823233519f53818ae","last_reissued_at":"2026-07-05T07:38:32.510781Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:38:32.510781Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.07957","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:38:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nN1TpP3eWHGctwmNoaD0owiQ/8VvyTY4raNyGhYgD3uKkArRB+1FqCQaqAbULenKkK0daK2hKw+epr0oImSECg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T06:19:34.528097Z"},"content_sha256":"cdf7a38b126f298ccc343b2efe385bdff9ee07e4f6ad9a80a3dc33401829f1e1","schema_version":"1.0","event_id":"sha256:cdf7a38b126f298ccc343b2efe385bdff9ee07e4f6ad9a80a3dc33401829f1e1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:IGQ4SMZP5BT3TFUILG7P55NOPO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Language Models are Better Bug Detector Through Code-Pair Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SE","authors_text":"Ahmed Binjahlan, Kamel Alrashedy","submitted_at":"2023-11-14T07:20:57Z","abstract_excerpt":"Large language models (LLMs) such as GPT-3.5 and CodeLlama are powerful models for code generation and understanding. Fine-tuning these models comes with a high computational cost and requires a large labeled dataset. Alternatively, in-context learning techniques allow models to learn downstream tasks with only a few examples. Recently, researchers have shown how in-context learning performs well in bug detection and repair. In this paper, we propose code-pair classification task in which both the buggy and non-buggy versions are given to the model, and the model identifies the buggy ones. We "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.07957","kind":"arxiv","version":2},"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/2311.07957/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":"2026-07-05T07:38:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tH2vk6vxPsitL+ec4PPLO3k+FiPIlLq2L/CK88wajOmNqhURvIaGiL4P34ShzzfCxZOvylXzflGFEdGuuYg2DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T06:19:34.528601Z"},"content_sha256":"e99fc06f12843a59471a6c354923e6d00adaa3a83274db4498f269c763aab6a6","schema_version":"1.0","event_id":"sha256:e99fc06f12843a59471a6c354923e6d00adaa3a83274db4498f269c763aab6a6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IGQ4SMZP5BT3TFUILG7P55NOPO/bundle.json","state_url":"https://pith.science/pith/IGQ4SMZP5BT3TFUILG7P55NOPO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IGQ4SMZP5BT3TFUILG7P55NOPO/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":"2026-08-08T06:19:34Z","links":{"resolver":"https://pith.science/pith/IGQ4SMZP5BT3TFUILG7P55NOPO","bundle":"https://pith.science/pith/IGQ4SMZP5BT3TFUILG7P55NOPO/bundle.json","state":"https://pith.science/pith/IGQ4SMZP5BT3TFUILG7P55NOPO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IGQ4SMZP5BT3TFUILG7P55NOPO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IGQ4SMZP5BT3TFUILG7P55NOPO","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":"a05a2f863acfa847c04dfc34165762721d000635c1a5c6f785b61de869cffb6e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-11-14T07:20:57Z","title_canon_sha256":"e59e8784c8f5d736cc9aafc4dfe32862068fc8d18d3a2440857d8bd7ef71e1d1"},"schema_version":"1.0","source":{"id":"2311.07957","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.07957","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"arxiv_version","alias_value":"2311.07957v2","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.07957","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"pith_short_12","alias_value":"IGQ4SMZP5BT3","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"pith_short_16","alias_value":"IGQ4SMZP5BT3TFUI","created_at":"2026-07-05T07:38:32Z"},{"alias_kind":"pith_short_8","alias_value":"IGQ4SMZP","created_at":"2026-07-05T07:38:32Z"}],"graph_snapshots":[{"event_id":"sha256:e99fc06f12843a59471a6c354923e6d00adaa3a83274db4498f269c763aab6a6","target":"graph","created_at":"2026-07-05T07:38:32Z","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/2311.07957/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) such as GPT-3.5 and CodeLlama are powerful models for code generation and understanding. Fine-tuning these models comes with a high computational cost and requires a large labeled dataset. Alternatively, in-context learning techniques allow models to learn downstream tasks with only a few examples. Recently, researchers have shown how in-context learning performs well in bug detection and repair. In this paper, we propose code-pair classification task in which both the buggy and non-buggy versions are given to the model, and the model identifies the buggy ones. We ","authors_text":"Ahmed Binjahlan, Kamel Alrashedy","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-11-14T07:20:57Z","title":"Language Models are Better Bug Detector Through Code-Pair Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.07957","kind":"arxiv","version":2},"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:cdf7a38b126f298ccc343b2efe385bdff9ee07e4f6ad9a80a3dc33401829f1e1","target":"record","created_at":"2026-07-05T07:38:32Z","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":"a05a2f863acfa847c04dfc34165762721d000635c1a5c6f785b61de869cffb6e","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SE","submitted_at":"2023-11-14T07:20:57Z","title_canon_sha256":"e59e8784c8f5d736cc9aafc4dfe32862068fc8d18d3a2440857d8bd7ef71e1d1"},"schema_version":"1.0","source":{"id":"2311.07957","kind":"arxiv","version":2}},"canonical_sha256":"41a1c9332fe867b9968859befef5ae7bb7586befd14f976823233519f53818ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"41a1c9332fe867b9968859befef5ae7bb7586befd14f976823233519f53818ae","first_computed_at":"2026-07-05T07:38:32.510781Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:38:32.510781Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+nvbz1ShZ9BpWVZVhcy0sOYXl46Uw7XToASCYfDd8/vQKNE2bmrDoASjPl9sJYivnx/wtKF6A64W50nmPIf+Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:38:32.511194Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.07957","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cdf7a38b126f298ccc343b2efe385bdff9ee07e4f6ad9a80a3dc33401829f1e1","sha256:e99fc06f12843a59471a6c354923e6d00adaa3a83274db4498f269c763aab6a6"],"state_sha256":"f4157c8211a5f7a44f2830d788924d804b1803f4b4d38b2c018dbe86f6ac11d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5qjzPVIEBpTxrk7ZYAR3hPWh1ANfw//Vn4XaGSFVabV0poBOzZSojVrmplx2jLOKrVGyYC/VKGZOuBpw3sb5CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T06:19:34.532664Z","bundle_sha256":"dd1c8ef8ffc94300023651ce7daf152b77579ac027e38b6b1ed397cf494bd055"}}