{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:HGLNEGE6643TJTUSBB5XKC4Q23","short_pith_number":"pith:HGLNEGE6","canonical_record":{"source":{"id":"2306.08568","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-14T15:18:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"35981c93fff9174666b1739ac0baa0093458a862d8a9fe0b3d7d5cc527568caf","abstract_canon_sha256":"e8be5acd8df6ed1a35be3a28c36ccf304ab43932083b697e00fc641fc7cd79ab"},"schema_version":"1.0"},"canonical_sha256":"3996d2189ef73734ce92087b750b90d6ca5dcf11ed69c1ef430e2f5fd57e4f3a","source":{"kind":"arxiv","id":"2306.08568","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.08568","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"arxiv_version","alias_value":"2306.08568v2","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.08568","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"pith_short_12","alias_value":"HGLNEGE6643T","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"pith_short_16","alias_value":"HGLNEGE6643TJTUS","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"pith_short_8","alias_value":"HGLNEGE6","created_at":"2026-07-05T11:09:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:HGLNEGE6643TJTUSBB5XKC4Q23","target":"record","payload":{"canonical_record":{"source":{"id":"2306.08568","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-14T15:18:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"35981c93fff9174666b1739ac0baa0093458a862d8a9fe0b3d7d5cc527568caf","abstract_canon_sha256":"e8be5acd8df6ed1a35be3a28c36ccf304ab43932083b697e00fc641fc7cd79ab"},"schema_version":"1.0"},"canonical_sha256":"3996d2189ef73734ce92087b750b90d6ca5dcf11ed69c1ef430e2f5fd57e4f3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:56.889540Z","signature_b64":"ngeC7l+fDsDah8h6DFCCzdvWPxe+ddtAsSI18is/HkaaLWh/8DDgz7dpG/VRUdZ4yGAKlWDEc05WXqObi/UCAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3996d2189ef73734ce92087b750b90d6ca5dcf11ed69c1ef430e2f5fd57e4f3a","last_reissued_at":"2026-07-05T11:09:56.889051Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:56.889051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.08568","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":"2026-07-05T11:09:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zD/DKVpr5vHDrAHJbL95dE7jde6InDMxLH9RCjKQGGk3oE2cdQiLPygthEcEDlIiWyk1D1/+vyPkn7yWxXb8CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T16:17:04.515706Z"},"content_sha256":"ba3c7c847baa6d82ced6d092a7e78bce1db42fc2dbbc0ef0a54fbf14d172528a","schema_version":"1.0","event_id":"sha256:ba3c7c847baa6d82ced6d092a7e78bce1db42fc2dbbc0ef0a54fbf14d172528a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:HGLNEGE6643TJTUSBB5XKC4Q23","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"WizardCoder: Empowering Code Large Language Models with Evol-Instruct","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Can Xu, Chongyang Tao, Daxin Jiang, Jing Ma, Pu Zhao, Qingfeng Sun, Qingwei Lin, Wenxiang Hu, Xiubo Geng, Ziyang Luo","submitted_at":"2023-06-14T15:18:48Z","abstract_excerpt":"Code Large Language Models (Code LLMs), such as StarCoder, have demonstrated exceptional performance in code-related tasks. However, most existing models are solely pre-trained on extensive raw code data without instruction fine-tuning. In this paper, we introduce WizardCoder, which empowers Code LLMs with complex instruction fine-tuning, by adapting the Evol-Instruct method to the domain of code. Through comprehensive experiments on four prominent code generation benchmarks, namely HumanEval, HumanEval+, MBPP, and DS-1000, we unveil the exceptional capabilities of our model. It surpasses all "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.08568","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/2306.08568/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":"2026-07-05T11:09:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dJi/FZRJjM4MeJ0Yi3BIZ9v51Kofe1R4CGGSPRGXWDcnGOC0HS0TFqcSD6ituTEBuzsD0VVG0OgRthEngE1TBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T16:17:04.516276Z"},"content_sha256":"c85043d54d3ada5b5d5160c1347a2b7c06065b88a9d72870173a5a9dff2422d0","schema_version":"1.0","event_id":"sha256:c85043d54d3ada5b5d5160c1347a2b7c06065b88a9d72870173a5a9dff2422d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HGLNEGE6643TJTUSBB5XKC4Q23/bundle.json","state_url":"https://pith.science/pith/HGLNEGE6643TJTUSBB5XKC4Q23/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HGLNEGE6643TJTUSBB5XKC4Q23/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":"2026-08-17T16:17:04Z","links":{"resolver":"https://pith.science/pith/HGLNEGE6643TJTUSBB5XKC4Q23","bundle":"https://pith.science/pith/HGLNEGE6643TJTUSBB5XKC4Q23/bundle.json","state":"https://pith.science/pith/HGLNEGE6643TJTUSBB5XKC4Q23/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HGLNEGE6643TJTUSBB5XKC4Q23/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:HGLNEGE6643TJTUSBB5XKC4Q23","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":"e8be5acd8df6ed1a35be3a28c36ccf304ab43932083b697e00fc641fc7cd79ab","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-14T15:18:48Z","title_canon_sha256":"35981c93fff9174666b1739ac0baa0093458a862d8a9fe0b3d7d5cc527568caf"},"schema_version":"1.0","source":{"id":"2306.08568","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.08568","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"arxiv_version","alias_value":"2306.08568v2","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.08568","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"pith_short_12","alias_value":"HGLNEGE6643T","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"pith_short_16","alias_value":"HGLNEGE6643TJTUS","created_at":"2026-07-05T11:09:56Z"},{"alias_kind":"pith_short_8","alias_value":"HGLNEGE6","created_at":"2026-07-05T11:09:56Z"}],"graph_snapshots":[{"event_id":"sha256:c85043d54d3ada5b5d5160c1347a2b7c06065b88a9d72870173a5a9dff2422d0","target":"graph","created_at":"2026-07-05T11:09:56Z","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/2306.08568/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Code Large Language Models (Code LLMs), such as StarCoder, have demonstrated exceptional performance in code-related tasks. However, most existing models are solely pre-trained on extensive raw code data without instruction fine-tuning. In this paper, we introduce WizardCoder, which empowers Code LLMs with complex instruction fine-tuning, by adapting the Evol-Instruct method to the domain of code. Through comprehensive experiments on four prominent code generation benchmarks, namely HumanEval, HumanEval+, MBPP, and DS-1000, we unveil the exceptional capabilities of our model. It surpasses all ","authors_text":"Can Xu, Chongyang Tao, Daxin Jiang, Jing Ma, Pu Zhao, Qingfeng Sun, Qingwei Lin, Wenxiang Hu, Xiubo Geng, Ziyang Luo","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-14T15:18:48Z","title":"WizardCoder: Empowering Code Large Language Models with Evol-Instruct"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.08568","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:ba3c7c847baa6d82ced6d092a7e78bce1db42fc2dbbc0ef0a54fbf14d172528a","target":"record","created_at":"2026-07-05T11:09:56Z","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":"e8be5acd8df6ed1a35be3a28c36ccf304ab43932083b697e00fc641fc7cd79ab","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-06-14T15:18:48Z","title_canon_sha256":"35981c93fff9174666b1739ac0baa0093458a862d8a9fe0b3d7d5cc527568caf"},"schema_version":"1.0","source":{"id":"2306.08568","kind":"arxiv","version":2}},"canonical_sha256":"3996d2189ef73734ce92087b750b90d6ca5dcf11ed69c1ef430e2f5fd57e4f3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3996d2189ef73734ce92087b750b90d6ca5dcf11ed69c1ef430e2f5fd57e4f3a","first_computed_at":"2026-07-05T11:09:56.889051Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:56.889051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ngeC7l+fDsDah8h6DFCCzdvWPxe+ddtAsSI18is/HkaaLWh/8DDgz7dpG/VRUdZ4yGAKlWDEc05WXqObi/UCAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:56.889540Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.08568","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba3c7c847baa6d82ced6d092a7e78bce1db42fc2dbbc0ef0a54fbf14d172528a","sha256:c85043d54d3ada5b5d5160c1347a2b7c06065b88a9d72870173a5a9dff2422d0"],"state_sha256":"590e07f7bbe8cafd678a2552eb49049225d29fdeacd12492fddb4d4c2398d38b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8AUa4hsyQKQo4glvufKVS2rotyN0x6VyZ0eVMDyEvEcL3FAOkkCXxvnc/RO2qejaioJEeMHJIRKN9jebq2GpDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T16:17:04.519477Z","bundle_sha256":"f43b773ae9f7b69bd2fd8f7a5c9d2ed699d36191368a6b251448df547bc8b96f"}}