{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:CJP2WNIYH3FDWOMGY76XSZBHNZ","short_pith_number":"pith:CJP2WNIY","canonical_record":{"source":{"id":"2405.05767","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-05-09T13:44:04Z","cross_cats_sorted":[],"title_canon_sha256":"d188286be5c254287efdc3e0f0a2c46f938dd2d908e0140392996c0e95e9f6e0","abstract_canon_sha256":"8c765fa9099f250f1e923bba485c75b7c585702eff1d591486e1bbafd4260424"},"schema_version":"1.0"},"canonical_sha256":"125fab35183eca3b3986c7fd7964276e5b44ee10bbecdfc8100be36ca163f98d","source":{"kind":"arxiv","id":"2405.05767","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.05767","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"arxiv_version","alias_value":"2405.05767v1","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.05767","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"pith_short_12","alias_value":"CJP2WNIYH3FD","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"pith_short_16","alias_value":"CJP2WNIYH3FDWOMG","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"pith_short_8","alias_value":"CJP2WNIY","created_at":"2026-07-05T08:17:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:CJP2WNIYH3FDWOMGY76XSZBHNZ","target":"record","payload":{"canonical_record":{"source":{"id":"2405.05767","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-05-09T13:44:04Z","cross_cats_sorted":[],"title_canon_sha256":"d188286be5c254287efdc3e0f0a2c46f938dd2d908e0140392996c0e95e9f6e0","abstract_canon_sha256":"8c765fa9099f250f1e923bba485c75b7c585702eff1d591486e1bbafd4260424"},"schema_version":"1.0"},"canonical_sha256":"125fab35183eca3b3986c7fd7964276e5b44ee10bbecdfc8100be36ca163f98d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:17:22.526129Z","signature_b64":"HjNnQGs1qwQzLQ69NZJDQOAoKOOp7ZMso7rgkWXdpzDMMkY1W7CqYgxvr1mKUhqGTxAt0+dGVDya61uPRxH0Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"125fab35183eca3b3986c7fd7964276e5b44ee10bbecdfc8100be36ca163f98d","last_reissued_at":"2026-07-05T08:17:22.525651Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:17:22.525651Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.05767","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":"2026-07-05T08:17:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C137Ds79vmOHk+vqpeBMmm27Fm96FMsdc5Oel1MnDwgG3Y5O3KI/QQQ8PzvRcFhgtprzs3kBvhNYecqHLpPaCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T01:34:02.912756Z"},"content_sha256":"b3df5aa3ea751a20d7daf4aae2d014507973cb6c6e224f0dcc3855ce7acc012a","schema_version":"1.0","event_id":"sha256:b3df5aa3ea751a20d7daf4aae2d014507973cb6c6e224f0dcc3855ce7acc012a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:CJP2WNIYH3FDWOMGY76XSZBHNZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Large Language Model-Aided Evolutionary Search for Constrained Multiobjective Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Jianyong Chen, Kay Chen Tan, Songbai Liu, Zeyi Wang","submitted_at":"2024-05-09T13:44:04Z","abstract_excerpt":"Evolutionary algorithms excel in solving complex optimization problems, especially those with multiple objectives. However, their stochastic nature can sometimes hinder rapid convergence to the global optima, particularly in scenarios involving constraints. In this study, we employ a large language model (LLM) to enhance evolutionary search for solving constrained multi-objective optimization problems. Our aim is to speed up the convergence of the evolutionary population. To achieve this, we finetune the LLM through tailored prompt engineering, integrating information concerning both objective"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.05767","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/2405.05767/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":"2026-07-05T08:17:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gLvRg4tE1qFFtJM06glf3QDnzclgn9Tad3RhCEcoOMjykYfU1TNyDbdmQP11YWTtCa9GgpvJQxmBn0DV+UzUAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T01:34:02.913281Z"},"content_sha256":"ba849caff7e43de65e9fe5d7cf3d9f682892b7d7fd832ab6bcf54bf30b9bb057","schema_version":"1.0","event_id":"sha256:ba849caff7e43de65e9fe5d7cf3d9f682892b7d7fd832ab6bcf54bf30b9bb057"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CJP2WNIYH3FDWOMGY76XSZBHNZ/bundle.json","state_url":"https://pith.science/pith/CJP2WNIYH3FDWOMGY76XSZBHNZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CJP2WNIYH3FDWOMGY76XSZBHNZ/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":"2026-08-05T01:34:02Z","links":{"resolver":"https://pith.science/pith/CJP2WNIYH3FDWOMGY76XSZBHNZ","bundle":"https://pith.science/pith/CJP2WNIYH3FDWOMGY76XSZBHNZ/bundle.json","state":"https://pith.science/pith/CJP2WNIYH3FDWOMGY76XSZBHNZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CJP2WNIYH3FDWOMGY76XSZBHNZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CJP2WNIYH3FDWOMGY76XSZBHNZ","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":"8c765fa9099f250f1e923bba485c75b7c585702eff1d591486e1bbafd4260424","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-05-09T13:44:04Z","title_canon_sha256":"d188286be5c254287efdc3e0f0a2c46f938dd2d908e0140392996c0e95e9f6e0"},"schema_version":"1.0","source":{"id":"2405.05767","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.05767","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"arxiv_version","alias_value":"2405.05767v1","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.05767","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"pith_short_12","alias_value":"CJP2WNIYH3FD","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"pith_short_16","alias_value":"CJP2WNIYH3FDWOMG","created_at":"2026-07-05T08:17:22Z"},{"alias_kind":"pith_short_8","alias_value":"CJP2WNIY","created_at":"2026-07-05T08:17:22Z"}],"graph_snapshots":[{"event_id":"sha256:ba849caff7e43de65e9fe5d7cf3d9f682892b7d7fd832ab6bcf54bf30b9bb057","target":"graph","created_at":"2026-07-05T08:17:22Z","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/2405.05767/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Evolutionary algorithms excel in solving complex optimization problems, especially those with multiple objectives. However, their stochastic nature can sometimes hinder rapid convergence to the global optima, particularly in scenarios involving constraints. In this study, we employ a large language model (LLM) to enhance evolutionary search for solving constrained multi-objective optimization problems. Our aim is to speed up the convergence of the evolutionary population. To achieve this, we finetune the LLM through tailored prompt engineering, integrating information concerning both objective","authors_text":"Jianyong Chen, Kay Chen Tan, Songbai Liu, Zeyi Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-05-09T13:44:04Z","title":"Large Language Model-Aided Evolutionary Search for Constrained Multiobjective Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.05767","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:b3df5aa3ea751a20d7daf4aae2d014507973cb6c6e224f0dcc3855ce7acc012a","target":"record","created_at":"2026-07-05T08:17:22Z","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":"8c765fa9099f250f1e923bba485c75b7c585702eff1d591486e1bbafd4260424","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2024-05-09T13:44:04Z","title_canon_sha256":"d188286be5c254287efdc3e0f0a2c46f938dd2d908e0140392996c0e95e9f6e0"},"schema_version":"1.0","source":{"id":"2405.05767","kind":"arxiv","version":1}},"canonical_sha256":"125fab35183eca3b3986c7fd7964276e5b44ee10bbecdfc8100be36ca163f98d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"125fab35183eca3b3986c7fd7964276e5b44ee10bbecdfc8100be36ca163f98d","first_computed_at":"2026-07-05T08:17:22.525651Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:17:22.525651Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HjNnQGs1qwQzLQ69NZJDQOAoKOOp7ZMso7rgkWXdpzDMMkY1W7CqYgxvr1mKUhqGTxAt0+dGVDya61uPRxH0Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:17:22.526129Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.05767","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b3df5aa3ea751a20d7daf4aae2d014507973cb6c6e224f0dcc3855ce7acc012a","sha256:ba849caff7e43de65e9fe5d7cf3d9f682892b7d7fd832ab6bcf54bf30b9bb057"],"state_sha256":"ddb285dab35389e9acd8a10a185ff69097d22f7d864f8190f362b80f93029b5e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"45GFT9SoFC+0ICaWrYkzPi+2Ox7U+XfrdozbFdQsltw01dgUWePXsje8soM6KI0ylYad/0DwNCewz1ZvkkRUCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T01:34:02.918304Z","bundle_sha256":"7737c7121fead417a0cebbdfd49ed506b18a74ca0eca3e266c279589149f735b"}}