{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:KHDOHGZHPOIUMCCUVMFCFTPK4E","short_pith_number":"pith:KHDOHGZH","schema_version":"1.0","canonical_sha256":"51c6e39b277b91460854ab0a22cdeae11e2e05ecd7d57355451bfdd3b111ba79","source":{"kind":"arxiv","id":"2608.09629","version":1},"attestation_state":"computed","paper":{"title":"Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Fan Yang, Hui Xue","submitted_at":"2026-08-10T14:10:25Z","abstract_excerpt":"Self-evolving agents are usually built around prescribed optimization pipelines: the framework decides how to gather evidence, revise a persistent artifact, select candidates, and stop. We ask whether this task-specific procedure remains necessary when a frontier model acts as the optimizer. We introduce Open-Ended Optimization (OEO), which keeps the objective, permitted interactions, resource budget, data boundary, and evaluation fixed while allowing the optimizer to compose the improvement process online. We compare OEO with two complementary prescribed approaches: SkillOpt, a staged pipelin"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2608.09629","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-10T14:10:25Z","cross_cats_sorted":[],"title_canon_sha256":"4d3bfb6aad6c354f31b37709cacc435b0a3e1e2a42ecad08e88b41a4a2598aa0","abstract_canon_sha256":"a1b15f20e49254b19a3c265bc2570c2b9df78e2a60994211d3494f520ed9ba0d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-11T02:24:42.140109Z","signature_b64":"9636WHAUHd0Fl0kOXCpOLDlfPHitVnagVofeOmXx3MUGL5vvRagB6EGJn1hjleFwt2NNmIwy91iekOFj2RvcDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"51c6e39b277b91460854ab0a22cdeae11e2e05ecd7d57355451bfdd3b111ba79","last_reissued_at":"2026-08-11T02:24:42.138563Z","signature_status":"signed_v1","first_computed_at":"2026-08-11T02:24:42.138563Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Rethinking Self-Evolving Agents: Do We Still Need Prescribed Optimization Pipelines?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Fan Yang, Hui Xue","submitted_at":"2026-08-10T14:10:25Z","abstract_excerpt":"Self-evolving agents are usually built around prescribed optimization pipelines: the framework decides how to gather evidence, revise a persistent artifact, select candidates, and stop. We ask whether this task-specific procedure remains necessary when a frontier model acts as the optimizer. We introduce Open-Ended Optimization (OEO), which keeps the objective, permitted interactions, resource budget, data boundary, and evaluation fixed while allowing the optimizer to compose the improvement process online. We compare OEO with two complementary prescribed approaches: SkillOpt, a staged pipelin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.09629","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/2608.09629/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2608.09629","created_at":"2026-08-11T02:24:42.139136+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.09629v1","created_at":"2026-08-11T02:24:42.139136+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.09629","created_at":"2026-08-11T02:24:42.139136+00:00"},{"alias_kind":"pith_short_12","alias_value":"KHDOHGZHPOIU","created_at":"2026-08-11T02:24:42.139136+00:00"},{"alias_kind":"pith_short_16","alias_value":"KHDOHGZHPOIUMCCU","created_at":"2026-08-11T02:24:42.139136+00:00"},{"alias_kind":"pith_short_8","alias_value":"KHDOHGZH","created_at":"2026-08-11T02:24:42.139136+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E","json":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E.json","graph_json":"https://pith.science/api/pith-number/KHDOHGZHPOIUMCCUVMFCFTPK4E/graph.json","events_json":"https://pith.science/api/pith-number/KHDOHGZHPOIUMCCUVMFCFTPK4E/events.json","paper":"https://pith.science/paper/KHDOHGZH"},"agent_actions":{"view_html":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E","download_json":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E.json","view_paper":"https://pith.science/paper/KHDOHGZH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.09629&json=true","fetch_graph":"https://pith.science/api/pith-number/KHDOHGZHPOIUMCCUVMFCFTPK4E/graph.json","fetch_events":"https://pith.science/api/pith-number/KHDOHGZHPOIUMCCUVMFCFTPK4E/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E/action/storage_attestation","attest_author":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E/action/author_attestation","sign_citation":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E/action/citation_signature","submit_replication":"https://pith.science/pith/KHDOHGZHPOIUMCCUVMFCFTPK4E/action/replication_record"}},"created_at":"2026-08-11T02:24:42.139136+00:00","updated_at":"2026-08-11T02:24:42.139136+00:00"}