{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:KUIUOL7FKTKG2RLIYKIQIYNMTT","short_pith_number":"pith:KUIUOL7F","schema_version":"1.0","canonical_sha256":"5511472fe554d46d4568c2910461ac9ccc732a824e71dea1d6d62f221d62f72c","source":{"kind":"arxiv","id":"2606.10237","version":1},"attestation_state":"computed","paper":{"title":"Minimalist Genetic Programming","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Leonardo Trujillo","submitted_at":"2026-06-08T22:51:58Z","abstract_excerpt":"Genetic programming (GP) is based on two important insights. First, that any learning task can fundamentally be posed as a program induction problem, where the goal is to construct a symbolic hierarchical model that is expressed as a syntax tree. Second, to pose this task as a search problem, and use evolution to locate the desired model. Since it was proposed, GP has produced notable results in a wide range of tasks and problem domains. This work presents an alternative view by modifying the second core insight of GP, posing the problem as a syntactic derivation task instead. In particular, t"},"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":"2606.10237","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T22:51:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"043cb6aab09758d7f999906bcedee32303d012f80f6328da1a8edff357ed60f3","abstract_canon_sha256":"342f5224ab51d204530aa15648d4de45798d5db5e22bb3641aaa8e5b1f5632c1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T01:09:01.664805Z","signature_b64":"MU8ZVcDmRuBwGVDhUEimMErRTXe0SuCh3wScYHzag5i+Wbk28+6BSfzKhPTS9caC1P0doRtKHyp3iy23NgKcAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5511472fe554d46d4568c2910461ac9ccc732a824e71dea1d6d62f221d62f72c","last_reissued_at":"2026-06-10T01:09:01.664244Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T01:09:01.664244Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Minimalist Genetic Programming","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Leonardo Trujillo","submitted_at":"2026-06-08T22:51:58Z","abstract_excerpt":"Genetic programming (GP) is based on two important insights. First, that any learning task can fundamentally be posed as a program induction problem, where the goal is to construct a symbolic hierarchical model that is expressed as a syntax tree. Second, to pose this task as a search problem, and use evolution to locate the desired model. Since it was proposed, GP has produced notable results in a wide range of tasks and problem domains. This work presents an alternative view by modifying the second core insight of GP, posing the problem as a syntactic derivation task instead. In particular, t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10237","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/2606.10237/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":"2606.10237","created_at":"2026-06-10T01:09:01.664345+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.10237v1","created_at":"2026-06-10T01:09:01.664345+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10237","created_at":"2026-06-10T01:09:01.664345+00:00"},{"alias_kind":"pith_short_12","alias_value":"KUIUOL7FKTKG","created_at":"2026-06-10T01:09:01.664345+00:00"},{"alias_kind":"pith_short_16","alias_value":"KUIUOL7FKTKG2RLI","created_at":"2026-06-10T01:09:01.664345+00:00"},{"alias_kind":"pith_short_8","alias_value":"KUIUOL7F","created_at":"2026-06-10T01:09:01.664345+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/KUIUOL7FKTKG2RLIYKIQIYNMTT","json":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT.json","graph_json":"https://pith.science/api/pith-number/KUIUOL7FKTKG2RLIYKIQIYNMTT/graph.json","events_json":"https://pith.science/api/pith-number/KUIUOL7FKTKG2RLIYKIQIYNMTT/events.json","paper":"https://pith.science/paper/KUIUOL7F"},"agent_actions":{"view_html":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT","download_json":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT.json","view_paper":"https://pith.science/paper/KUIUOL7F","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.10237&json=true","fetch_graph":"https://pith.science/api/pith-number/KUIUOL7FKTKG2RLIYKIQIYNMTT/graph.json","fetch_events":"https://pith.science/api/pith-number/KUIUOL7FKTKG2RLIYKIQIYNMTT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT/action/storage_attestation","attest_author":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT/action/author_attestation","sign_citation":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT/action/citation_signature","submit_replication":"https://pith.science/pith/KUIUOL7FKTKG2RLIYKIQIYNMTT/action/replication_record"}},"created_at":"2026-06-10T01:09:01.664345+00:00","updated_at":"2026-06-10T01:09:01.664345+00:00"}