{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EEPKMONAHIPNQQXWKJMHK4IR24","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":"74a22810070d03ff415d6376340ff640b7dfeed46b5f114253c5877cba22acf9","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-04-23T08:29:53Z","title_canon_sha256":"7df40c94453d68d299c315914535cbb8c0f5509de8d47ee7eaae0f240eb2a6f9"},"schema_version":"1.0","source":{"id":"2504.16503","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.16503","created_at":"2026-07-05T10:53:00Z"},{"alias_kind":"arxiv_version","alias_value":"2504.16503v1","created_at":"2026-07-05T10:53:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16503","created_at":"2026-07-05T10:53:00Z"},{"alias_kind":"pith_short_12","alias_value":"EEPKMONAHIPN","created_at":"2026-07-05T10:53:00Z"},{"alias_kind":"pith_short_16","alias_value":"EEPKMONAHIPNQQXW","created_at":"2026-07-05T10:53:00Z"},{"alias_kind":"pith_short_8","alias_value":"EEPKMONA","created_at":"2026-07-05T10:53:00Z"}],"graph_snapshots":[{"event_id":"sha256:f4837a876fcb03e25cf917b3cf414d5b8a66790eb450752db6e3cf1c80c1c6da","target":"graph","created_at":"2026-07-05T10:53:00Z","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/2504.16503/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Symbolic regression is a technique that can automatically derive analytic models from data. Traditionally, symbolic regression has been implemented primarily through genetic programming that evolves populations of candidate solutions sampled by genetic operators, crossover and mutation. More recently, neural networks have been employed to learn the entire analytical model, i.e., its structure and coefficients, using regularized gradient-based optimization. Although this approach tunes the model's coefficients better, it is prone to premature convergence to suboptimal model structures. Here, we","authors_text":"Ji\\v{r}\\'i Kubal\\'ik, Robert Babu\\v{s}ka","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-04-23T08:29:53Z","title":"Neuro-Evolutionary Approach to Physics-Aware Symbolic Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16503","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":"sha256:5a2c28b88b9d03e7122de90047678f9ad9ef51794020fc99924aef603a71b807","target":"record","created_at":"2026-07-05T10:53:00Z","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":"74a22810070d03ff415d6376340ff640b7dfeed46b5f114253c5877cba22acf9","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-04-23T08:29:53Z","title_canon_sha256":"7df40c94453d68d299c315914535cbb8c0f5509de8d47ee7eaae0f240eb2a6f9"},"schema_version":"1.0","source":{"id":"2504.16503","kind":"arxiv","version":1}},"canonical_sha256":"211ea639a03a1ed842f65258757111d72f47f51c653028b226f4d2b53bef9a8b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"211ea639a03a1ed842f65258757111d72f47f51c653028b226f4d2b53bef9a8b","first_computed_at":"2026-07-05T10:53:00.781654Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:53:00.781654Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6zozR+QBIyMMAqWHW619wcgg48qBc6SfXBiEQxjF+mCyRVaQObx7n46opjKgzCTqCjKmzUD6n2alYC6kX1b7Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:53:00.782142Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.16503","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a2c28b88b9d03e7122de90047678f9ad9ef51794020fc99924aef603a71b807","sha256:f4837a876fcb03e25cf917b3cf414d5b8a66790eb450752db6e3cf1c80c1c6da"],"state_sha256":"f3fb0f1c9b40d9766225d6cc74f6592eeb7523b56e2aeb0f33b2a132a04c1ad4"}