{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MTFDHMLRBZUVPRV7Y5XOQVAXFZ","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":"fc6e0176dced73129ea710c482fa574a2ad72909c6b79a6fa26d06a897a33cb5","cross_cats_sorted":["cs.AI","cs.SC"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-05T06:26:49Z","title_canon_sha256":"6a5ea952341632ab847316104febcd42bc82962006e78948826238e4b8fc989d"},"schema_version":"1.0","source":{"id":"2502.02917","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02917","created_at":"2026-07-05T10:12:26Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02917v2","created_at":"2026-07-05T10:12:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02917","created_at":"2026-07-05T10:12:26Z"},{"alias_kind":"pith_short_12","alias_value":"MTFDHMLRBZUV","created_at":"2026-07-05T10:12:26Z"},{"alias_kind":"pith_short_16","alias_value":"MTFDHMLRBZUVPRV7","created_at":"2026-07-05T10:12:26Z"},{"alias_kind":"pith_short_8","alias_value":"MTFDHMLR","created_at":"2026-07-05T10:12:26Z"}],"graph_snapshots":[{"event_id":"sha256:91294521a780bd03b0fac64acf52f31e01eec43644a1255d914fa1f0fe1e18cf","target":"graph","created_at":"2026-07-05T10:12:26Z","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/2502.02917/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Symbolic Regression (SR) holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for both online search methods and pre-trained transformer models. Additionally, current state-of-the-art approaches typically do not consider the integration of domain experts' prior knowledge and do not support iterative interactions with the model during the equation discovery process. To address these challenges, we propose the Symbolic Q-network (Sym-Q), an advanced in","authors_text":"David Kammer, Hao Dong, Michele Viscione, Olga Fink, Wenqi Zhou, Yuan Tian","cross_cats":["cs.AI","cs.SC"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-05T06:26:49Z","title":"Interactive Symbolic Regression through Offline Reinforcement Learning: A Co-Design Framework"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02917","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":"sha256:2047f6773c667a822ddaf98e1ee3b0490ace20b186c079b7c7f540511715f834","target":"record","created_at":"2026-07-05T10:12:26Z","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":"fc6e0176dced73129ea710c482fa574a2ad72909c6b79a6fa26d06a897a33cb5","cross_cats_sorted":["cs.AI","cs.SC"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-05T06:26:49Z","title_canon_sha256":"6a5ea952341632ab847316104febcd42bc82962006e78948826238e4b8fc989d"},"schema_version":"1.0","source":{"id":"2502.02917","kind":"arxiv","version":2}},"canonical_sha256":"64ca33b1710e6957c6bfc76ee854172e44ca49151e12f52d38ffb3a2ed573c49","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"64ca33b1710e6957c6bfc76ee854172e44ca49151e12f52d38ffb3a2ed573c49","first_computed_at":"2026-07-05T10:12:26.465503Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:12:26.465503Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dN39UmvEL7wp7VsbUoPjWLI94LVQ2T+TVAliAr8c041c2JrR+toQ2ZgXL32NxihRrsCCVZyea95HkzU2UaujBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:12:26.466013Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.02917","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2047f6773c667a822ddaf98e1ee3b0490ace20b186c079b7c7f540511715f834","sha256:91294521a780bd03b0fac64acf52f31e01eec43644a1255d914fa1f0fe1e18cf"],"state_sha256":"dfb2dc781a4a41c4422b45132d4eacdfb9f802de9971b0cc83a6100e94260b3c"}