{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GD4IB22JKAACC3KBNNXTCWNYW5","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":"adba76e1fef35a35f1528105e01d1ef13158b37777287621ab7272422f338677","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T18:44:25Z","title_canon_sha256":"3d22605df4b9c95dabc18defadd568972205876788916512d99e514ce6a07d33"},"schema_version":"1.0","source":{"id":"2501.14012","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.14012","created_at":"2026-07-05T10:57:32Z"},{"alias_kind":"arxiv_version","alias_value":"2501.14012v3","created_at":"2026-07-05T10:57:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.14012","created_at":"2026-07-05T10:57:32Z"},{"alias_kind":"pith_short_12","alias_value":"GD4IB22JKAAC","created_at":"2026-07-05T10:57:32Z"},{"alias_kind":"pith_short_16","alias_value":"GD4IB22JKAACC3KB","created_at":"2026-07-05T10:57:32Z"},{"alias_kind":"pith_short_8","alias_value":"GD4IB22J","created_at":"2026-07-05T10:57:32Z"}],"graph_snapshots":[{"event_id":"sha256:706607936c76d7c53309e718a66285cd6bd0eb488191b5ff46bff8abd3937dcb","target":"graph","created_at":"2026-07-05T10:57:32Z","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/2501.14012/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Surrogate models are frequently employed as efficient substitutes for the costly execution of real-world processes. However, constructing a high-quality surrogate model often demands extensive data acquisition. A solution to this issue is to transfer pre-trained surrogate models for new tasks, provided that certain invariances exist between tasks. This study focuses on transferring non-differentiable surrogate models (e.g., random forests) from a source function to a target function, where we assume their domains are related by an unknown affine transformation, using only a limited amount of t","authors_text":"Diederick Vermetten, Hao Wang, Manuel L\\'opez-Ib\\'a\\~nez, Shuaiqun Pan, Thomas B\\\"ack","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T18:44:25Z","title":"Transfer Learning of Surrogate Models via Domain Affine Transformation Across Synthetic and Real-World Benchmarks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.14012","kind":"arxiv","version":3},"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":"sha256:372cc2679c1ad9539df5fdfe475c6e7d7ac0fb826e93c9ab8debe5c820a85f2b","target":"record","created_at":"2026-07-05T10:57:32Z","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":"adba76e1fef35a35f1528105e01d1ef13158b37777287621ab7272422f338677","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-23T18:44:25Z","title_canon_sha256":"3d22605df4b9c95dabc18defadd568972205876788916512d99e514ce6a07d33"},"schema_version":"1.0","source":{"id":"2501.14012","kind":"arxiv","version":3}},"canonical_sha256":"30f880eb495000216d416b6f3159b8b7556bccaf07469fa2c3fe2f38b3a00351","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30f880eb495000216d416b6f3159b8b7556bccaf07469fa2c3fe2f38b3a00351","first_computed_at":"2026-07-05T10:57:32.991420Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:57:32.991420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"d5BgpGjGjt2o89YKMAtRe2/ru2glN0uV6LZLFPEDk5J7FlwyEQIVaxN7xnL1Yq1qP7yTwzxwQvW/3pK3u4tuBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:57:32.991908Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.14012","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:372cc2679c1ad9539df5fdfe475c6e7d7ac0fb826e93c9ab8debe5c820a85f2b","sha256:706607936c76d7c53309e718a66285cd6bd0eb488191b5ff46bff8abd3937dcb"],"state_sha256":"fec6a61d6347ee154293e338da0cf632a677c1cf1f9be8911874ff6a25bf3472"}