{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:MFK6II73ODMSWY5P6SBBXMKXNZ","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":"33561225dac6c21d41eaf15c51d035f5121ca5bd268a2747efff9b46f89996ac","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-06T14:41:11Z","title_canon_sha256":"2fbec475e5407a52e48196392351ceadf43abf0166b1abe10d7d2d6e8a64ce23"},"schema_version":"1.0","source":{"id":"2608.06107","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.06107","created_at":"2026-08-07T01:40:33Z"},{"alias_kind":"arxiv_version","alias_value":"2608.06107v1","created_at":"2026-08-07T01:40:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.06107","created_at":"2026-08-07T01:40:33Z"},{"alias_kind":"pith_short_12","alias_value":"MFK6II73ODMS","created_at":"2026-08-07T01:40:33Z"},{"alias_kind":"pith_short_16","alias_value":"MFK6II73ODMSWY5P","created_at":"2026-08-07T01:40:33Z"},{"alias_kind":"pith_short_8","alias_value":"MFK6II73","created_at":"2026-08-07T01:40:33Z"}],"graph_snapshots":[{"event_id":"sha256:4ddacf0a67e26666879bc720092e01a3945013b95bd0212823897e72553ba540","target":"graph","created_at":"2026-08-07T01:40:33Z","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/2608.06107/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning offers a promising avenue to accelerate physical simulations by replacing computationally expensive traditional Partial Differential Equation (PDE) solvers with fast, differentiable surrogate models. However, standard auto-regressive ML emulators often suffer from error accumulation over long horizons and struggle to capture the stochasticity of complex physical systems. In this paper, we propose Kastor, a comprehensive methodology to adapt a deterministic physics foundation model into a highly efficient and accurate generative surrogate. First, we introduce a two-stage infere","authors_text":"Alexis Jacq, Guillaume Couairon, Quentin Berthet, Renu Singh, Romuald Elie, Yana Hasson, Yu-Han Wu","cross_cats":["cs.NA","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-06T14:41:11Z","title":"Kastor: An efficient fine-tuning strategy for generative emulation of PDE simulations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.06107","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:a4e8e34f37ec315d1b6871162b9b42876730705aeddf51233461cf3233c77375","target":"record","created_at":"2026-08-07T01:40:33Z","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":"33561225dac6c21d41eaf15c51d035f5121ca5bd268a2747efff9b46f89996ac","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-08-06T14:41:11Z","title_canon_sha256":"2fbec475e5407a52e48196392351ceadf43abf0166b1abe10d7d2d6e8a64ce23"},"schema_version":"1.0","source":{"id":"2608.06107","kind":"arxiv","version":1}},"canonical_sha256":"6155e423fb70d92b63aff4821bb1576e4ed5d47593f0cf09978972862f342d12","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6155e423fb70d92b63aff4821bb1576e4ed5d47593f0cf09978972862f342d12","first_computed_at":"2026-08-07T01:40:33.020085Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-07T01:40:33.020085Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"B67ZEsO3zsEzOlL9H6jR4YvoUaRRwkNtf2JkjHiCVz54ET0MapJ1S4jhxLXKtO7XGrZkSDUrAmVpZBvSLN2EBw==","signature_status":"signed_v1","signed_at":"2026-08-07T01:40:33.021732Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.06107","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a4e8e34f37ec315d1b6871162b9b42876730705aeddf51233461cf3233c77375","sha256:4ddacf0a67e26666879bc720092e01a3945013b95bd0212823897e72553ba540"],"state_sha256":"a632e976fe806b4b4c2de0dff4a1c29eead6a665a41082e4f9644ddc8aa2f350"}