{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WCOMTJFRTSY4765E2VYAHBVBVA","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":"8993793c891ff4757c24c57f5e987586ed1df27a0fd0af50f8172c11a4b24599","cross_cats_sorted":["cs.SY","eess.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-01-10T18:46:28Z","title_canon_sha256":"d96494d52325f143ea539914d73a87af36a156ca932b7f5b435138633c989802"},"schema_version":"1.0","source":{"id":"2501.06167","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.06167","created_at":"2026-07-05T09:59:34Z"},{"alias_kind":"arxiv_version","alias_value":"2501.06167v1","created_at":"2026-07-05T09:59:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.06167","created_at":"2026-07-05T09:59:34Z"},{"alias_kind":"pith_short_12","alias_value":"WCOMTJFRTSY4","created_at":"2026-07-05T09:59:34Z"},{"alias_kind":"pith_short_16","alias_value":"WCOMTJFRTSY4765E","created_at":"2026-07-05T09:59:34Z"},{"alias_kind":"pith_short_8","alias_value":"WCOMTJFR","created_at":"2026-07-05T09:59:34Z"}],"graph_snapshots":[{"event_id":"sha256:08ed9947f8447f5b3f3fe90a23846d9523ab303bdd42263b63e2c510c174f843","target":"graph","created_at":"2026-07-05T09:59:34Z","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/2501.06167/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a gradient-based meta-learning framework for rapid adaptation of neural state-space models (NSSMs) for black-box system identification. When applicable, we also incorporate domain-specific physical constraints to improve the accuracy of the NSSM. The major benefit of our approach is that instead of relying solely on data from a single target system, our framework utilizes data from a diverse set of source systems, enabling learning from limited target data, as well as with few online training iterations. Through benchmark examples, we demonstrate the potential of our approach, study","authors_text":"Abraham P. Vinod, Ankush Chakrabarty, Christopher R. Laughman, Gordon Wichern, Karl Berntorp, Vedang M. Deshpande","cross_cats":["cs.SY","eess.SY","math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-01-10T18:46:28Z","title":"Meta-Learning for Physically-Constrained Neural System Identification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.06167","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":"sha256:6321ab9d50701d02d39ac21efe6ffa37b86c9b788def971bd4e88a67622ffe57","target":"record","created_at":"2026-07-05T09:59:34Z","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":"8993793c891ff4757c24c57f5e987586ed1df27a0fd0af50f8172c11a4b24599","cross_cats_sorted":["cs.SY","eess.SY","math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-01-10T18:46:28Z","title_canon_sha256":"d96494d52325f143ea539914d73a87af36a156ca932b7f5b435138633c989802"},"schema_version":"1.0","source":{"id":"2501.06167","kind":"arxiv","version":1}},"canonical_sha256":"b09cc9a4b19cb1cffba4d5700386a1a81342d8ea28ed534e70aad38a277e1eb4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b09cc9a4b19cb1cffba4d5700386a1a81342d8ea28ed534e70aad38a277e1eb4","first_computed_at":"2026-07-05T09:59:34.009680Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:59:34.009680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2MDkQPeKHkZZd8rjfQLHZGC/v+XrGykJc8Zh5cfh0Y0gw0Yyk+qh2iXwFAxxydVUHDaclAAi0cpazFEPoRuWCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:59:34.010179Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.06167","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6321ab9d50701d02d39ac21efe6ffa37b86c9b788def971bd4e88a67622ffe57","sha256:08ed9947f8447f5b3f3fe90a23846d9523ab303bdd42263b63e2c510c174f843"],"state_sha256":"269374ff11aba04e5679645941c93136d35c4e9222a6221962a0cd1ba480d56b"}