{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:MYUIJTG4B7IBO5G7AWXB5K7CPO","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":"7833ede0ee5f8eb5ea606eab649683364ced403ecd4f8fa19df2f06acdf2d9be","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-05-28T12:30:50Z","title_canon_sha256":"0d9a6252d435def200de6661dc83d63fddc600ef4960185c143009506e1d7116"},"schema_version":"1.0","source":{"id":"2605.29849","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.29849","created_at":"2026-05-29T02:05:55Z"},{"alias_kind":"arxiv_version","alias_value":"2605.29849v1","created_at":"2026-05-29T02:05:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29849","created_at":"2026-05-29T02:05:55Z"},{"alias_kind":"pith_short_12","alias_value":"MYUIJTG4B7IB","created_at":"2026-05-29T02:05:55Z"},{"alias_kind":"pith_short_16","alias_value":"MYUIJTG4B7IBO5G7","created_at":"2026-05-29T02:05:55Z"},{"alias_kind":"pith_short_8","alias_value":"MYUIJTG4","created_at":"2026-05-29T02:05:55Z"}],"graph_snapshots":[{"event_id":"sha256:ed21601b8c0492edbf6b77d44c78161a963642ef6b7c1b83d2e3d60cc2aca5c6","target":"graph","created_at":"2026-05-29T02:05:55Z","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/2605.29849/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning (ML) is increasingly used for data-driven modeling of buildings to enable downstream tasks such as fault detection and diagnosis, and energy-efficient control. While recent work improves generalization across building characteristics, weather, and occupancy, generalization also depends on sufficient exploration of the control-driven system state space. Existing real-world datasets and simulation environments predominantly reflect stationary operation under fixed control policies, resulting in limited excitation and reduced robustness to unseen operating conditions.\n  This pape","authors_text":"Benjamin Sch\\\"afer, Benjamin Tischler, Fabian Raisch, Felix Koch, Thomas Krug","cross_cats":["cs.LG","cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-05-28T12:30:50Z","title":"BuilDyn: Excitation-Driven Data Generation for Building Thermal Dynamics Modeling and Control"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29849","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":"sha256:92d0ce50750d77adabbb0c1c6505ecc573def2bf837f7326ea888102de404e4e","target":"record","created_at":"2026-05-29T02:05:55Z","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":"7833ede0ee5f8eb5ea606eab649683364ced403ecd4f8fa19df2f06acdf2d9be","cross_cats_sorted":["cs.LG","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-05-28T12:30:50Z","title_canon_sha256":"0d9a6252d435def200de6661dc83d63fddc600ef4960185c143009506e1d7116"},"schema_version":"1.0","source":{"id":"2605.29849","kind":"arxiv","version":1}},"canonical_sha256":"662884ccdc0fd01774df05ae1eabe27b81912b6e89ecc46715dc7b8328441a75","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"662884ccdc0fd01774df05ae1eabe27b81912b6e89ecc46715dc7b8328441a75","first_computed_at":"2026-05-29T02:05:55.949282Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T02:05:55.949282Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KmrYH2dO5L9zEwAS7AVmwIWS0glGHBgmykORPUE/XvBj4ZiBsuUc+6AedqUkJke1X+P5T/cabdd3h2beNoadDA==","signature_status":"signed_v1","signed_at":"2026-05-29T02:05:55.950123Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.29849","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:92d0ce50750d77adabbb0c1c6505ecc573def2bf837f7326ea888102de404e4e","sha256:ed21601b8c0492edbf6b77d44c78161a963642ef6b7c1b83d2e3d60cc2aca5c6"],"state_sha256":"8db5c8f5c65ee00b21d6149f4ac64b9bce75959db88f29ad31fab60bdbe106c4"}