{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WOG5BHIWRFVWO5NFSGFGCYTZH6","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":"00ec4abcb61de15d772837c2bfee35d5b2813699d04152e80470cde5b5c5c4b6","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-02-23T09:06:42Z","title_canon_sha256":"c72b1052118313a338c7e33f22e37e8652669fddaf7dc8bef494321828ff3dc8"},"schema_version":"1.0","source":{"id":"2302.11864","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.11864","created_at":"2026-07-05T05:48:52Z"},{"alias_kind":"arxiv_version","alias_value":"2302.11864v2","created_at":"2026-07-05T05:48:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.11864","created_at":"2026-07-05T05:48:52Z"},{"alias_kind":"pith_short_12","alias_value":"WOG5BHIWRFVW","created_at":"2026-07-05T05:48:52Z"},{"alias_kind":"pith_short_16","alias_value":"WOG5BHIWRFVWO5NF","created_at":"2026-07-05T05:48:52Z"},{"alias_kind":"pith_short_8","alias_value":"WOG5BHIW","created_at":"2026-07-05T05:48:52Z"}],"graph_snapshots":[{"event_id":"sha256:7f2f7461a01c1614ba9245e2c054d11756dd721235976a54a3d197030ca3f397","target":"graph","created_at":"2026-07-05T05:48:52Z","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/2302.11864/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Physical simulations that accurately model reality are crucial for many engineering disciplines such as mechanical engineering and robotic motion planning. In recent years, learned Graph Network Simulators produced accurate mesh-based simulations while requiring only a fraction of the computational cost of traditional simulators. Yet, the resulting predictors are confined to learning from data generated by existing mesh-based simulators and thus cannot include real world sensory information such as point cloud data. As these predictors have to simulate complex physical systems from only an ini","authors_text":"Franziska Mathis-Ullrich, Gerhard Neumann, Jonas Linkerh\\\"agner, Niklas Freymuth, Paul Maria Scheikl","cross_cats":["cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-02-23T09:06:42Z","title":"Grounding Graph Network Simulators using Physical Sensor Observations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.11864","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":"sha256:5f1cee06f8815b6789ace168978f3c1ef8e329f5c76b09566807f6e71a61e22e","target":"record","created_at":"2026-07-05T05:48:52Z","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":"00ec4abcb61de15d772837c2bfee35d5b2813699d04152e80470cde5b5c5c4b6","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-02-23T09:06:42Z","title_canon_sha256":"c72b1052118313a338c7e33f22e37e8652669fddaf7dc8bef494321828ff3dc8"},"schema_version":"1.0","source":{"id":"2302.11864","kind":"arxiv","version":2}},"canonical_sha256":"b38dd09d16896b6775a5918a6162793fac43e2c0be996f804a3216942a6827f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b38dd09d16896b6775a5918a6162793fac43e2c0be996f804a3216942a6827f9","first_computed_at":"2026-07-05T05:48:52.811984Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:48:52.811984Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4eoQAYkByqBtbwGyXot2ORIx6yucbXXj/JrcueqF0HMTNSVueOZgcKJ443tFAbkJ52zruJ+Huv+EHQvMxOJHAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:48:52.812441Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.11864","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f1cee06f8815b6789ace168978f3c1ef8e329f5c76b09566807f6e71a61e22e","sha256:7f2f7461a01c1614ba9245e2c054d11756dd721235976a54a3d197030ca3f397"],"state_sha256":"9082ae5b991ccf46758c4543e35f9d5504b3454e79699d93a6ff1678c4471eed"}