{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:5FYHVG3EFNG2LGLPMO5XTPUVFS","short_pith_number":"pith:5FYHVG3E","schema_version":"1.0","canonical_sha256":"e9707a9b642b4da5996f63bb79be952ca0f7685d05db1c766db0436b65055d7e","source":{"kind":"arxiv","id":"2506.04528","version":1},"attestation_state":"computed","paper":{"title":"Hierarchical Implicit Neural Emulators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Karan Jakhar, Michael Maire, Pedram Hassanzadeh, Peter Y. Lu, Rebecca Willett, Ruoxi Jiang, Xiao Zhang","submitted_at":"2025-06-05T00:28:26Z","abstract_excerpt":"Neural PDE solvers offer a powerful tool for modeling complex dynamical systems, but often struggle with error accumulation over long time horizons and maintaining stability and physical consistency. We introduce a multiscale implicit neural emulator that enhances long-term prediction accuracy by conditioning on a hierarchy of lower-dimensional future state representations. Drawing inspiration from the stability properties of numerical implicit time-stepping methods, our approach leverages predictions several steps ahead in time at increasing compression rates for next-timestep refinements. By"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.04528","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-05T00:28:26Z","cross_cats_sorted":[],"title_canon_sha256":"2c5bc03dea2856bec9eee736f5a6c1c6fe6a8fb95d9854a84de620a135117213","abstract_canon_sha256":"6498f46c12a01dfcdd3979222daf03fe2759433098b4088cd72af5eaaf380684"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:16:15.987634Z","signature_b64":"2dyCYZpzxKP2kzauysI+OPYjYoLXBPu3q+8+sZ31HzWhIiPrYyQ3gzt7e41yRbEpAI5WEM3igpt0HvJ242foCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e9707a9b642b4da5996f63bb79be952ca0f7685d05db1c766db0436b65055d7e","last_reissued_at":"2026-07-05T11:16:15.987106Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:16:15.987106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Hierarchical Implicit Neural Emulators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Karan Jakhar, Michael Maire, Pedram Hassanzadeh, Peter Y. Lu, Rebecca Willett, Ruoxi Jiang, Xiao Zhang","submitted_at":"2025-06-05T00:28:26Z","abstract_excerpt":"Neural PDE solvers offer a powerful tool for modeling complex dynamical systems, but often struggle with error accumulation over long time horizons and maintaining stability and physical consistency. We introduce a multiscale implicit neural emulator that enhances long-term prediction accuracy by conditioning on a hierarchy of lower-dimensional future state representations. Drawing inspiration from the stability properties of numerical implicit time-stepping methods, our approach leverages predictions several steps ahead in time at increasing compression rates for next-timestep refinements. By"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.04528","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2506.04528/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.04528","created_at":"2026-07-05T11:16:15.987168+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.04528v1","created_at":"2026-07-05T11:16:15.987168+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.04528","created_at":"2026-07-05T11:16:15.987168+00:00"},{"alias_kind":"pith_short_12","alias_value":"5FYHVG3EFNG2","created_at":"2026-07-05T11:16:15.987168+00:00"},{"alias_kind":"pith_short_16","alias_value":"5FYHVG3EFNG2LGLP","created_at":"2026-07-05T11:16:15.987168+00:00"},{"alias_kind":"pith_short_8","alias_value":"5FYHVG3E","created_at":"2026-07-05T11:16:15.987168+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS","json":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS.json","graph_json":"https://pith.science/api/pith-number/5FYHVG3EFNG2LGLPMO5XTPUVFS/graph.json","events_json":"https://pith.science/api/pith-number/5FYHVG3EFNG2LGLPMO5XTPUVFS/events.json","paper":"https://pith.science/paper/5FYHVG3E"},"agent_actions":{"view_html":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS","download_json":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS.json","view_paper":"https://pith.science/paper/5FYHVG3E","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.04528&json=true","fetch_graph":"https://pith.science/api/pith-number/5FYHVG3EFNG2LGLPMO5XTPUVFS/graph.json","fetch_events":"https://pith.science/api/pith-number/5FYHVG3EFNG2LGLPMO5XTPUVFS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS/action/storage_attestation","attest_author":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS/action/author_attestation","sign_citation":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS/action/citation_signature","submit_replication":"https://pith.science/pith/5FYHVG3EFNG2LGLPMO5XTPUVFS/action/replication_record"}},"created_at":"2026-07-05T11:16:15.987168+00:00","updated_at":"2026-07-05T11:16:15.987168+00:00"}