{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:J2HI5HZPVNDSO2U3ZBN43YNLG5","short_pith_number":"pith:J2HI5HZP","schema_version":"1.0","canonical_sha256":"4e8e8e9f2fab47276a9bc85bcde1ab375af289a2c157674a8b626a02eef20055","source":{"kind":"arxiv","id":"2202.00199","version":2},"attestation_state":"computed","paper":{"title":"RFUniverse: A Multiphysics Simulation Platform for Embodied AI","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cewu Lu, Han Xue, Haoyuan Fu, Jieyi Zhang, Ruolin Ye, Tutian Tang, Wenqiang Xu, Wenxin Du, Yutong Li, Zhenjun Yu","submitted_at":"2022-02-01T03:35:13Z","abstract_excerpt":"Multiphysics phenomena, the coupling effects involving different aspects of physics laws, are pervasive in the real world and can often be encountered when performing everyday household tasks. Intelligent agents which seek to assist or replace human laborers will need to learn to cope with such phenomena in household task settings. To equip the agents with such kind of abilities, the research community needs a simulation environment, which will have the capability to serve as the testbed for the training process of these intelligent agents, to have the ability to support multiphysics coupling "},"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":"2202.00199","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2022-02-01T03:35:13Z","cross_cats_sorted":[],"title_canon_sha256":"9382bf2dcf50e4c140b26f0c02addc1322230df39d5b0889279a4dc9b0c16d62","abstract_canon_sha256":"ab66d3bc7829f18cb513c98b983998a36c7d105117e33a5ad6b4a8add290756d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:09:42.095343Z","signature_b64":"YsY+yUsMYACtAGP5AtGXyCX+j5UV7qmz+hag/AJonzP3X4jLRtsMlDNd2klRRv7tum9kuOckPOKKuSPWhIqiAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e8e8e9f2fab47276a9bc85bcde1ab375af289a2c157674a8b626a02eef20055","last_reissued_at":"2026-07-05T06:09:42.094837Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:09:42.094837Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RFUniverse: A Multiphysics Simulation Platform for Embodied AI","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cewu Lu, Han Xue, Haoyuan Fu, Jieyi Zhang, Ruolin Ye, Tutian Tang, Wenqiang Xu, Wenxin Du, Yutong Li, Zhenjun Yu","submitted_at":"2022-02-01T03:35:13Z","abstract_excerpt":"Multiphysics phenomena, the coupling effects involving different aspects of physics laws, are pervasive in the real world and can often be encountered when performing everyday household tasks. Intelligent agents which seek to assist or replace human laborers will need to learn to cope with such phenomena in household task settings. To equip the agents with such kind of abilities, the research community needs a simulation environment, which will have the capability to serve as the testbed for the training process of these intelligent agents, to have the ability to support multiphysics coupling "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.00199","kind":"arxiv","version":2},"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/2202.00199/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":"2202.00199","created_at":"2026-07-05T06:09:42.094896+00:00"},{"alias_kind":"arxiv_version","alias_value":"2202.00199v2","created_at":"2026-07-05T06:09:42.094896+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.00199","created_at":"2026-07-05T06:09:42.094896+00:00"},{"alias_kind":"pith_short_12","alias_value":"J2HI5HZPVNDS","created_at":"2026-07-05T06:09:42.094896+00:00"},{"alias_kind":"pith_short_16","alias_value":"J2HI5HZPVNDSO2U3","created_at":"2026-07-05T06:09:42.094896+00:00"},{"alias_kind":"pith_short_8","alias_value":"J2HI5HZP","created_at":"2026-07-05T06:09:42.094896+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.10366","citing_title":"A Practical Recipe Towards Improving Sim-and-Real Correlation for VLA Evaluation","ref_index":29,"is_internal_anchor":false},{"citing_arxiv_id":"2403.09227","citing_title":"BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation","ref_index":56,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5","json":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5.json","graph_json":"https://pith.science/api/pith-number/J2HI5HZPVNDSO2U3ZBN43YNLG5/graph.json","events_json":"https://pith.science/api/pith-number/J2HI5HZPVNDSO2U3ZBN43YNLG5/events.json","paper":"https://pith.science/paper/J2HI5HZP"},"agent_actions":{"view_html":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5","download_json":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5.json","view_paper":"https://pith.science/paper/J2HI5HZP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2202.00199&json=true","fetch_graph":"https://pith.science/api/pith-number/J2HI5HZPVNDSO2U3ZBN43YNLG5/graph.json","fetch_events":"https://pith.science/api/pith-number/J2HI5HZPVNDSO2U3ZBN43YNLG5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5/action/storage_attestation","attest_author":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5/action/author_attestation","sign_citation":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5/action/citation_signature","submit_replication":"https://pith.science/pith/J2HI5HZPVNDSO2U3ZBN43YNLG5/action/replication_record"}},"created_at":"2026-07-05T06:09:42.094896+00:00","updated_at":"2026-07-05T06:09:42.094896+00:00"}