{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:DGELFTRQ3NHJBKPFK7Q44JWHFS","short_pith_number":"pith:DGELFTRQ","schema_version":"1.0","canonical_sha256":"1988b2ce30db4e90a9e557e1ce26c72c89d6f04de544da7b61bb0990c54f3247","source":{"kind":"arxiv","id":"2309.05622","version":1},"attestation_state":"computed","paper":{"title":"Task-Oriented Cross-System Design for Timely and Accurate Modeling in the Metaverse","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Branka Vucetic, Changyang She, Guodong Zhao, Kan Chen, Muhammad Ali Imran, Yufeng Diao, Zhen Meng","submitted_at":"2023-09-11T17:11:32Z","abstract_excerpt":"In this paper, we establish a task-oriented cross-system design framework to minimize the required packet rate for timely and accurate modeling of a real-world robotic arm in the Metaverse, where sensing, communication, prediction, control, and rendering are considered. To optimize a scheduling policy and prediction horizons, we design a Constraint Proximal Policy Optimization(C-PPO) algorithm by integrating domain knowledge from relevant systems into the advanced reinforcement learning algorithm, Proximal Policy Optimization(PPO). Specifically, the Jacobian matrix for analyzing the motion of "},"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":"2309.05622","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-09-11T17:11:32Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"ce9c5682b3b1b1166f60a3023cb7c1917e42e04cd06bcd53d60e8f586d750b37","abstract_canon_sha256":"b41fdcadc9606796be66d0b9d6ea6920b3c226f9d3a9dac2f237bfbf2d1ab6b9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:49:37.862780Z","signature_b64":"Cp3bdBQljUqUf54BGzjeDVVxJnlW9RMtu6Zx1X4CoaBvpYEprE6GKd52NEtH4A26zeCVBt1WlGMmoi7JXRCpCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1988b2ce30db4e90a9e557e1ce26c72c89d6f04de544da7b61bb0990c54f3247","last_reissued_at":"2026-07-05T06:49:37.862358Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:49:37.862358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Task-Oriented Cross-System Design for Timely and Accurate Modeling in the Metaverse","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Branka Vucetic, Changyang She, Guodong Zhao, Kan Chen, Muhammad Ali Imran, Yufeng Diao, Zhen Meng","submitted_at":"2023-09-11T17:11:32Z","abstract_excerpt":"In this paper, we establish a task-oriented cross-system design framework to minimize the required packet rate for timely and accurate modeling of a real-world robotic arm in the Metaverse, where sensing, communication, prediction, control, and rendering are considered. To optimize a scheduling policy and prediction horizons, we design a Constraint Proximal Policy Optimization(C-PPO) algorithm by integrating domain knowledge from relevant systems into the advanced reinforcement learning algorithm, Proximal Policy Optimization(PPO). Specifically, the Jacobian matrix for analyzing the motion of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.05622","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/2309.05622/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":"2309.05622","created_at":"2026-07-05T06:49:37.862429+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.05622v1","created_at":"2026-07-05T06:49:37.862429+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.05622","created_at":"2026-07-05T06:49:37.862429+00:00"},{"alias_kind":"pith_short_12","alias_value":"DGELFTRQ3NHJ","created_at":"2026-07-05T06:49:37.862429+00:00"},{"alias_kind":"pith_short_16","alias_value":"DGELFTRQ3NHJBKPF","created_at":"2026-07-05T06:49:37.862429+00:00"},{"alias_kind":"pith_short_8","alias_value":"DGELFTRQ","created_at":"2026-07-05T06:49:37.862429+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/DGELFTRQ3NHJBKPFK7Q44JWHFS","json":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS.json","graph_json":"https://pith.science/api/pith-number/DGELFTRQ3NHJBKPFK7Q44JWHFS/graph.json","events_json":"https://pith.science/api/pith-number/DGELFTRQ3NHJBKPFK7Q44JWHFS/events.json","paper":"https://pith.science/paper/DGELFTRQ"},"agent_actions":{"view_html":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS","download_json":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS.json","view_paper":"https://pith.science/paper/DGELFTRQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.05622&json=true","fetch_graph":"https://pith.science/api/pith-number/DGELFTRQ3NHJBKPFK7Q44JWHFS/graph.json","fetch_events":"https://pith.science/api/pith-number/DGELFTRQ3NHJBKPFK7Q44JWHFS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS/action/storage_attestation","attest_author":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS/action/author_attestation","sign_citation":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS/action/citation_signature","submit_replication":"https://pith.science/pith/DGELFTRQ3NHJBKPFK7Q44JWHFS/action/replication_record"}},"created_at":"2026-07-05T06:49:37.862429+00:00","updated_at":"2026-07-05T06:49:37.862429+00:00"}