{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:MFJ4MGYN7VQIZ7FPILJTXBQE3Q","short_pith_number":"pith:MFJ4MGYN","schema_version":"1.0","canonical_sha256":"6153c61b0dfd608cfcaf42d33b8604dc0a26abed08ac0ec71575ee716b276175","source":{"kind":"arxiv","id":"2605.21897","version":1},"attestation_state":"computed","paper":{"title":"AdaPTwin: Adaptive Multi-Fidelity Predictive Digital Twin for Proactive Radio Resource Management in Vehicular Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NI","cs.SY"],"primary_cat":"eess.SY","authors_text":"Armin Makvandi, Md. Jahangir Hossain, Md. Zoheb Hassan","submitted_at":"2026-05-21T02:10:57Z","abstract_excerpt":"The highly dynamic nature of vehicular networks necessitates proactive and site-specific radio resource management (RRM) to achieve ultra-reliable low-latency communications. While Network Digital Twins (NDTs) have emerged as a promising enabler, ray-tracing remains time-consuming, challenging accurate RRM under latency constraints. We propose AdaPTwin, an adaptive multi-fidelity predictive NDT for proactive and latency-aware RRM in vehicular networks. Unlike single- and multi-fidelity NDTs with fixed fidelity levels, AdaPTwin dynamically adjusts NDT fidelity based on network conditions. The f"},"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":"2605.21897","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-05-21T02:10:57Z","cross_cats_sorted":["cs.NI","cs.SY"],"title_canon_sha256":"d6f35ba85d3453869b1356b091ab6716f67eec3873f9369d4335c3d480d49199","abstract_canon_sha256":"7c2c80f4a9929b9fa0721b2ead17c84539aac108a787f2a688e7c81de3280105"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T01:04:13.483333Z","signature_b64":"yNOPqJ29PqnZ8dz/6mH+sJru5UBpXV9RMwNbmMXcFuk7wjJaoMqI3DUi/cNP8YJit4JFHrDMT8Yki6cA0kJ8Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6153c61b0dfd608cfcaf42d33b8604dc0a26abed08ac0ec71575ee716b276175","last_reissued_at":"2026-05-22T01:04:13.482531Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T01:04:13.482531Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AdaPTwin: Adaptive Multi-Fidelity Predictive Digital Twin for Proactive Radio Resource Management in Vehicular Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.NI","cs.SY"],"primary_cat":"eess.SY","authors_text":"Armin Makvandi, Md. Jahangir Hossain, Md. Zoheb Hassan","submitted_at":"2026-05-21T02:10:57Z","abstract_excerpt":"The highly dynamic nature of vehicular networks necessitates proactive and site-specific radio resource management (RRM) to achieve ultra-reliable low-latency communications. While Network Digital Twins (NDTs) have emerged as a promising enabler, ray-tracing remains time-consuming, challenging accurate RRM under latency constraints. We propose AdaPTwin, an adaptive multi-fidelity predictive NDT for proactive and latency-aware RRM in vehicular networks. Unlike single- and multi-fidelity NDTs with fixed fidelity levels, AdaPTwin dynamically adjusts NDT fidelity based on network conditions. The f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.21897","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/2605.21897/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":"2605.21897","created_at":"2026-05-22T01:04:13.482649+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.21897v1","created_at":"2026-05-22T01:04:13.482649+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.21897","created_at":"2026-05-22T01:04:13.482649+00:00"},{"alias_kind":"pith_short_12","alias_value":"MFJ4MGYN7VQI","created_at":"2026-05-22T01:04:13.482649+00:00"},{"alias_kind":"pith_short_16","alias_value":"MFJ4MGYN7VQIZ7FP","created_at":"2026-05-22T01:04:13.482649+00:00"},{"alias_kind":"pith_short_8","alias_value":"MFJ4MGYN","created_at":"2026-05-22T01:04:13.482649+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/MFJ4MGYN7VQIZ7FPILJTXBQE3Q","json":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q.json","graph_json":"https://pith.science/api/pith-number/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/graph.json","events_json":"https://pith.science/api/pith-number/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/events.json","paper":"https://pith.science/paper/MFJ4MGYN"},"agent_actions":{"view_html":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q","download_json":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q.json","view_paper":"https://pith.science/paper/MFJ4MGYN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.21897&json=true","fetch_graph":"https://pith.science/api/pith-number/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/graph.json","fetch_events":"https://pith.science/api/pith-number/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/action/storage_attestation","attest_author":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/action/author_attestation","sign_citation":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/action/citation_signature","submit_replication":"https://pith.science/pith/MFJ4MGYN7VQIZ7FPILJTXBQE3Q/action/replication_record"}},"created_at":"2026-05-22T01:04:13.482649+00:00","updated_at":"2026-05-22T01:04:13.482649+00:00"}