{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3MSWY3AF25LYMA5SQTLR6AG6SN","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":"3219fb2c3027fbfd7ff9d70db67c8b2dce7202ca2bc50e42c27d43c7530ac9a7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-03-09T06:10:34Z","title_canon_sha256":"4bf7628753c33b625418f430f0197ed8df44c4d770cdc11e7c687169e3be0649"},"schema_version":"1.0","source":{"id":"2503.06468","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.06468","created_at":"2026-07-05T10:27:34Z"},{"alias_kind":"arxiv_version","alias_value":"2503.06468v1","created_at":"2026-07-05T10:27:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.06468","created_at":"2026-07-05T10:27:34Z"},{"alias_kind":"pith_short_12","alias_value":"3MSWY3AF25LY","created_at":"2026-07-05T10:27:34Z"},{"alias_kind":"pith_short_16","alias_value":"3MSWY3AF25LYMA5S","created_at":"2026-07-05T10:27:34Z"},{"alias_kind":"pith_short_8","alias_value":"3MSWY3AF","created_at":"2026-07-05T10:27:34Z"}],"graph_snapshots":[{"event_id":"sha256:087cc3870f2c509ac9bcba6a299610afa02fc9ff164f8a0553a715c25aebe752","target":"graph","created_at":"2026-07-05T10:27:34Z","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/2503.06468/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) is a promising paradigm that can enable collaborative model training between vehicles while protecting data privacy, thereby significantly improving the performance of intelligent transportation systems (ITSs). In vehicular networks, due to mobility, resource constraints, and the concurrent execution of multiple training tasks, how to allocate limited resources effectively to achieve optimal model training of multiple tasks is an extremely challenging issue. In this paper, we propose a mobility-aware multi-task decentralized federated learning (MMFL) framework for vehic","authors_text":"Di Yuan, Dongyu Chen, He Huang, Juncheng Jia, Keqin Li, Mianxiong Dong, Tao Deng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-03-09T06:10:34Z","title":"Mobility-Aware Multi-Task Decentralized Federated Learning for Vehicular Networks: Modeling, Analysis, and Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.06468","kind":"arxiv","version":1},"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":"sha256:0d0d62932337b62d1ba263959b2082490bf216641f675caf32ddf19043d81a5b","target":"record","created_at":"2026-07-05T10:27:34Z","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":"3219fb2c3027fbfd7ff9d70db67c8b2dce7202ca2bc50e42c27d43c7530ac9a7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-03-09T06:10:34Z","title_canon_sha256":"4bf7628753c33b625418f430f0197ed8df44c4d770cdc11e7c687169e3be0649"},"schema_version":"1.0","source":{"id":"2503.06468","kind":"arxiv","version":1}},"canonical_sha256":"db256c6c05d7578603b284d71f00de9379c9839335616ad14796c953b964af6b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"db256c6c05d7578603b284d71f00de9379c9839335616ad14796c953b964af6b","first_computed_at":"2026-07-05T10:27:34.445107Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:27:34.445107Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iuXD57jAz9nwGqBd9ZVGdy0Lg+HHW6PRlonQ2W5fICJa63q35cGoA/rOt4CxQtUDaZ/NhlaU+h1qIH1LtklfDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:27:34.447004Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.06468","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0d0d62932337b62d1ba263959b2082490bf216641f675caf32ddf19043d81a5b","sha256:087cc3870f2c509ac9bcba6a299610afa02fc9ff164f8a0553a715c25aebe752"],"state_sha256":"4d070ccb7ec55d02970e42457524746bbdfea25a18c218cf172fba4bc3f6759e"}