{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:4IWJRKVHCUPHD5WX2NFPTSE3KR","short_pith_number":"pith:4IWJRKVH","canonical_record":{"source":{"id":"2303.10677","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-19T14:44:37Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"bdbfe39d8ac7e23a69cd0eff8120c6290214bdb9d44d75cb4682dd8a6932722e","abstract_canon_sha256":"bf5990b2b004b89062b1bc958645ba9b2d9ee6655389f6317cef4a3d845b049a"},"schema_version":"1.0"},"canonical_sha256":"e22c98aaa7151e71f6d7d34af9c89b545afbc5c1206420dc7f6d4e065a0aa84b","source":{"kind":"arxiv","id":"2303.10677","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.10677","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"arxiv_version","alias_value":"2303.10677v1","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.10677","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"pith_short_12","alias_value":"4IWJRKVHCUPH","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"pith_short_16","alias_value":"4IWJRKVHCUPHD5WX","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"pith_short_8","alias_value":"4IWJRKVH","created_at":"2026-07-05T05:52:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:4IWJRKVHCUPHD5WX2NFPTSE3KR","target":"record","payload":{"canonical_record":{"source":{"id":"2303.10677","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-19T14:44:37Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"bdbfe39d8ac7e23a69cd0eff8120c6290214bdb9d44d75cb4682dd8a6932722e","abstract_canon_sha256":"bf5990b2b004b89062b1bc958645ba9b2d9ee6655389f6317cef4a3d845b049a"},"schema_version":"1.0"},"canonical_sha256":"e22c98aaa7151e71f6d7d34af9c89b545afbc5c1206420dc7f6d4e065a0aa84b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:52:35.109818Z","signature_b64":"37ZYLF1F/lAIe2UMJZ5EWIBIyi/v6cTSEA65Rfg6b7/4GvgQ+XpqJtTXyQBOsM+DppRD3X0ttDU7Pg9RfMraAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e22c98aaa7151e71f6d7d34af9c89b545afbc5c1206420dc7f6d4e065a0aa84b","last_reissued_at":"2026-07-05T05:52:35.109474Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:52:35.109474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.10677","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:52:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sKfBCok7sIaUgV/QQq4n6u8XXk417CSozz4oi7pdHMRIcrKYtYSCL3zHC8JoxT1vvuIMjS8VwTr7QM9Ej4MuAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T04:13:01.507985Z"},"content_sha256":"936ce35deaa1499f7598a910b32e2d99dd2757eac3d82d90cd78a2e8c1b2a8d1","schema_version":"1.0","event_id":"sha256:936ce35deaa1499f7598a910b32e2d99dd2757eac3d82d90cd78a2e8c1b2a8d1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:4IWJRKVHCUPHD5WX2NFPTSE3KR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey of Federated Learning for Connected and Automated Vehicles","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.LG","authors_text":"Liangqi Yuan, Stanislaw H /.Zak, Vishnu Pandi Chellapandi, Ziran Wang","submitted_at":"2023-03-19T14:44:37Z","abstract_excerpt":"Connected and Automated Vehicles (CAVs) are one of the emerging technologies in the automotive domain that has the potential to alleviate the issues of accidents, traffic congestion, and pollutant emissions, leading to a safe, efficient, and sustainable transportation system. Machine learning-based methods are widely used in CAVs for crucial tasks like perception, motion planning, and motion control, where machine learning models in CAVs are solely trained using the local vehicle data, and the performance is not certain when exposed to new environments or unseen conditions. Federated learning "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.10677","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/2303.10677/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:52:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QH/x22/ZULitLKXq8uj/lLqrPBviHlisVN0jwOIjWoTm79CQKK1edLazXM+WwxudaAuiFOeWdsg3qUhx1Y29BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T04:13:01.508516Z"},"content_sha256":"7863f0ef1056c34a97dcdfba2a24735aaa73f2e0383a0f8dbc49e0964ad7575b","schema_version":"1.0","event_id":"sha256:7863f0ef1056c34a97dcdfba2a24735aaa73f2e0383a0f8dbc49e0964ad7575b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4IWJRKVHCUPHD5WX2NFPTSE3KR/bundle.json","state_url":"https://pith.science/pith/4IWJRKVHCUPHD5WX2NFPTSE3KR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4IWJRKVHCUPHD5WX2NFPTSE3KR/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-21T04:13:01Z","links":{"resolver":"https://pith.science/pith/4IWJRKVHCUPHD5WX2NFPTSE3KR","bundle":"https://pith.science/pith/4IWJRKVHCUPHD5WX2NFPTSE3KR/bundle.json","state":"https://pith.science/pith/4IWJRKVHCUPHD5WX2NFPTSE3KR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4IWJRKVHCUPHD5WX2NFPTSE3KR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:4IWJRKVHCUPHD5WX2NFPTSE3KR","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":"bf5990b2b004b89062b1bc958645ba9b2d9ee6655389f6317cef4a3d845b049a","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-19T14:44:37Z","title_canon_sha256":"bdbfe39d8ac7e23a69cd0eff8120c6290214bdb9d44d75cb4682dd8a6932722e"},"schema_version":"1.0","source":{"id":"2303.10677","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.10677","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"arxiv_version","alias_value":"2303.10677v1","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.10677","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"pith_short_12","alias_value":"4IWJRKVHCUPH","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"pith_short_16","alias_value":"4IWJRKVHCUPHD5WX","created_at":"2026-07-05T05:52:35Z"},{"alias_kind":"pith_short_8","alias_value":"4IWJRKVH","created_at":"2026-07-05T05:52:35Z"}],"graph_snapshots":[{"event_id":"sha256:7863f0ef1056c34a97dcdfba2a24735aaa73f2e0383a0f8dbc49e0964ad7575b","target":"graph","created_at":"2026-07-05T05:52:35Z","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/2303.10677/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Connected and Automated Vehicles (CAVs) are one of the emerging technologies in the automotive domain that has the potential to alleviate the issues of accidents, traffic congestion, and pollutant emissions, leading to a safe, efficient, and sustainable transportation system. Machine learning-based methods are widely used in CAVs for crucial tasks like perception, motion planning, and motion control, where machine learning models in CAVs are solely trained using the local vehicle data, and the performance is not certain when exposed to new environments or unseen conditions. Federated learning ","authors_text":"Liangqi Yuan, Stanislaw H /.Zak, Vishnu Pandi Chellapandi, Ziran Wang","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-19T14:44:37Z","title":"A Survey of Federated Learning for Connected and Automated Vehicles"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.10677","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":"sha256:936ce35deaa1499f7598a910b32e2d99dd2757eac3d82d90cd78a2e8c1b2a8d1","target":"record","created_at":"2026-07-05T05:52:35Z","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":"bf5990b2b004b89062b1bc958645ba9b2d9ee6655389f6317cef4a3d845b049a","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-19T14:44:37Z","title_canon_sha256":"bdbfe39d8ac7e23a69cd0eff8120c6290214bdb9d44d75cb4682dd8a6932722e"},"schema_version":"1.0","source":{"id":"2303.10677","kind":"arxiv","version":1}},"canonical_sha256":"e22c98aaa7151e71f6d7d34af9c89b545afbc5c1206420dc7f6d4e065a0aa84b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e22c98aaa7151e71f6d7d34af9c89b545afbc5c1206420dc7f6d4e065a0aa84b","first_computed_at":"2026-07-05T05:52:35.109474Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:52:35.109474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"37ZYLF1F/lAIe2UMJZ5EWIBIyi/v6cTSEA65Rfg6b7/4GvgQ+XpqJtTXyQBOsM+DppRD3X0ttDU7Pg9RfMraAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:52:35.109818Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.10677","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:936ce35deaa1499f7598a910b32e2d99dd2757eac3d82d90cd78a2e8c1b2a8d1","sha256:7863f0ef1056c34a97dcdfba2a24735aaa73f2e0383a0f8dbc49e0964ad7575b"],"state_sha256":"21d87af445bb45c38e8778615f1b022615ce691edfa33d6f6aff9b1f5f3b3afb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tKZY8QzkK6zmXUe4WkrG4nwWaxvL5jdXgV8CqVIPe1w5IgIkG2GLj/3ZJCpmvKZ64D9L4sYw1yL/BKgpHODoDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T04:13:01.517298Z","bundle_sha256":"7e3ee4f276e29833650cdbd92f97f49a51f334a72e2841d29e95ef709a6c245d"}}