{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ZPTGKCC7KA6QUUBS6ROIOFTI4F","short_pith_number":"pith:ZPTGKCC7","canonical_record":{"source":{"id":"2508.19597","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-27T06:19:21Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"823333dd283ed6df8d4e00d7b49ea1ce1c008b227a0f5d9f7e256537c30406d2","abstract_canon_sha256":"a8ef9a847d15cf726753e4bc7e528d4769aba3dd8326ebb568e735d1f6e1186b"},"schema_version":"1.0"},"canonical_sha256":"cbe665085f503d0a5032f45c871668e16e430b40eb8051113638d2faee58ab3c","source":{"kind":"arxiv","id":"2508.19597","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.19597","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"arxiv_version","alias_value":"2508.19597v2","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.19597","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"pith_short_12","alias_value":"ZPTGKCC7KA6Q","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"pith_short_16","alias_value":"ZPTGKCC7KA6QUUBS","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"pith_short_8","alias_value":"ZPTGKCC7","created_at":"2026-07-05T12:06:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ZPTGKCC7KA6QUUBS6ROIOFTI4F","target":"record","payload":{"canonical_record":{"source":{"id":"2508.19597","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-27T06:19:21Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"823333dd283ed6df8d4e00d7b49ea1ce1c008b227a0f5d9f7e256537c30406d2","abstract_canon_sha256":"a8ef9a847d15cf726753e4bc7e528d4769aba3dd8326ebb568e735d1f6e1186b"},"schema_version":"1.0"},"canonical_sha256":"cbe665085f503d0a5032f45c871668e16e430b40eb8051113638d2faee58ab3c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:06:18.910372Z","signature_b64":"zZtIq5EGGr2wBrGVpBKAY5xEFLvJ1Cp0nFBJTInU3P7n9YSbNj9mZhSm4eKa3+iKUu5aHaNL0h8e9tSdFEaaAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cbe665085f503d0a5032f45c871668e16e430b40eb8051113638d2faee58ab3c","last_reissued_at":"2026-07-05T12:06:18.909797Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:06:18.909797Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.19597","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:06:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EwuD3igScNfW+uhFL4DKVTbgHd4zRw919cgcXupuFOFVhU0U2DoyIGpbIjMooQjjOqzWloA9MiOqh9KVvdUODw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:54:32.556537Z"},"content_sha256":"d0e0ad6dfebca971292f3472d41265b76259da2bf3f005b0fdb1b7b6dd5c3a39","schema_version":"1.0","event_id":"sha256:d0e0ad6dfebca971292f3472d41265b76259da2bf3f005b0fdb1b7b6dd5c3a39"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ZPTGKCC7KA6QUUBS6ROIOFTI4F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Complementary Learning System Empowers Online Continual Learning of Vehicle Motion Forecasting in Smart Cities","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Chao Lu, Cheng Gong, Chen Lv, Guodong Du, Jianwei Gong, Xiaocong Zhao, Yunlong Lin, Zirui Li","submitted_at":"2025-08-27T06:19:21Z","abstract_excerpt":"Artificial intelligence underpins most smart city services, yet deep neural network (DNN) that forecasts vehicle motion still struggle with catastrophic forgetting, the loss of earlier knowledge when models are updated. Conventional fixes enlarge the training set or replay past data, but these strategies incur high data collection costs, sample inefficiently and fail to balance long- and short-term experience, leaving them short of human-like continual learning. Here we introduce Dual-LS, a task-free, online continual learning paradigm for DNN-based motion forecasting that is inspired by the c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.19597","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/2508.19597/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":"2026-07-05T12:06:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ztnui9/DwqiLnMkL4E0aQMc3dSQjk+5AdWQ7/NqMf0IRLRtD10NhtKTUJG2oTmWC8DsJo0hsPX2Z/d0Kyvz6CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T23:54:32.557041Z"},"content_sha256":"51378bcd4de4eb24e5302c8d7869d4b596f897679d57022832f0260c47ae2908","schema_version":"1.0","event_id":"sha256:51378bcd4de4eb24e5302c8d7869d4b596f897679d57022832f0260c47ae2908"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZPTGKCC7KA6QUUBS6ROIOFTI4F/bundle.json","state_url":"https://pith.science/pith/ZPTGKCC7KA6QUUBS6ROIOFTI4F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZPTGKCC7KA6QUUBS6ROIOFTI4F/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":"2026-08-05T23:54:32Z","links":{"resolver":"https://pith.science/pith/ZPTGKCC7KA6QUUBS6ROIOFTI4F","bundle":"https://pith.science/pith/ZPTGKCC7KA6QUUBS6ROIOFTI4F/bundle.json","state":"https://pith.science/pith/ZPTGKCC7KA6QUUBS6ROIOFTI4F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZPTGKCC7KA6QUUBS6ROIOFTI4F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ZPTGKCC7KA6QUUBS6ROIOFTI4F","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":"a8ef9a847d15cf726753e4bc7e528d4769aba3dd8326ebb568e735d1f6e1186b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-27T06:19:21Z","title_canon_sha256":"823333dd283ed6df8d4e00d7b49ea1ce1c008b227a0f5d9f7e256537c30406d2"},"schema_version":"1.0","source":{"id":"2508.19597","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.19597","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"arxiv_version","alias_value":"2508.19597v2","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.19597","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"pith_short_12","alias_value":"ZPTGKCC7KA6Q","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"pith_short_16","alias_value":"ZPTGKCC7KA6QUUBS","created_at":"2026-07-05T12:06:18Z"},{"alias_kind":"pith_short_8","alias_value":"ZPTGKCC7","created_at":"2026-07-05T12:06:18Z"}],"graph_snapshots":[{"event_id":"sha256:51378bcd4de4eb24e5302c8d7869d4b596f897679d57022832f0260c47ae2908","target":"graph","created_at":"2026-07-05T12:06:18Z","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/2508.19597/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Artificial intelligence underpins most smart city services, yet deep neural network (DNN) that forecasts vehicle motion still struggle with catastrophic forgetting, the loss of earlier knowledge when models are updated. Conventional fixes enlarge the training set or replay past data, but these strategies incur high data collection costs, sample inefficiently and fail to balance long- and short-term experience, leaving them short of human-like continual learning. Here we introduce Dual-LS, a task-free, online continual learning paradigm for DNN-based motion forecasting that is inspired by the c","authors_text":"Chao Lu, Cheng Gong, Chen Lv, Guodong Du, Jianwei Gong, Xiaocong Zhao, Yunlong Lin, Zirui Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-27T06:19:21Z","title":"Complementary Learning System Empowers Online Continual Learning of Vehicle Motion Forecasting in Smart Cities"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.19597","kind":"arxiv","version":2},"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:d0e0ad6dfebca971292f3472d41265b76259da2bf3f005b0fdb1b7b6dd5c3a39","target":"record","created_at":"2026-07-05T12:06:18Z","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":"a8ef9a847d15cf726753e4bc7e528d4769aba3dd8326ebb568e735d1f6e1186b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-27T06:19:21Z","title_canon_sha256":"823333dd283ed6df8d4e00d7b49ea1ce1c008b227a0f5d9f7e256537c30406d2"},"schema_version":"1.0","source":{"id":"2508.19597","kind":"arxiv","version":2}},"canonical_sha256":"cbe665085f503d0a5032f45c871668e16e430b40eb8051113638d2faee58ab3c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cbe665085f503d0a5032f45c871668e16e430b40eb8051113638d2faee58ab3c","first_computed_at":"2026-07-05T12:06:18.909797Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:06:18.909797Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zZtIq5EGGr2wBrGVpBKAY5xEFLvJ1Cp0nFBJTInU3P7n9YSbNj9mZhSm4eKa3+iKUu5aHaNL0h8e9tSdFEaaAw==","signature_status":"signed_v1","signed_at":"2026-07-05T12:06:18.910372Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.19597","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d0e0ad6dfebca971292f3472d41265b76259da2bf3f005b0fdb1b7b6dd5c3a39","sha256:51378bcd4de4eb24e5302c8d7869d4b596f897679d57022832f0260c47ae2908"],"state_sha256":"3d26ac5f34252d5ba28cb2a50b3acd0f773ce0733fee83e04322e8e8ee9b4024"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/US8hNwXA2C53h00O/xbn1YKT7XcyzzPqgKobLvwR5FxM3YWDodhyXm2dj8yJn2FpgrlZY98ffqlXYiN/lJ0Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T23:54:32.560606Z","bundle_sha256":"589d07bf5f228cee21494271b49ca72721e24b0d0137f7e76a7d9166cba71324"}}