{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4KZAWZPBZAAIBSC3KSRVWFRK2S","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":"c4ffc9be63384c07050d295b3728ceefb85d2e18780e96b9dc8c8fecd0cc9abf","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-12-12T14:01:24Z","title_canon_sha256":"d4069be443e9af57a5cb5e32f1bf980c514f56a707541d35a543d5ec17f80b08"},"schema_version":"1.0","source":{"id":"2512.11944","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2512.11944","created_at":"2026-05-29T02:04:59Z"},{"alias_kind":"arxiv_version","alias_value":"2512.11944v2","created_at":"2026-05-29T02:04:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2512.11944","created_at":"2026-05-29T02:04:59Z"},{"alias_kind":"pith_short_12","alias_value":"4KZAWZPBZAAI","created_at":"2026-05-29T02:04:59Z"},{"alias_kind":"pith_short_16","alias_value":"4KZAWZPBZAAIBSC3","created_at":"2026-05-29T02:04:59Z"},{"alias_kind":"pith_short_8","alias_value":"4KZAWZPB","created_at":"2026-05-29T02:04:59Z"}],"graph_snapshots":[{"event_id":"sha256:49ca6e6b5552b08fc19d8041e68846a5a0b89c13294f20d80568ed241ed441b7","target":"graph","created_at":"2026-05-29T02:04:59Z","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/2512.11944/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Motion planning for autonomous driving (AD) faces a critical trade-off. While traditional rule-based pipelines offer verifiable safety and interpretability, they often fail to generalize in complex scenarios. Conversely, emerging learning-based methods-including imitation learning (IL), reinforcement learning (RL), and generative AI-offer greater adaptability but are often constrained by opacity and safety risks. Existing surveys typically analyze these AI methods in isolation, overlooking the potential of integrating them with rigorous control frameworks. To bridge this gap, this paper presen","authors_text":"Haoran Wang, Jia Hu, Yang Chang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-12-12T14:01:24Z","title":"A Review of Learning-Based Motion Planning: Toward a Data-Driven Optimal Control Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2512.11944","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":"sha256:8c93de3ade59159264e38602ffd04da5fe92d93d68455baa355d7bdc16607585","target":"record","created_at":"2026-05-29T02:04:59Z","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":"c4ffc9be63384c07050d295b3728ceefb85d2e18780e96b9dc8c8fecd0cc9abf","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-12-12T14:01:24Z","title_canon_sha256":"d4069be443e9af57a5cb5e32f1bf980c514f56a707541d35a543d5ec17f80b08"},"schema_version":"1.0","source":{"id":"2512.11944","kind":"arxiv","version":2}},"canonical_sha256":"e2b20b65e1c80080c85b54a35b162ad4a216b76426a4e1763e5d234724fabbb3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e2b20b65e1c80080c85b54a35b162ad4a216b76426a4e1763e5d234724fabbb3","first_computed_at":"2026-05-29T02:04:59.894222Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T02:04:59.894222Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t2RxlxQPNrjFJmvh24IttgwrxKio+Wp2PpF87M7hUleGPhGn3DNFHGcBlCIJ2UvduxGus4MzlqT62RIoHmxIDw==","signature_status":"signed_v1","signed_at":"2026-05-29T02:04:59.895191Z","signed_message":"canonical_sha256_bytes"},"source_id":"2512.11944","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c93de3ade59159264e38602ffd04da5fe92d93d68455baa355d7bdc16607585","sha256:49ca6e6b5552b08fc19d8041e68846a5a0b89c13294f20d80568ed241ed441b7"],"state_sha256":"7559fe4c3c120c691a2c539fb203368449a4224285ad8ebce79d2d10480284bb"}