{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:LMLO5SKSYL7SA7MUTVDCCMN5FJ","short_pith_number":"pith:LMLO5SKS","schema_version":"1.0","canonical_sha256":"5b16eec952c2ff207d949d462131bd2a78de256c1bc1e0e9174a7dceed9968c2","source":{"kind":"arxiv","id":"2208.04987","version":1},"attestation_state":"computed","paper":{"title":"Vehicle Type Specific Waypoint Generation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.HC","cs.RO","cs.SY","eess.SY"],"primary_cat":"cs.AI","authors_text":"Adam Scibior, Frank Wood, Jonathan Wilder Lavington, Yunpeng Liu","submitted_at":"2022-08-09T18:29:00Z","abstract_excerpt":"We develop a generic mechanism for generating vehicle-type specific sequences of waypoints from a probabilistic foundation model of driving behavior. Many foundation behavior models are trained on data that does not include vehicle information, which limits their utility in downstream applications such as planning. Our novel methodology conditionally specializes such a behavior predictive model to a vehicle-type by utilizing byproducts of the reinforcement learning algorithms used to produce vehicle specific controllers. We show how to compose a vehicle specific value function estimate with a "},"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":"2208.04987","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2022-08-09T18:29:00Z","cross_cats_sorted":["cs.HC","cs.RO","cs.SY","eess.SY"],"title_canon_sha256":"996d3965f1e8a4f3cc1398a0a309bd62296f916338e230cac5a0d21a793c303c","abstract_canon_sha256":"3e56a4c7ad06d6754fd30413c8d506927b20cc79cc03f31c411efd6ba0b284b6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:11:42.450329Z","signature_b64":"YnfU+QPEh5pPP4lg9nrslQT8XdZjTHLLwnsH4zIn14d6ADN8WdWxgvx9uztrO15J0fFAAuh+swOq/jaBwQS6Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b16eec952c2ff207d949d462131bd2a78de256c1bc1e0e9174a7dceed9968c2","last_reissued_at":"2026-07-05T06:11:42.449947Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:11:42.449947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Vehicle Type Specific Waypoint Generation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.HC","cs.RO","cs.SY","eess.SY"],"primary_cat":"cs.AI","authors_text":"Adam Scibior, Frank Wood, Jonathan Wilder Lavington, Yunpeng Liu","submitted_at":"2022-08-09T18:29:00Z","abstract_excerpt":"We develop a generic mechanism for generating vehicle-type specific sequences of waypoints from a probabilistic foundation model of driving behavior. Many foundation behavior models are trained on data that does not include vehicle information, which limits their utility in downstream applications such as planning. Our novel methodology conditionally specializes such a behavior predictive model to a vehicle-type by utilizing byproducts of the reinforcement learning algorithms used to produce vehicle specific controllers. We show how to compose a vehicle specific value function estimate with a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.04987","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/2208.04987/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":"2208.04987","created_at":"2026-07-05T06:11:42.450014+00:00"},{"alias_kind":"arxiv_version","alias_value":"2208.04987v1","created_at":"2026-07-05T06:11:42.450014+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.04987","created_at":"2026-07-05T06:11:42.450014+00:00"},{"alias_kind":"pith_short_12","alias_value":"LMLO5SKSYL7S","created_at":"2026-07-05T06:11:42.450014+00:00"},{"alias_kind":"pith_short_16","alias_value":"LMLO5SKSYL7SA7MU","created_at":"2026-07-05T06:11:42.450014+00:00"},{"alias_kind":"pith_short_8","alias_value":"LMLO5SKS","created_at":"2026-07-05T06:11:42.450014+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/LMLO5SKSYL7SA7MUTVDCCMN5FJ","json":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ.json","graph_json":"https://pith.science/api/pith-number/LMLO5SKSYL7SA7MUTVDCCMN5FJ/graph.json","events_json":"https://pith.science/api/pith-number/LMLO5SKSYL7SA7MUTVDCCMN5FJ/events.json","paper":"https://pith.science/paper/LMLO5SKS"},"agent_actions":{"view_html":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ","download_json":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ.json","view_paper":"https://pith.science/paper/LMLO5SKS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2208.04987&json=true","fetch_graph":"https://pith.science/api/pith-number/LMLO5SKSYL7SA7MUTVDCCMN5FJ/graph.json","fetch_events":"https://pith.science/api/pith-number/LMLO5SKSYL7SA7MUTVDCCMN5FJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ/action/storage_attestation","attest_author":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ/action/author_attestation","sign_citation":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ/action/citation_signature","submit_replication":"https://pith.science/pith/LMLO5SKSYL7SA7MUTVDCCMN5FJ/action/replication_record"}},"created_at":"2026-07-05T06:11:42.450014+00:00","updated_at":"2026-07-05T06:11:42.450014+00:00"}