{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:K2FMIKGYFBB74Q5TT25EKET6DY","short_pith_number":"pith:K2FMIKGY","schema_version":"1.0","canonical_sha256":"568ac428d82843fe43b39eba45127e1e1a20fcc3b18fd77d93eed614cea7ad14","source":{"kind":"arxiv","id":"2606.07338","version":1},"attestation_state":"computed","paper":{"title":"VeriDrive: Verifiable Counterfactual Supervision for Cost-Efficient Vision-Language Planning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hubert P. H. Shum, Toby P. Breckon, Zikai Zhang","submitted_at":"2026-06-05T14:50:11Z","abstract_excerpt":"Vision-language driving models increasingly use reasoning supervision to bridge perception, prediction, and planning, but existing driving rationales are often free-form and expensive to generate with frontier models. We present VeriDrive, a framework for constructing planning-oriented, verifiable counterfactual supervision. VeriDrive converts driving reasoning into a structured Perception-Evaluation-Revision chain that grounds key objects in future motion, evaluates alternative ego trajectories with rule-checkable evidence, revises risky intent toward expert behavior, and produces final plann"},"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":"2606.07338","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-05T14:50:11Z","cross_cats_sorted":[],"title_canon_sha256":"2a5ae68d958e8d016c5d3126e46be41cae80d9c89cea5ddb337c0fa6789bb711","abstract_canon_sha256":"869faeb574927865b6db9259c6def295ba31cca57b10c2e5fbdf9f0d2472e88d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-08T01:05:20.514772Z","signature_b64":"zzSkB4FVHd33f+shKT1cRr7O1j+nfij07HmXuKGpiCElZBcYxnAreAH6pfF53QCCiQSGrwa+7sPnd5UJnQsbAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"568ac428d82843fe43b39eba45127e1e1a20fcc3b18fd77d93eed614cea7ad14","last_reissued_at":"2026-06-08T01:05:20.513917Z","signature_status":"signed_v1","first_computed_at":"2026-06-08T01:05:20.513917Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"VeriDrive: Verifiable Counterfactual Supervision for Cost-Efficient Vision-Language Planning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hubert P. H. Shum, Toby P. Breckon, Zikai Zhang","submitted_at":"2026-06-05T14:50:11Z","abstract_excerpt":"Vision-language driving models increasingly use reasoning supervision to bridge perception, prediction, and planning, but existing driving rationales are often free-form and expensive to generate with frontier models. We present VeriDrive, a framework for constructing planning-oriented, verifiable counterfactual supervision. VeriDrive converts driving reasoning into a structured Perception-Evaluation-Revision chain that grounds key objects in future motion, evaluates alternative ego trajectories with rule-checkable evidence, revises risky intent toward expert behavior, and produces final plann"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.07338","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/2606.07338/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":"2606.07338","created_at":"2026-06-08T01:05:20.514054+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.07338v1","created_at":"2026-06-08T01:05:20.514054+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.07338","created_at":"2026-06-08T01:05:20.514054+00:00"},{"alias_kind":"pith_short_12","alias_value":"K2FMIKGYFBB7","created_at":"2026-06-08T01:05:20.514054+00:00"},{"alias_kind":"pith_short_16","alias_value":"K2FMIKGYFBB74Q5T","created_at":"2026-06-08T01:05:20.514054+00:00"},{"alias_kind":"pith_short_8","alias_value":"K2FMIKGY","created_at":"2026-06-08T01:05:20.514054+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/K2FMIKGYFBB74Q5TT25EKET6DY","json":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY.json","graph_json":"https://pith.science/api/pith-number/K2FMIKGYFBB74Q5TT25EKET6DY/graph.json","events_json":"https://pith.science/api/pith-number/K2FMIKGYFBB74Q5TT25EKET6DY/events.json","paper":"https://pith.science/paper/K2FMIKGY"},"agent_actions":{"view_html":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY","download_json":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY.json","view_paper":"https://pith.science/paper/K2FMIKGY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.07338&json=true","fetch_graph":"https://pith.science/api/pith-number/K2FMIKGYFBB74Q5TT25EKET6DY/graph.json","fetch_events":"https://pith.science/api/pith-number/K2FMIKGYFBB74Q5TT25EKET6DY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY/action/storage_attestation","attest_author":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY/action/author_attestation","sign_citation":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY/action/citation_signature","submit_replication":"https://pith.science/pith/K2FMIKGYFBB74Q5TT25EKET6DY/action/replication_record"}},"created_at":"2026-06-08T01:05:20.514054+00:00","updated_at":"2026-06-08T01:05:20.514054+00:00"}