{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:V7MJJFE66UY7GDGLSST5TPAEB6","short_pith_number":"pith:V7MJJFE6","schema_version":"1.0","canonical_sha256":"afd894949ef531f30ccb94a7d9bc040f8a7ab54761530ee8fc16f918bec5ad6f","source":{"kind":"arxiv","id":"2606.31483","version":1},"attestation_state":"computed","paper":{"title":"A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Arno Eichberger, Dong Bi, Jiayuan Gong, Ji Zhou, Paul Kovacevic, Tomislav Mihalj, Yongqi Zhao","submitted_at":"2026-06-30T10:58:21Z","abstract_excerpt":"Personalized driving can improve the user acceptance of automated driving systems. However, existing methods still provide limited support for translating natural-language driving preferences, especially when such preferences are expressed implicitly, into executable and distinguishable driving behaviors. This paper proposes a large language model (LLM)-supported personalized driving framework for highway lane-change scenarios. The framework maps natural-language driving commands to executable planning parameters in the open-source Apollo automated driving stack according to three driving styl"},"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":"2606.31483","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-30T10:58:21Z","cross_cats_sorted":[],"title_canon_sha256":"32520c3e36452d5a6aefc055c7fcb9ce034592cbc1183d50be4def2bc8bf14eb","abstract_canon_sha256":"7405de97d70067f7b091278db98a1b583cbf5a53f0798f41a6ad88b23996ead9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-01T01:18:04.661527Z","signature_b64":"Idb9gWq3x3iOH4+oPopLRPb+pQVkWAb19DB+H53P1+RmWyWvnM97h2YbZRlMEEPwG/Ah1JwAHwepIQ/Cwx39Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"afd894949ef531f30ccb94a7d9bc040f8a7ab54761530ee8fc16f918bec5ad6f","last_reissued_at":"2026-07-01T01:18:04.661006Z","signature_status":"signed_v1","first_computed_at":"2026-07-01T01:18:04.661006Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Arno Eichberger, Dong Bi, Jiayuan Gong, Ji Zhou, Paul Kovacevic, Tomislav Mihalj, Yongqi Zhao","submitted_at":"2026-06-30T10:58:21Z","abstract_excerpt":"Personalized driving can improve the user acceptance of automated driving systems. However, existing methods still provide limited support for translating natural-language driving preferences, especially when such preferences are expressed implicitly, into executable and distinguishable driving behaviors. This paper proposes a large language model (LLM)-supported personalized driving framework for highway lane-change scenarios. The framework maps natural-language driving commands to executable planning parameters in the open-source Apollo automated driving stack according to three driving styl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.31483","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/2606.31483/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":"2606.31483","created_at":"2026-07-01T01:18:04.661064+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.31483v1","created_at":"2026-07-01T01:18:04.661064+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.31483","created_at":"2026-07-01T01:18:04.661064+00:00"},{"alias_kind":"pith_short_12","alias_value":"V7MJJFE66UY7","created_at":"2026-07-01T01:18:04.661064+00:00"},{"alias_kind":"pith_short_16","alias_value":"V7MJJFE66UY7GDGL","created_at":"2026-07-01T01:18:04.661064+00:00"},{"alias_kind":"pith_short_8","alias_value":"V7MJJFE6","created_at":"2026-07-01T01:18:04.661064+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/V7MJJFE66UY7GDGLSST5TPAEB6","json":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6.json","graph_json":"https://pith.science/api/pith-number/V7MJJFE66UY7GDGLSST5TPAEB6/graph.json","events_json":"https://pith.science/api/pith-number/V7MJJFE66UY7GDGLSST5TPAEB6/events.json","paper":"https://pith.science/paper/V7MJJFE6"},"agent_actions":{"view_html":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6","download_json":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6.json","view_paper":"https://pith.science/paper/V7MJJFE6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.31483&json=true","fetch_graph":"https://pith.science/api/pith-number/V7MJJFE66UY7GDGLSST5TPAEB6/graph.json","fetch_events":"https://pith.science/api/pith-number/V7MJJFE66UY7GDGLSST5TPAEB6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6/action/storage_attestation","attest_author":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6/action/author_attestation","sign_citation":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6/action/citation_signature","submit_replication":"https://pith.science/pith/V7MJJFE66UY7GDGLSST5TPAEB6/action/replication_record"}},"created_at":"2026-07-01T01:18:04.661064+00:00","updated_at":"2026-07-01T01:18:04.661064+00:00"}