{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:ACOPT4HAG4CVCMWOTZWRMPKXL2","short_pith_number":"pith:ACOPT4HA","schema_version":"1.0","canonical_sha256":"009cf9f0e037055132ce9e6d163d575e987db6e6e0051e5a0b0735ca1f725208","source":{"kind":"arxiv","id":"2401.07323","version":1},"attestation_state":"computed","paper":{"title":"MapNeXt: Revisiting Training and Scaling Practices for Online Vectorized HD Map Construction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Toyota Li","submitted_at":"2024-01-14T16:14:36Z","abstract_excerpt":"High-Definition (HD) maps are pivotal to autopilot navigation. Integrating the capability of lightweight HD map construction at runtime into a self-driving system recently emerges as a promising direction. In this surge, vision-only perception stands out, as a camera rig can still perceive the stereo information, let alone its appealing signature of portability and economy. The latest MapTR architecture solves the online HD map construction task in an end-to-end fashion but its potential is yet to be explored. In this work, we present a full-scale upgrade of MapTR and propose MapNeXt, the next"},"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":"2401.07323","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-01-14T16:14:36Z","cross_cats_sorted":[],"title_canon_sha256":"0d82d17b8c7dcb39edec836b47e2b85a1ded084a7a7e14637d249ceff2c09ae6","abstract_canon_sha256":"5c059cf7558452c9bbec1a3e6b4e22864fb1a854cd3ac18ef57078cb3fc66b57"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:33:35.491911Z","signature_b64":"QYYROV3pJ2Gljkpx0Rw4zd0xN4mCj0f79WqfplpvJs1SjTa/npCuW2eqh61LHSC0ECmyAT2XrRKv20KFJkeWAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"009cf9f0e037055132ce9e6d163d575e987db6e6e0051e5a0b0735ca1f725208","last_reissued_at":"2026-07-05T07:33:35.491533Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:33:35.491533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MapNeXt: Revisiting Training and Scaling Practices for Online Vectorized HD Map Construction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Toyota Li","submitted_at":"2024-01-14T16:14:36Z","abstract_excerpt":"High-Definition (HD) maps are pivotal to autopilot navigation. Integrating the capability of lightweight HD map construction at runtime into a self-driving system recently emerges as a promising direction. In this surge, vision-only perception stands out, as a camera rig can still perceive the stereo information, let alone its appealing signature of portability and economy. The latest MapTR architecture solves the online HD map construction task in an end-to-end fashion but its potential is yet to be explored. In this work, we present a full-scale upgrade of MapTR and propose MapNeXt, the next"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.07323","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/2401.07323/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":"2401.07323","created_at":"2026-07-05T07:33:35.491589+00:00"},{"alias_kind":"arxiv_version","alias_value":"2401.07323v1","created_at":"2026-07-05T07:33:35.491589+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.07323","created_at":"2026-07-05T07:33:35.491589+00:00"},{"alias_kind":"pith_short_12","alias_value":"ACOPT4HAG4CV","created_at":"2026-07-05T07:33:35.491589+00:00"},{"alias_kind":"pith_short_16","alias_value":"ACOPT4HAG4CVCMWO","created_at":"2026-07-05T07:33:35.491589+00:00"},{"alias_kind":"pith_short_8","alias_value":"ACOPT4HA","created_at":"2026-07-05T07:33:35.491589+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.00861","citing_title":"SafeMap: Robust HD Map Construction from Incomplete Observations","ref_index":24,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2","json":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2.json","graph_json":"https://pith.science/api/pith-number/ACOPT4HAG4CVCMWOTZWRMPKXL2/graph.json","events_json":"https://pith.science/api/pith-number/ACOPT4HAG4CVCMWOTZWRMPKXL2/events.json","paper":"https://pith.science/paper/ACOPT4HA"},"agent_actions":{"view_html":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2","download_json":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2.json","view_paper":"https://pith.science/paper/ACOPT4HA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2401.07323&json=true","fetch_graph":"https://pith.science/api/pith-number/ACOPT4HAG4CVCMWOTZWRMPKXL2/graph.json","fetch_events":"https://pith.science/api/pith-number/ACOPT4HAG4CVCMWOTZWRMPKXL2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2/action/storage_attestation","attest_author":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2/action/author_attestation","sign_citation":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2/action/citation_signature","submit_replication":"https://pith.science/pith/ACOPT4HAG4CVCMWOTZWRMPKXL2/action/replication_record"}},"created_at":"2026-07-05T07:33:35.491589+00:00","updated_at":"2026-07-05T07:33:35.491589+00:00"}