{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:E4YLA7WPGHEXFNBB7RSIVUXIJH","short_pith_number":"pith:E4YLA7WP","schema_version":"1.0","canonical_sha256":"2730b07ecf31c972b421fc648ad2e849cf96e17fd6566ee7b5bad510e50d452a","source":{"kind":"arxiv","id":"2508.03890","version":2},"attestation_state":"computed","paper":{"title":"Uncertainty-aware Accurate Elevation Modeling for Off-road Navigation via Neural Processes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Byron Boots, Daehoon Gwak, James Hays, Sanghun Jung","submitted_at":"2025-08-05T20:19:02Z","abstract_excerpt":"Terrain elevation modeling for off-road navigation aims to accurately estimate changes in terrain geometry in real-time and quantify the corresponding uncertainties. Having precise estimations and uncertainties plays a crucial role in planning and control algorithms to explore safe and reliable maneuver strategies. However, existing approaches, such as Gaussian Processes (GPs) and neural network-based methods, often fail to meet these needs. They are either unable to perform in real-time due to high computational demands, underestimating sharp geometry changes, or harming elevation accuracy wh"},"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":"2508.03890","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-08-05T20:19:02Z","cross_cats_sorted":[],"title_canon_sha256":"a86b1798ac4ea6a5b140a0969ba8b7eec09ffc70466b48e27dfadc5cd75e9b0a","abstract_canon_sha256":"d0b208b18f5e4e7d77a89f10c15bafb2920565568c33589565032dbc2be6e9a0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:50:39.828126Z","signature_b64":"gTu+VAXtCx0Mr13Sbfv77lS61SmIlhQuZ1ilLMUWY5li/nfMGDCZWT25ARIphGJ9hkna6ccxVwYqWs3aFdu8Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2730b07ecf31c972b421fc648ad2e849cf96e17fd6566ee7b5bad510e50d452a","last_reissued_at":"2026-07-05T11:50:39.827559Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:50:39.827559Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Uncertainty-aware Accurate Elevation Modeling for Off-road Navigation via Neural Processes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Byron Boots, Daehoon Gwak, James Hays, Sanghun Jung","submitted_at":"2025-08-05T20:19:02Z","abstract_excerpt":"Terrain elevation modeling for off-road navigation aims to accurately estimate changes in terrain geometry in real-time and quantify the corresponding uncertainties. Having precise estimations and uncertainties plays a crucial role in planning and control algorithms to explore safe and reliable maneuver strategies. However, existing approaches, such as Gaussian Processes (GPs) and neural network-based methods, often fail to meet these needs. They are either unable to perform in real-time due to high computational demands, underestimating sharp geometry changes, or harming elevation accuracy wh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.03890","kind":"arxiv","version":2},"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/2508.03890/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":"2508.03890","created_at":"2026-07-05T11:50:39.827628+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.03890v2","created_at":"2026-07-05T11:50:39.827628+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.03890","created_at":"2026-07-05T11:50:39.827628+00:00"},{"alias_kind":"pith_short_12","alias_value":"E4YLA7WPGHEX","created_at":"2026-07-05T11:50:39.827628+00:00"},{"alias_kind":"pith_short_16","alias_value":"E4YLA7WPGHEXFNBB","created_at":"2026-07-05T11:50:39.827628+00:00"},{"alias_kind":"pith_short_8","alias_value":"E4YLA7WP","created_at":"2026-07-05T11:50:39.827628+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/E4YLA7WPGHEXFNBB7RSIVUXIJH","json":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH.json","graph_json":"https://pith.science/api/pith-number/E4YLA7WPGHEXFNBB7RSIVUXIJH/graph.json","events_json":"https://pith.science/api/pith-number/E4YLA7WPGHEXFNBB7RSIVUXIJH/events.json","paper":"https://pith.science/paper/E4YLA7WP"},"agent_actions":{"view_html":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH","download_json":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH.json","view_paper":"https://pith.science/paper/E4YLA7WP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.03890&json=true","fetch_graph":"https://pith.science/api/pith-number/E4YLA7WPGHEXFNBB7RSIVUXIJH/graph.json","fetch_events":"https://pith.science/api/pith-number/E4YLA7WPGHEXFNBB7RSIVUXIJH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH/action/storage_attestation","attest_author":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH/action/author_attestation","sign_citation":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH/action/citation_signature","submit_replication":"https://pith.science/pith/E4YLA7WPGHEXFNBB7RSIVUXIJH/action/replication_record"}},"created_at":"2026-07-05T11:50:39.827628+00:00","updated_at":"2026-07-05T11:50:39.827628+00:00"}