{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:JFRSJG2PFX2IT6A5RWNTMMBRYR","short_pith_number":"pith:JFRSJG2P","canonical_record":{"source":{"id":"2503.05088","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-07T02:13:37Z","cross_cats_sorted":[],"title_canon_sha256":"56a79407d89e4a2bebf5ffe54975d3949576828861b228aa9453610deb677436","abstract_canon_sha256":"996f2102135537ee42af6470d6af45915c53550b9c04793072c27840ecf8f728"},"schema_version":"1.0"},"canonical_sha256":"4963249b4f2df489f81d8d9b363031c44d9e84746274eafe8f20ff2497c47b05","source":{"kind":"arxiv","id":"2503.05088","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.05088","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"arxiv_version","alias_value":"2503.05088v1","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.05088","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"pith_short_12","alias_value":"JFRSJG2PFX2I","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"pith_short_16","alias_value":"JFRSJG2PFX2IT6A5","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"pith_short_8","alias_value":"JFRSJG2P","created_at":"2026-07-05T10:26:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:JFRSJG2PFX2IT6A5RWNTMMBRYR","target":"record","payload":{"canonical_record":{"source":{"id":"2503.05088","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-07T02:13:37Z","cross_cats_sorted":[],"title_canon_sha256":"56a79407d89e4a2bebf5ffe54975d3949576828861b228aa9453610deb677436","abstract_canon_sha256":"996f2102135537ee42af6470d6af45915c53550b9c04793072c27840ecf8f728"},"schema_version":"1.0"},"canonical_sha256":"4963249b4f2df489f81d8d9b363031c44d9e84746274eafe8f20ff2497c47b05","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:26:20.368172Z","signature_b64":"b0TGwr79ppK5X5amsM8nQSSp7XmHjqwl+UR1JNuHqGFeLXFGb/hhktNAgdFz9FTIv2neBppU/Lb/cTnVwesjAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4963249b4f2df489f81d8d9b363031c44d9e84746274eafe8f20ff2497c47b05","last_reissued_at":"2026-07-05T10:26:20.367456Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:26:20.367456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.05088","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:26:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"siQoVuRDQs5f9Tu3TJKazVqILTE4C7FN32zhZwRl5h8LRwQRcOEj/DO6q8RRBTrWrBQSFoMqWCcAiKZXgRhXBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:17:15.610140Z"},"content_sha256":"6975af6f40e44cf9961cf5ca0a32747ba46e14e1b36f8da85abfb3779a3fdea5","schema_version":"1.0","event_id":"sha256:6975af6f40e44cf9961cf5ca0a32747ba46e14e1b36f8da85abfb3779a3fdea5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:JFRSJG2PFX2IT6A5RWNTMMBRYR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Bo Zhang, Changhong Lin, Jiarong Lin, Kehua Sheng, Rui Wang, XiaoZhi Qu, Zhiqiang Sui","submitted_at":"2025-03-07T02:13:37Z","abstract_excerpt":"Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy of the integrated location and orientation depends on the precision of the uncertainty modeling. Traditional methods of uncertainty modeling typically assume a Gaussian distribution and involve manual heuristic parameter tuning. However, these methods struggle to scale effectively and address long-tail scenarios. To address these challenges, we propose a learning-based method that encodes sensor information using hig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.05088","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/2503.05088/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:26:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nvvhg8YqbIMKMrykP44+INA1gwrIDIIq24aipegqey4FZGEdTCdYXl+CxDjfD93eZ+dgwTo9PrjB/PSV/l0kAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T16:17:15.610543Z"},"content_sha256":"f5e6f5052992aa6bf40782095028ba56d7ef47d001e0ea31c7ac8a4a64559a91","schema_version":"1.0","event_id":"sha256:f5e6f5052992aa6bf40782095028ba56d7ef47d001e0ea31c7ac8a4a64559a91"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JFRSJG2PFX2IT6A5RWNTMMBRYR/bundle.json","state_url":"https://pith.science/pith/JFRSJG2PFX2IT6A5RWNTMMBRYR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JFRSJG2PFX2IT6A5RWNTMMBRYR/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T16:17:15Z","links":{"resolver":"https://pith.science/pith/JFRSJG2PFX2IT6A5RWNTMMBRYR","bundle":"https://pith.science/pith/JFRSJG2PFX2IT6A5RWNTMMBRYR/bundle.json","state":"https://pith.science/pith/JFRSJG2PFX2IT6A5RWNTMMBRYR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JFRSJG2PFX2IT6A5RWNTMMBRYR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:JFRSJG2PFX2IT6A5RWNTMMBRYR","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"996f2102135537ee42af6470d6af45915c53550b9c04793072c27840ecf8f728","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-07T02:13:37Z","title_canon_sha256":"56a79407d89e4a2bebf5ffe54975d3949576828861b228aa9453610deb677436"},"schema_version":"1.0","source":{"id":"2503.05088","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.05088","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"arxiv_version","alias_value":"2503.05088v1","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.05088","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"pith_short_12","alias_value":"JFRSJG2PFX2I","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"pith_short_16","alias_value":"JFRSJG2PFX2IT6A5","created_at":"2026-07-05T10:26:20Z"},{"alias_kind":"pith_short_8","alias_value":"JFRSJG2P","created_at":"2026-07-05T10:26:20Z"}],"graph_snapshots":[{"event_id":"sha256:f5e6f5052992aa6bf40782095028ba56d7ef47d001e0ea31c7ac8a4a64559a91","target":"graph","created_at":"2026-07-05T10:26:20Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2503.05088/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy of the integrated location and orientation depends on the precision of the uncertainty modeling. Traditional methods of uncertainty modeling typically assume a Gaussian distribution and involve manual heuristic parameter tuning. However, these methods struggle to scale effectively and address long-tail scenarios. To address these challenges, we propose a learning-based method that encodes sensor information using hig","authors_text":"Bo Zhang, Changhong Lin, Jiarong Lin, Kehua Sheng, Rui Wang, XiaoZhi Qu, Zhiqiang Sui","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-07T02:13:37Z","title":"An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.05088","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:6975af6f40e44cf9961cf5ca0a32747ba46e14e1b36f8da85abfb3779a3fdea5","target":"record","created_at":"2026-07-05T10:26:20Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"996f2102135537ee42af6470d6af45915c53550b9c04793072c27840ecf8f728","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-03-07T02:13:37Z","title_canon_sha256":"56a79407d89e4a2bebf5ffe54975d3949576828861b228aa9453610deb677436"},"schema_version":"1.0","source":{"id":"2503.05088","kind":"arxiv","version":1}},"canonical_sha256":"4963249b4f2df489f81d8d9b363031c44d9e84746274eafe8f20ff2497c47b05","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4963249b4f2df489f81d8d9b363031c44d9e84746274eafe8f20ff2497c47b05","first_computed_at":"2026-07-05T10:26:20.367456Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:26:20.367456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"b0TGwr79ppK5X5amsM8nQSSp7XmHjqwl+UR1JNuHqGFeLXFGb/hhktNAgdFz9FTIv2neBppU/Lb/cTnVwesjAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:26:20.368172Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.05088","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6975af6f40e44cf9961cf5ca0a32747ba46e14e1b36f8da85abfb3779a3fdea5","sha256:f5e6f5052992aa6bf40782095028ba56d7ef47d001e0ea31c7ac8a4a64559a91"],"state_sha256":"c4a383166306ce48eeb4b5fe38ad2dd267ae136158718ae6cac165111b4787e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TxBeRx4zbxrflcZNcqtZPtjMGU90LUJTwfhArKlTKTnM46r+WQvcjZ2//tHbBz7NynGYbCHMx+vQmEtb2XosCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T16:17:15.612482Z","bundle_sha256":"3f493b6d8bec0d80f6aedd429f84600466666c72b531d41d73ddd6ecd7a555ae"}}