{"as_of":"2026-08-18T05:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5a41ca265c8f1692d21a3c52c70cc12261e46426e34407e37950b8e6de06fe3f","coverage":[{"denominator":53,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":53,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T15:50:12.516780Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:15:40.285115Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-16T11:15:40.551556Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"cited_work":{"arxiv_id":"2502.01297","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.01297","snapshot_observed_at":"2026-08-16T11:15:40.551556Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","venue":"cs.CV","work_id":"49a9564d-0967-4bd6-93a4-815c8fbb58ca","year":2025},"citing_paper":{"arxiv_id":"2504.15970","last_updated":"2025-04-22T15:11:55Z","snapshot_observed_at":"2026-08-16T11:11:26.317714Z","submitted_at":"2025-04-22T15:11:55Z","title":"Recent Advances and Future Directions in Extended Reality (XR): Exploring AI-Powered Spatial Intelligence","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T11:15:40.285115Z"},"links":{"cited_paper":"/paper/2502.01297","citing_paper":"/paper/2504.15970"},"observation_digest":"sha256:49cc414c979c2b6a1e149d0f388fcc62e1deef5eb34ad348234c3fc1475ad275","observation_id":"36b167a5-2e45-4ce0-b04e-02b480eb32be","resolution":{"observed_at":"2026-08-16T11:15:40.556305Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.01297/citation-record","integrity":"/paper/2502.01297/integrity","json":"/paper/2502.01297/citation-record.json","paper":"/paper/2502.01297"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.737966Z","title":null,"venue":null,"work_id":"48926774-b3f7-4791-b9a7-7579c7176642","year":2017},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.215785Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:a9acc405aa750c8ed79af637ed8c892a32bc67af1a6ecb348f2131a9497c987e","observation_id":"f1f79c2e-3b81-434e-a57f-2552031c33f1","resolution":{"observed_at":"2026-08-09T15:50:13.742740Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.723059Z","title":null,"venue":null,"work_id":"2cbae58c-44d4-4ae6-9d96-248133ea0972","year":2022},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.221987Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:112a0631b45afc636f407d764d4472e86ef984657aa6740ef1c22ea86e7d2a79","observation_id":"1f94f58b-3538-49f4-88a2-b28236e04be7","resolution":{"observed_at":"2026-08-09T15:50:13.727633Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.707059Z","title":"Bloesch, M","venue":null,"work_id":"17e76cac-7458-462e-9de5-2b65c63fc366","year":2017},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.227065Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:76cd6034e2fcad99cf5ffa64083ebb3908c44056d339d4fe4d73b61b40366952","observation_id":"960a5d7e-529e-4101-941b-d094eb453391","resolution":{"observed_at":"2026-08-09T15:50:13.712072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.690658Z","title":null,"venue":null,"work_id":"fee5d8ab-0bf0-4b59-b625-d9521472d714","year":null},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.232573Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:89d4e245c3b86408e890c5de80fad7354afef7e0fe572e48ce3a05b534a18714","observation_id":"ed8bc729-c001-4038-a9dd-62dcce57c11d","resolution":{"observed_at":"2026-08-09T15:50:13.695999Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.674698Z","title":"Burri, J","venue":null,"work_id":"177697e5-5e61-41b5-a690-654ae5fc374d","year":2016},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.237606Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:db16f494c532701650fd3e0bde4cc21468315492d9cc1ea7982b88091511ef67","observation_id":"e6d8a410-647c-49cd-aa2d-edcfbca2421f","resolution":{"observed_at":"2026-08-09T15:50:13.679433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.658557Z","title":null,"venue":null,"work_id":"fe6e8da3-1839-4f18-ad85-8e5d6f4c1184","year":2021},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.242691Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:19809f62e7f0b3f1e7381b916fb18533515b4bb5e5765c7b123ad7cbe8cc8835","observation_id":"10feb8c8-67c1-49e0-86d9-28365b6d9fb8","resolution":{"observed_at":"2026-08-09T15:50:13.663502Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.642126Z","title":"Calonder, V","venue":null,"work_id":"c5220d20-78f2-4211-a0ac-f37dde51b3b8","year":2010},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.248015Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:86c6f11f57d261f994d82073dddb1aebcc89017f3e1f8ecf5bf2dcaf3e41ce12","observation_id":"3a5ce46d-ebc6-4b3a-aea3-deb6148882aa","resolution":{"observed_at":"2026-08-09T15:50:13.647266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.625855Z","title":"Campos, R","venue":null,"work_id":"6080f3bf-5b7c-47c3-b148-0a50257ffd9f","year":null},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.254615Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:cf14417b2e6d50649c29adec5633249e14815a0768f7ff77a18ecb5a3bdb6a1a","observation_id":"fecd9d33-a080-4c28-b541-d15942d29f69","resolution":{"observed_at":"2026-08-09T15:50:13.630685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.608468Z","title":"Campos, J","venue":null,"work_id":"2fbf640c-5605-48b6-b25d-c867e30fcbfe","year":2019},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.260183Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:165f5b3f1f9a7b260e4b183461d75d72ea4fbd84e53df64b1eed8e67fc2401d0","observation_id":"cbb47489-38c5-423a-81c3-d0fbf805e045","resolution":{"observed_at":"2026-08-09T15:50:13.613764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.588062Z","title":"Campos, J","venue":null,"work_id":"7f3540f7-6ae4-4f5c-81bd-8dc3206f51f4","year":2020},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.264869Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:6d57e40739dcfd48ae414e98b899c51f04b026b03d44da48df284208983da126","observation_id":"424e65c4-248a-42f8-a846-e47b2946df02","resolution":{"observed_at":"2026-08-09T15:50:13.594026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.570995Z","title":null,"venue":null,"work_id":"55d9f64b-e849-4371-af8f-ab063b42b44f","year":2021},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.269785Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:a4bdbd89fe6592e914761410d3b255c67b4982505a4c4843c9467ba03b7c998c","observation_id":"f80beacd-4f47-4bd5-918c-aa3250cd6923","resolution":{"observed_at":"2026-08-09T15:50:13.575863Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.554669Z","title":"Cortés, A","venue":null,"work_id":"691a01f3-1c4e-4567-9b33-63580c56438b","year":2018},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.274647Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:9d94e85009ac0112ab63ab5591147421eefbeb96721c4af09eb93e0e9555c5d1","observation_id":"cc9af4b0-6704-43d4-a70c-d8f4079c0949","resolution":{"observed_at":"2026-08-09T15:50:13.559842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2012.63862","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:12.936031Z","title":"Dong-Si and A","venue":null,"work_id":"04179d77-607d-49d7-8e7d-f55e380729c3","year":2012},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.279358Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:440c525cc9c3db28532f23215a15fafda2601fd3e8b30865344467082ecd64de","observation_id":"34fa8d3d-71c3-4bdf-b1df-7170d1f5fb9d","resolution":{"observed_at":"2026-08-09T15:50:12.943617Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.538234Z","title":"Engel, V","venue":null,"work_id":"14d15896-2f25-498e-851b-bccacfb65e78","year":null},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.284101Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:f4b2598e493a885f06188e96a02a47a7b7d0336779f2edd027b9b4aff8bac138","observation_id":"08f9f2ab-26f8-4a8b-95f7-bc7c6bf432e3","resolution":{"observed_at":"2026-08-09T15:50:13.543263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.522293Z","title":"Forster, L","venue":null,"work_id":"cb4c2503-db1e-43fb-84ab-d548a21c6310","year":2017},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.289020Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:e8428231b1dc49311c0c5ec71f0c3facf3e99b26a2a22f6d04403d313218661b","observation_id":"79ea29f3-9efb-4d46-8c51-cff784eab5ae","resolution":{"observed_at":"2026-08-09T15:50:13.526967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.506886Z","title":"Geneva, K","venue":null,"work_id":"dd620775-385e-41dd-bbfd-b78054987c82","year":2020},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.294152Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:e872d61fa92eb17edb24f37aa27a3d9536a78f81a4b6a482a35ae4cebcab2089","observation_id":"db96525c-3643-48d0-8b3b-6e9e329df128","resolution":{"observed_at":"2026-08-09T15:50:13.511952Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.489270Z","title":"Geneva and G","venue":null,"work_id":"17371b9c-cfbb-452b-8a0f-50a5bc1e9ed2","year":2022},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.299379Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:ddd6c41633f0ba586cf71a7a571801125d8abd89d0f6e51e38853aba8f670c3f","observation_id":"97f4bba4-db07-4d91-a9cf-df12843cdedf","resolution":{"observed_at":"2026-08-09T15:50:13.494381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.473710Z","title":null,"venue":null,"work_id":"874b74e8-3b4f-4d4f-962d-318f4caa3c6f","year":2017},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.304435Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:9c0923a053e82799845c8a66f8a707e3330596399921b7ae29c50e16ba36eabd","observation_id":"aca98308-9542-49db-8341-58a99b5285b9","resolution":{"observed_at":"2026-08-09T15:50:13.478395Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.456959Z","title":null,"venue":null,"work_id":"3df27440-8d3a-4f4a-ae71-c3bea4def67b","year":2023},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.309689Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:c4bc2229b073b97743003fd5fb99935958e70d4ad8ec2754b46d625ae516a303","observation_id":"a5e31ea6-3d00-4de8-96f0-6eaca0e45a9e","resolution":{"observed_at":"2026-08-09T15:50:13.462476Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.441004Z","title":"Huai and G","venue":null,"work_id":"8397f68b-4a26-4455-a13a-4d295bd7139b","year":2022},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.315300Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:aaf9a658fbe7b63cb001fae3673576ae4d028610d778a017690868774f005fd0","observation_id":"92ced38f-e252-42e6-b524-d283dd5c41fe","resolution":{"observed_at":"2026-08-09T15:50:13.445855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.424663Z","title":"Jinyu, Y","venue":null,"work_id":"e7c9de74-ae8d-418e-8733-193f5686f93e","year":null},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.320198Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:9e3a0da173df04b7cbbdc7841a07a971f0c2075a8cc350aca2c81ddea24833f5","observation_id":"58561bc1-72fc-49d3-b00c-26f102547da0","resolution":{"observed_at":"2026-08-09T15:50:13.430132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5244/c.25.16","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Kneip, M","venue":null,"work_id":"a9e91fb5-067d-4aac-9e5a-3498cde1c944","year":2011},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.325765Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:a791c24d98370a1cf10cf0faf8923e74bc3fb6d80f75518806ee9886f96cfe4b","observation_id":"a8c899d7-9c8d-4b24-bcba-9dae851dd4ad","resolution":{"observed_at":"2026-08-09T15:50:12.594608Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/iccv.2013.292","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Kneip and S","venue":null,"work_id":"fcbc9ad3-f7a4-4925-b4a0-7d2beef91173","year":2013},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.330864Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:828f63f9b2a01fe6d5a2cc2f20869dd4e38f5141e778361cfb1f9264478bc777","observation_id":"7f257a9d-566d-4713-9421-1876e9c2c447","resolution":{"observed_at":"2026-08-09T15:50:12.576991Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:12.335790Z","title":"Leutenegger, M","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.335790Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:39b7952f7ff83f0d2da9b5fe18314c77f3210a99299d6ecbedea96cfc000cc03","observation_id":"37e7b2bd-3cb8-4c30-8f38-f1664c159a17","resolution":{"observed_at":"2026-08-09T15:50:12.335790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.408585Z","title":"Leutenegger, S","venue":null,"work_id":"f2638701-f1ad-453e-a509-7f1167ff0245","year":2015},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.341274Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:0d16dda5a22adef79e36e989cf7c18bfd387e554e65e279a4315f6fdbeb412f9","observation_id":"26667930-fbc6-4ab3-abd6-92034983e075","resolution":{"observed_at":"2026-08-09T15:50:13.413851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.389988Z","title":"Lucas and T","venue":null,"work_id":"2348e272-40d9-4024-ade4-4e8e76f3433a","year":1981},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.347514Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:d8784656177d9767dda03f8d4728c63558683e5bbfb0cdd46b394822f5b3de42","observation_id":"bd56632e-abf2-43c5-8ee4-541b9c0fced6","resolution":{"observed_at":"2026-08-09T15:50:13.395923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.371675Z","title":"Martinelli","venue":null,"work_id":"f3f91a33-70f5-438b-90cf-e53cf8e6ae60","year":2014},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.353191Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:11e00215b940181c374c4985c41528ddedeee1b4554424afde4628cb44855b75","observation_id":"2a7ce20c-fcaf-4339-838f-06301e425bb2","resolution":{"observed_at":"2026-08-09T15:50:13.376764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.350233Z","title":null,"venue":null,"work_id":"98691e10-6b59-4131-afb4-72c1eb23610d","year":1982},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.359423Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:2c7d378bcecdaf25c6a952d3959f6c62b1e4b7b7f7a9db28c220523c93a84762","observation_id":"e5c2ef91-701f-4e23-bcf2-1b0a8ba262e9","resolution":{"observed_at":"2026-08-09T15:50:13.356467Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.333316Z","title":"Merrill, P","venue":null,"work_id":"e1e80949-798c-4949-9c0e-9038e065c63d","year":2023},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.364302Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:ecdc38c58a73e1f16e9310156c8e29adc0086dd41572ce67c08c97397b41e301","observation_id":"a10b6994-924a-4ee3-8b1c-15a6d3b529fa","resolution":{"observed_at":"2026-08-09T15:50:13.339166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.316461Z","title":null,"venue":null,"work_id":"8211d678-52e6-49a2-b4a3-fb90a2e7d0dd","year":2007},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.369108Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:7b878e43f80ba9e8b3b21067e912a95efc0dad77d82f7c83db67d42a62a9ddbb","observation_id":"d4713e93-41bd-4856-9007-2d011ec9545d","resolution":{"observed_at":"2026-08-09T15:50:13.321877Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.298299Z","title":"Mur-Artal, J","venue":null,"work_id":"330eed41-3658-4044-be03-0cdf717529a7","year":2015},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.374722Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:cd7b65efc26ca52db844ee0e825cc50c6eb1ace8d9b750fe6347af94a4cebb81","observation_id":"f97448bd-68fe-4c02-9094-cf16c3398656","resolution":{"observed_at":"2026-08-09T15:50:13.304508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.278605Z","title":"Mur-Artal and J","venue":null,"work_id":"dc6e09bc-4b25-4809-83e3-4ac54d0fe766","year":2017},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.381723Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:efa64f8d2b486f62708dedaafb2bc6a5a362580bccb7663a7d7249ac7513a70c","observation_id":"a7bb21ef-86c5-44e5-8deb-da83a53cea7c","resolution":{"observed_at":"2026-08-09T15:50:13.284042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.264278Z","title":null,"venue":null,"work_id":"967e0f94-5f92-4ce0-8923-af0a7b845767","year":2004},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.393729Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:a1703ae4484215c414fc17c15ae31351cd8505f9d48d38bb821d86a3255a2de8","observation_id":"b2c1bd4b-c3c0-42e9-9180-5d2565a43add","resolution":{"observed_at":"2026-08-09T15:50:13.268825Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.250000Z","title":null,"venue":null,"work_id":"abbb1b22-8ecc-4ef2-b4b1-748c281a79f2","year":2019},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.399092Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:bb68447ea611c6abf041fe1caa42d9dac58039b1495d56f7f1de884aefb4decb","observation_id":"f74d69e2-058b-43d3-88b5-95ca0380f5ff","resolution":{"observed_at":"2026-08-09T15:50:13.254645Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.232906Z","title":null,"venue":null,"work_id":"b8e3ec0a-1460-4d18-beb4-d290d52219e5","year":2018},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.404611Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:6efd21a9db0bdb137a71fc2b53b60fb1af8785cd58cd6c8ee54a3dd277db3157","observation_id":"b5984440-21da-4ae8-8835-7763581e730d","resolution":{"observed_at":"2026-08-09T15:50:13.237752Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.213360Z","title":null,"venue":null,"work_id":"e55cd40f-8286-4e2f-9fc4-16f72cfbe128","year":2019},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.410394Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:45be0d1da9be889df824d882554ff8cd7e757f270f77cef0b3025ebb9899248d","observation_id":"db1ea51b-fe7b-4c58-bbaf-a446d2bcbfb4","resolution":{"observed_at":"2026-08-09T15:50:13.219601Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:12.415998Z","title":"Qin and S","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.415998Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:255acad760cb948ad453342abc8a39e687c80ef79beefd47b72ac0cc9da7e15d","observation_id":"0360d6b2-2b3a-4d7c-8eb7-aa9b9437b7db","resolution":{"observed_at":"2026-08-09T15:50:12.415998Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.194598Z","title":"Ranftl, K","venue":null,"work_id":"d97f45d2-a203-4624-8d17-64faeb30307f","year":2020},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.421812Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:72fe762a34cb757fadc816efbad5d744cec297fb622114a0922b13f891cc9319","observation_id":"b8e5e0b9-b401-40a9-a5e9-c3c7423d7296","resolution":{"observed_at":"2026-08-09T15:50:13.200252Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.176884Z","title":"Rublee, V","venue":null,"work_id":"bbfb8cd7-e471-4ee5-b24f-65f28ab1922d","year":2011},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.428166Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:5f5f50328497f16839fc7ab0796dd2d4a9f69cc1bf5db99599be174772331c80","observation_id":"a95abd5b-63fe-4bf1-b96a-0f0dfc3da117","resolution":{"observed_at":"2026-08-09T15:50:13.181706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.160976Z","title":"Sarlin, D","venue":null,"work_id":"34638f08-b947-45a6-b85c-cf7dee662ffb","year":2020},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.433794Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:c4617f927a289de8ad52ec79286b03ce001201b0bcbcd7bd39a4241d14bcacda","observation_id":"67901a05-75bf-4b4e-848a-d987f0a23ad6","resolution":{"observed_at":"2026-08-09T15:50:13.166020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:12.444472Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.444472Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:7f3b60e9d74ee948753812b01a5bddeee6ef3847259fd9f8c0873ed044c27d94","observation_id":"67057381-250b-4e94-9890-01040a175762","resolution":{"observed_at":"2026-08-09T15:50:12.444472Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.139391Z","title":"Seiskari, P","venue":null,"work_id":"72b647c9-e064-46bc-8c27-7b4f7f6079ad","year":2022},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.452415Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:fb582d7a329aecf1a756ff28a0b782fe165a1fe50ff6bafaadc6ff5f7ecded39","observation_id":"bc8bc469-ca7a-4399-b743-eb855ee114cb","resolution":{"observed_at":"2026-08-09T15:50:13.146631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.121946Z","title":"Shi and Tomasi","venue":null,"work_id":"07ab470f-29ac-483c-9159-a0eb77826f36","year":1994},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.463819Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:3cc280b875ecb8a9fed0da1c711d4be3d368cfa71b23f92b45f74acb7879c45d","observation_id":"e1c3c3d4-28fb-4369-a234-f1e35b8f8bff","resolution":{"observed_at":"2026-08-09T15:50:13.127275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.105180Z","title":null,"venue":null,"work_id":"16353e72-f0fd-4c33-bb67-0da09f11bfe2","year":null},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.469847Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:4875ef93f3cef60f40ffc315fff45a89cdb5913b36ec958e3c63f873e261ed20","observation_id":"2199b9e0-6495-47d4-bbf1-b01cdbf0b7a7","resolution":{"observed_at":"2026-08-09T15:50:13.110780Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.088042Z","title":"Triggs, P","venue":null,"work_id":"2793d10a-d708-4061-97e8-3219075623bb","year":1999},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.474746Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:249fd4c91c5de1ac9323b90b7bca3d177d44f7281b452ec9035d7a33bce42a72","observation_id":"98ce23cd-d3f8-46b1-9390-b3d0e7309b54","resolution":{"observed_at":"2026-08-09T15:50:13.093412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.071056Z","title":"von Stumberg and D","venue":null,"work_id":"68cabe40-3f81-4754-b2a6-1a349b256be2","year":2022},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.480047Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:1dfa37f8b1941e9041077471853de025500819eb89c4fe7939d368196bbedbfd","observation_id":"082bb06f-9519-463d-9516-dedeb39d3884","resolution":{"observed_at":"2026-08-09T15:50:13.076689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.054218Z","title":"V on Stumberg, V","venue":null,"work_id":"bcb7bec9-3a82-4583-aa55-c9b12f3e3539","year":2018},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.485151Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:57ea8253fbe9a9cf8d156c45f597cad170aca1c71b60e99ecc7654fa77f4d1a9","observation_id":"18b3d02c-1f54-4076-aa13-f036e0293433","resolution":{"observed_at":"2026-08-09T15:50:13.059720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.038276Z","title":null,"venue":null,"work_id":"6602550f-4c53-420f-95ce-5de24ef2d26d","year":2015},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.489762Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:abefbb16f31b2d97d8ef20abfca2eec86a83e71f627e167e00086d8966e89555","observation_id":"d56b21da-b72e-4fa8-ba93-5d8a9c293728","resolution":{"observed_at":"2026-08-09T15:50:13.043053Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.021268Z","title":"Zhang and D","venue":null,"work_id":"67f99e68-3c10-4cee-a628-6b666d857959","year":2018},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.494403Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:dfcd1a458bcf58a4e58046ba47346dbfebac72f649406c4ae1e5b357ee158e37","observation_id":"2d318adc-fc01-4f1a-ac98-2ab47beec9e0","resolution":{"observed_at":"2026-08-09T15:50:13.026490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:13.004561Z","title":"Zhong, L","venue":null,"work_id":"d464a877-ed1b-434d-8e62-d4f56316299a","year":2023},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.499485Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:0d6c55824808d0c2f6e4377de404df22ff51a6e38a1cc4e31ab0f7ca17022b64","observation_id":"d3cc8b96-b47b-4f9b-ad59-90f0badcc67b","resolution":{"observed_at":"2026-08-09T15:50:13.010002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:12.988478Z","title":null,"venue":null,"work_id":"83bf1103-0ec2-4e9f-beb2-18c8b50c010a","year":2022},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.504853Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:8545fff3c53322d668dfa1535d49b916329bc39b5eb9f48af38e9adf1bf13e0d","observation_id":"fa538bfd-cd26-41f0-8b3c-edfea6525210","resolution":{"observed_at":"2026-08-09T15:50:12.993449Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:12.971147Z","title":null,"venue":null,"work_id":"bcd25e3f-be59-4636-9a43-cea62ac36970","year":2017},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.510680Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:632b0e572d32781640f1ce7a80b7ad7ee3abbce9efe4c6db71eb26349b940dd7","observation_id":"9b3b4038-8ebf-482c-8464-c59ab42a6124","resolution":{"observed_at":"2026-08-09T15:50:12.975947Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:50:12.953733Z","title":"Zuñiga-Noël, F.-A","venue":null,"work_id":"a74cacad-2e64-4246-a5b5-3200f0333d09","year":2021},"citing_paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-09T15:50:12.516780Z"},"links":{"citing_paper":"/paper/2502.01297"},"observation_digest":"sha256:a7ce9f1afd73118d46c3900a49bbbe6854f701d82c80ac15447cf272b9903a87","observation_id":"f542f9ce-5d75-4902-a65d-a1b25ee0ee31","resolution":{"observed_at":"2026-08-09T15:50:12.958372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.01297","last_updated":"2025-02-03T12:17:51Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T11:17:54.052806Z","submitted_at":"2025-02-03T12:17:51Z","title":"XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications"},"reference_resolution":{"displayed":53,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":19,"verified_exact":2,"verified_fuzzy":30},"total_outbound_references":53},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2502.01297."}