{"as_of":"2026-08-11T06:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:628f17839d87404a56199b210c2af7e87713819c05ba233428d77c4ff06e9873","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:15:08.169609Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.08743/citation-record","integrity":"/paper/2507.08743/integrity","json":"/paper/2507.08743/citation-record.json","paper":"/paper/2507.08743"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:15:15.643114Z","title":"Digital twin: Generalization, characterization and implementation,","venue":null,"work_id":"ed0b3574-4790-443e-bb77-6154b4939b95","year":null},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.109655Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:c52182e57bdfb6f8623ea5c5d27e5d4511839e592f4b595ad39dc7c9b7370948","observation_id":"a37cba9c-bbae-4564-9c6f-1c406197abfd","resolution":{"observed_at":"2026-08-06T18:15:15.744906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:15.362096Z","title":"Digital twin in manufacturing: A categorical literature review and classification,","venue":null,"work_id":"00c352f7-39f1-4d8e-aa25-390fc7c1ef5f","year":2018},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.281954Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:262e0fcefa664f6dc5e4e3d7e133b2dc43ba725e32633d11c24a7da6509e69d5","observation_id":"eeda84dc-f004-472f-b286-e448c00bead2","resolution":{"observed_at":"2026-08-06T18:15:15.427206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:15.205387Z","title":"Characterising the digital twin: A systematic literature review,","venue":null,"work_id":"fbaf0ef4-3171-41f6-837a-28aa28b654c8","year":2020},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.363898Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:6e5c86b913e582e71f23a6ec21b4d655c4abfa750f29ce8fc64cf68931194e82","observation_id":"ba3f044a-fb05-4da1-ab63-c867f7307254","resolution":{"observed_at":"2026-08-06T18:15:15.290595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:15.045417Z","title":"Digital twin: Enabling technologies, challenges and open research,","venue":null,"work_id":"30e0c9d9-c121-4f38-a2fa-795f864f85a2","year":2020},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.436091Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:ca920c2f3fec1ea5b37409f7597262af409804953f595ada9bb5bc20931fc38e","observation_id":"1b5244e2-41f9-4a64-a9b0-e1748ecbfb74","resolution":{"observed_at":"2026-08-06T18:15:15.104524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:14.851388Z","title":"Digital twin- assisted cooperative driving at non-signalized intersec- tions,","venue":null,"work_id":"3e74d4fe-1e66-493f-95f6-71b7a1c8be73","year":2021},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.498909Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:525cdc020da402a7cdd37a54ef038798917e14db6cbd58d2de5b085848c7718e","observation_id":"49a58a4c-d6f4-4299-9137-1778847d91b3","resolution":{"observed_at":"2026-08-06T18:15:14.948290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:14.722103Z","title":"Collaboration as a service: Digital-twin- enabled collaborative and distributed autonomous driv- ing,","venue":null,"work_id":"3b72f019-1340-4b51-8680-cef79eb4dc2f","year":2022},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.586696Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:ccd0732c1be9caf6600d860a64097aced8c90e61df64cd0dbff406da0d2c81f0","observation_id":"008ea090-60ce-4672-a15f-d403713b27e2","resolution":{"observed_at":"2026-08-06T18:15:14.769854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:14.569820Z","title":"Mixed cloud control testbed: Validating vehicle-road-cloud integration via mixed dig- ital twin,","venue":null,"work_id":"74700f2f-998d-49ca-8d0e-a9eeed02da7b","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.677772Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:dfe8405cf61f665721eafc17045c1b6e152f5ce1683fced91e48c36d79041fe5","observation_id":"123d7e9c-0680-42f6-88c8-5bc8cb76960d","resolution":{"observed_at":"2026-08-06T18:15:14.641046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:14.392326Z","title":"Digital twin-based cloud-native vehicular net- works architecture for intelligent driving,","venue":null,"work_id":"79fd0af2-6434-41a1-898b-ecda7f6e5d6d","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.741279Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:a91eac2141035258336f0aee17b6b2417e80eab754ba71c979681082e4589b56","observation_id":"661b6de6-adbe-4fee-bb4b-d0d878f202a8","resolution":{"observed_at":"2026-08-06T18:15:14.486782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:14.202329Z","title":"A digital twin-based traffic guidance scheme for autonomous driving,","venue":null,"work_id":"2ccc4d22-00bd-4f71-a507-feedaebc1cbe","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.821848Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:5f2941f7e1d9afee2caac8ff061da3a4c8e6b7dfac441c45b4191cd98bf3686d","observation_id":"a138df0e-4456-4838-b770-a12f53db3e52","resolution":{"observed_at":"2026-08-06T18:15:14.265310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:14.031124Z","title":"Smart mobility digital twin based automated vehicle navigation system: A proof of concept,","venue":null,"work_id":"a32f826d-17dd-4820-abdd-7e139167bbeb","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.903043Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:14f523eea025b8954141a53da79e709e8418d4a267c03bc4eb923875a51a1050","observation_id":"9614e6ed-221f-48ff-9653-4e02da9ef6d2","resolution":{"observed_at":"2026-08-06T18:15:14.064932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:13.894257Z","title":"Task-efficiency oriented v2x communications: Digital twin meets mobile edge computing,","venue":null,"work_id":"833dff05-d982-48df-bea4-abd96d3a3728","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.001569Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:05e6d67027992a22b845953b20679654099597c72c867036a20f365b418f93e3","observation_id":"11d35138-8ab5-4320-9838-9523e9d88973","resolution":{"observed_at":"2026-08-06T18:15:13.953013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:13.717454Z","title":"Wireless digital twin for assessing the reliability of vehicular communication links,","venue":null,"work_id":"50d6e07c-4e82-4c51-ba46-9ff67fb06b86","year":2022},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.112498Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:2648a9b57d6fff14925447a0cdb4dc8accc4a5060768fd9445a653099774aef0","observation_id":"27337ba9-0297-4446-83f6-aad9ab42e9ea","resolution":{"observed_at":"2026-08-06T18:15:13.812963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:13.527203Z","title":"Application of lightweight digital twin system in intel- ligent transportation,","venue":null,"work_id":"c14bdda3-48c1-471b-8a54-966d26379daf","year":2022},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.204654Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:badfb23fcdb0c727c28087b8a230ce4823068f4e4b26d7f232c7fef8477b03dd","observation_id":"f69b318e-db2e-4f16-afca-5bf8b8c107a6","resolution":{"observed_at":"2026-08-06T18:15:13.609643Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:13.329939Z","title":"A multi-modal simulation framework to enable digital twin-based v2x communications in dynamic environments,","venue":null,"work_id":"59af33ad-5b0f-4f8c-bf01-6c40f44bc489","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.288116Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:75dfc219c276c2b1d8152eaab722613565915306b49d73f1c0bdc9cc9a7a0e62","observation_id":"79290c91-5cda-4b02-8cd3-e11994d1f5f4","resolution":{"observed_at":"2026-08-06T18:15:13.421295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:13.134208Z","title":"Spat/map v2x communication between traffic light and vehicles and a realization with digital twin,","venue":null,"work_id":"b9dace4f-e9d7-4282-81e3-5fbd74c8a335","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.349335Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:2c9236265c1541083560a1a2ad309da18d1b4898ff26fe0630a89cb47d4b306e","observation_id":"2bf43fcc-4389-4a01-a1af-356a786c7317","resolution":{"observed_at":"2026-08-06T18:15:13.227427Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.10863","last_updated":"2023-07-01T22:24:17Z","snapshot_observed_at":"2026-08-10T16:26:14.517293Z","submitted_at":"2021-08-19T11:33:47Z","title":"A Transportation Digital-Twin Approach for Adaptive Traffic Control Systems","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.10863","snapshot_observed_at":"2026-08-06T18:15:04.428448Z","title":"A Transportation Digital-Twin Approach for Adaptive Traffic Control Systems,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.428448Z"},"links":{"cited_paper":"/paper/2109.10863","citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:d408084d7fc740c135624784fbd8099226bbf7246197e93a514c2276e985fe68","observation_id":"98c7c286-8c60-49e7-bfaf-401090609186","resolution":{"observed_at":"2026-08-06T18:15:04.428448Z","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":"2026-08-06T18:15:12.988404Z","title":"Digital twin for pedestrian safety warning at a single urban traffic intersection,","venue":null,"work_id":"500a45e9-00ca-48b5-ac7d-6d5da7a042b8","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.656065Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:2372651ed92db5a74b3e0f3a0b5d95b7f0756b69e8ce9048b22f0e9918de6b4a","observation_id":"b65c4715-a475-4fb4-ab06-13be7efe6d01","resolution":{"observed_at":"2026-08-06T18:15:13.041345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:12.817984Z","title":"Scan-to-graph: automatic generation and representation of highway geometric digital twins from point cloud data,","venue":null,"work_id":"70c7f9a8-df03-419e-a444-06ecffc92fa3","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:04.949365Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:857b37b31fe3c3be2b686ff2779b016d80e37385ccadb0f97aedb3e4859a461c","observation_id":"40ccc83c-8791-4fcd-a2b4-c628ad8644eb","resolution":{"observed_at":"2026-08-06T18:15:12.900034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:12.678872Z","title":"Building digital twins of existing highways using map data based on engineering expertise,","venue":null,"work_id":"60dafeb2-e62c-4c9b-a9f2-ffb3e562a1b6","year":2022},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.345514Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:48c7d40f4fca64a790f7049b91f2bec9b07eadf6f4e2db91c794c6f204d8a315","observation_id":"5edfb757-0aa0-43b9-99e2-8508918fe3b1","resolution":{"observed_at":"2026-08-06T18:15:12.725029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:12.557070Z","title":"3d highway curve reconstruction from mobile laser scanning point clouds,","venue":null,"work_id":"ffc449ca-172c-47cc-af52-a6d7d18507d8","year":2019},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.407291Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:758ba054de2f3def4176349227cbbdc414345b9da309db607d929756dced9af5","observation_id":"0463fbda-e253-409c-876f-f057daddd916","resolution":{"observed_at":"2026-08-06T18:15:12.608597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:12.382580Z","title":"Automating construction of road digital twin geometry using context and location aware segmentation,","venue":null,"work_id":"2b8b7227-0022-4726-8275-8f776e3eaf08","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.457245Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:193a1ec6c9a685de89b49d700e35c47fc15b57f5295801259ccac215a53dcad4","observation_id":"40a56e90-dcca-4043-bd1b-7e9fdd7460d6","resolution":{"observed_at":"2026-08-06T18:15:12.489506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:12.219101Z","title":"6-layer model for a struc- tured description and categorization of urban traffic and environment,","venue":null,"work_id":"c0321c2a-0a89-434c-9b8e-0fbb97e38ccb","year":2021},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.515338Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:b02e7ec327db1c77bdefff2b5e7a9d8c69e77ca8196d995ccb098f534750b8de","observation_id":"0b666e32-0071-4e5f-b0a1-548c0efb24a4","resolution":{"observed_at":"2026-08-06T18:15:12.289039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:12.063909Z","title":"Advances and open problems in federated learning,","venue":null,"work_id":"57dcac2f-5a86-4415-bb79-2271505cf588","year":2021},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.581351Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:7772964048e8ba9faa8f46fde2da7706f30ffbe76ce5d406c6b12dfd5f9dae5d","observation_id":"cc7f6f7d-1a70-4bcb-aaa1-eba41adce0ca","resolution":{"observed_at":"2026-08-06T18:15:12.140396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:11.791705Z","title":"A survey on federated learning in intelligent transportation systems,","venue":null,"work_id":"cd28ef57-f01c-4335-9f9f-3789a93827d7","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.659096Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:baf28cec889738461638863534e6b285804ae98d22e0b27fc769a9d335785a23","observation_id":"0c3f3eb8-d717-4789-b249-e0c9c3984c75","resolution":{"observed_at":"2026-08-06T18:15:11.880088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:11.620840Z","title":"A digital twin-based traffic light management system using BIRCH algorithm,","venue":null,"work_id":"4d16fff0-dcdb-4234-99de-24421da636e6","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.690150Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:7b5ed20d04220381d45248d2667025b0dafeee2267e7c889025eaab72a9c91fb","observation_id":"1bbf0fef-aad0-4ca5-8229-ccc241877d00","resolution":{"observed_at":"2026-08-06T18:15:11.685105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"6394.36182","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:15:08.508606Z","title":"A Digital Twin Environment for 5G Vehicle-to-Everything: Architecture and Open Issues,","venue":null,"work_id":"2e36a4ae-9365-4412-9309-8028c65c6653","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.740216Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:b9bf74e54800b0c94018710f88c60528e9c10c1e5fe62b991c1b06046e42dea6","observation_id":"7bd34f50-19f6-4c3b-a27b-38bd1f091b1f","resolution":{"observed_at":"2026-08-06T18:15:08.675258Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:11.480979Z","title":"Towards next generation of pedestrian and connected vehicle in-the-loop research: A digital twin co- simulation framework,","venue":null,"work_id":"8b69bad9-a9ff-4106-914d-6ce2994b0965","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.815918Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:a21a7d364a423a7a3bc0736ac32807b7b7f2ab90e251cc517c97e0d0fd9789e1","observation_id":"00ea7d4d-d38a-4968-96fe-196566c8b3b8","resolution":{"observed_at":"2026-08-06T18:15:11.545092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:11.274434Z","title":"Intelligent highway adaptive lane learning system in multiple rois of surveillance camera video,","venue":null,"work_id":"61ba9aaf-d61f-4636-8217-ce992049e1f1","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:05.921176Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:e96ea5cd11a9dfc2a5ee2ba6f49912359991faf442890bd41a0aaecbeec2af8d","observation_id":"0b649afd-771a-4610-b5d1-8f885a01a8af","resolution":{"observed_at":"2026-08-06T18:15:11.380159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:10.987251Z","title":"Lane detection in video-based intelligent transportation monitoring via fast extracting and clustering of vehicle motion trajectories,","venue":null,"work_id":"d68fe955-f668-4973-8058-aee5b78e528a","year":2014},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:06.069578Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:a5a78880c1c5ad94a41c859d419057985cc4a8e7083cd35d4fa6e5b2e5814872","observation_id":"26ab24c7-2689-475b-9fa7-186ec7b26ee3","resolution":{"observed_at":"2026-08-06T18:15:11.123844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:10.787295Z","title":"A review of ap- plications in federated learning,","venue":null,"work_id":"7c44f035-b14f-461a-a343-5ff3169dcb70","year":2020},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:06.452192Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:c4165d7c31409d6bd88b8af76d163e27af52cf5148aa10c13a82253063bc28cd","observation_id":"a4ac8efe-63ad-41b8-9955-e9fee0536f93","resolution":{"observed_at":"2026-08-06T18:15:10.884228Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:10.542111Z","title":"Adaptive federated learning and digital twin for industrial internet of things,","venue":null,"work_id":"c82b7a06-9894-43b7-ad5e-f1670400d0e6","year":2021},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:07.216614Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:1133a0bde95e7578d584d8687d3ff3afe0d7b7ffc4a00524fb3beab174c0cd18","observation_id":"e3a6f667-2f54-4b99-bd33-5d14d94bb2d2","resolution":{"observed_at":"2026-08-06T18:15:10.655088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:10.322638Z","title":"Digital twins-enabled federated learning in mo- bile networks: From the perspective of communication- assisted sensing,","venue":null,"work_id":"e0b8d99f-acb3-4ae0-8338-6a3e70fe26fa","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:07.298285Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:037de405777dbcd911f3e346f4582877b2e052be9e2bd18c2cb9c5604f40151b","observation_id":"febe9c67-e3f6-4da9-8b41-9b2b6d35571a","resolution":{"observed_at":"2026-08-06T18:15:10.409794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:10.099378Z","title":"Digital twin-enabled efficient federated learning for col- lision warning in intelligent driving,","venue":null,"work_id":"95a8413b-48e0-44f5-909d-8898cad8a016","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:07.511353Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:5f6baf766f4cbc194033d8111d6d0c75f067c4022afd1950c0d0f17948e7bfcd","observation_id":"411876b6-d497-4462-a111-9bd2054140aa","resolution":{"observed_at":"2026-08-06T18:15:10.214384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:09.764040Z","title":"Federated learning for digital twin-based vehicular networks: Architecture and chal- lenges,","venue":null,"work_id":"b2816370-32e4-4869-b0b4-e514d276a5d8","year":2024},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:07.651431Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:b765c2910c9daf05b30ea2b53cffaf5f614dc315dd5832bf618c54a7f4c8d957","observation_id":"3a198f5a-fda4-420e-aaf9-bd2a03be4020","resolution":{"observed_at":"2026-08-06T18:15:09.973209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:09.428317Z","title":"Learning to learn from apis: Black-box data-free meta-learning,","venue":null,"work_id":"81be8992-b291-4712-ac7f-4d808337bae6","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:07.841383Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:74564213f79a84ad9e140e9373094bf31e5ecb3dd7b652e0503828104fd55314","observation_id":"5e6e09ef-9fa7-4228-84ce-c7d1f10ea495","resolution":{"observed_at":"2026-08-06T18:15:09.581634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:09.148791Z","title":"Model-agnostic meta-learning for fast adaptation of deep networks,","venue":null,"work_id":"002c61a8-ad3b-47de-98b4-e8428407f4b4","year":2017},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:07.988973Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:93600110e4a584971f45004c4900a725223a8de6379d1de873babb2596f939a6","observation_id":"9cd52b38-7ee5-4303-9c96-b368b43cb6b3","resolution":{"observed_at":"2026-08-06T18:15:09.278381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:08.830194Z","title":"Ultralytics YOLO,","venue":null,"work_id":"07c1599a-df77-4227-aded-f7165e8101ff","year":2023},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:08.169609Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:6a506d8e1a376100f08e09ab211aa26730fbe8f4bbaba0bb2f6f074a66c94e54","observation_id":"e0bc6cbd-b35f-4790-a956-e12a969b4c2e","resolution":{"observed_at":"2026-08-06T18:15:08.996078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T18:15:15.494495Z","title":"Available: https://www.sciencedirect","venue":null,"work_id":"bd64b08d-4d11-48de-a7c3-695f85b366f9","year":null},"citing_paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T18:15:03.213922Z"},"links":{"citing_paper":"/paper/2507.08743"},"observation_digest":"sha256:6a400732ea76f82b94afb2b5c6bcb159785029602f3c1fee0a367cce6d167ecf","observation_id":"8c745f26-9441-4fba-9d74-d7147117b9f5","resolution":{"observed_at":"2026-08-06T18:15:15.560477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.08743","last_updated":"2025-07-11T16:45:59Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T18:07:44.780430Z","submitted_at":"2025-07-11T16:45:59Z","title":"Geo-ORBIT: A Federated Digital Twin Framework for Scene-Adaptive Lane Geometry Detection"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":36},"total_outbound_references":38},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.08743."}