{"as_of":"2026-08-05T15:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7c0f4bc0286c365cfa62f9bccc23d005904b5b34cf46723c35e1327ccd8b03e5","coverage":[{"denominator":72,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":72,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T14:15:22.880265Z","state":"measured"},{"denominator":76,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":76,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T12:35:16.147653Z","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":"2026-07-04T16:29:57.449515Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"cited_work":{"arxiv_id":"2512.21078","doi":null,"metadata_source":"pith","pith_arxiv_id":"2512.21078","snapshot_observed_at":"2026-07-04T16:29:57.449515Z","title":"UniPR-3D: Towards universal visual place recognition with visual geometry grounded transformer","venue":"cs.CV","work_id":"4e723783-10c9-4905-aef0-9ce84581a649","year":2025},"citing_paper":{"arxiv_id":"2604.14795","last_updated":"2026-04-16T08:58:57Z","snapshot_observed_at":"2026-07-06T23:02:31.717911Z","submitted_at":"2026-04-16T08:58:57Z","title":"Keep It CALM: Toward Calibration-Free Kilometer-Level SLAM with Visual Geometry Foundation Models via an Assistant Eye","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-10T11:16:16.958472Z"},"links":{"cited_paper":"/paper/2512.21078","citing_paper":"/paper/2604.14795"},"observation_digest":"sha256:329b35281fe3e35a75521339d85c53970988a2e26678d992531f69653dee2d20","observation_id":"09d731d8-7049-4436-b0c8-4a367d558392","resolution":{"observed_at":"2026-06-30T03:18:05.886082Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"cited_work":{"arxiv_id":"2512.21078","doi":null,"metadata_source":"pith","pith_arxiv_id":"2512.21078","snapshot_observed_at":"2026-07-04T16:29:57.449515Z","title":"UniPR-3D: Towards universal visual place recognition with visual geometry grounded transformer","venue":"cs.CV","work_id":"4e723783-10c9-4905-aef0-9ce84581a649","year":2025},"citing_paper":{"arxiv_id":"2605.16911","last_updated":"2026-05-16T09:51:04Z","snapshot_observed_at":"2026-07-06T23:27:57.805018Z","submitted_at":"2026-05-16T09:51:04Z","title":"VGGT-Occ: Geometry-Grounded and Density-Aware Gated Fusion for 3D Occupancy Prediction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-19T21:19:17.894557Z"},"links":{"cited_paper":"/paper/2512.21078","citing_paper":"/paper/2605.16911"},"observation_digest":"sha256:57092861f228fb46293be220ccdffd75c6420b345030306cd74f88c5805ca476","observation_id":"c6c82e1e-580d-4d1d-a7e7-b88d5238dd56","resolution":{"observed_at":"2026-06-30T03:18:05.886082Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"cited_work":{"arxiv_id":"2512.21078","doi":null,"metadata_source":"pith","pith_arxiv_id":"2512.21078","snapshot_observed_at":"2026-07-04T16:29:57.449515Z","title":"UniPR-3D: Towards universal visual place recognition with visual geometry grounded transformer","venue":"cs.CV","work_id":"4e723783-10c9-4905-aef0-9ce84581a649","year":2025},"citing_paper":{"arxiv_id":"2606.24234","last_updated":"2026-07-07T08:54:08Z","snapshot_observed_at":"2026-08-03T11:09:10.565475Z","submitted_at":"2026-06-23T07:22:54Z","title":"From Open Waters to Enclosed Cabins: ProteusVPR for Cross-Scene Visual Place Recognition in Maritime Perception and Cabin Inspection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-26T00:35:38.735712Z"},"links":{"cited_paper":"/paper/2512.21078","citing_paper":"/paper/2606.24234"},"observation_digest":"sha256:979ed786decf259ec835cd95fbf0ae23b3cdb70fad9318fc4d50984bfe6ccb68","observation_id":"6c989688-fcb6-4895-8b1d-f996cb21ea5e","resolution":{"observed_at":"2026-07-04T16:29:57.450921Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2512.21078","snapshot_observed_at":"2026-07-12T12:35:16.147653Z","title":"Unipr-3d: Towards universal visual place recogni- tion with visual geometry grounded transformer","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.24234","last_updated":"2026-07-07T08:54:08Z","snapshot_observed_at":"2026-08-03T11:09:10.565475Z","submitted_at":"2026-06-23T07:22:54Z","title":"From Open Waters to Enclosed Cabins: ProteusVPR for Cross-Scene Visual Place Recognition in Maritime Perception and Cabin Inspection","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-12T12:35:16.147653Z"},"links":{"cited_paper":"/paper/2512.21078","citing_paper":"/paper/2606.24234"},"observation_digest":"sha256:15ff21624b018820bac064616256f30de71a4450c7003e8a45047905310df6fa","observation_id":"5b29a7ac-b8ed-4d06-a848-4fa4106c5096","resolution":{"observed_at":"2026-07-12T12:35:16.147653Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2512.21078/citation-record","integrity":"/paper/2512.21078/integrity","json":"/paper/2512.21078/citation-record.json","paper":"/paper/2512.21078"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.560631Z","title":"Gsv-cities: Toward appropriate supervised visual place recognition.Neurocomputing, 513:194–203, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.560631Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:2e9646087e74b38368c254fa5c6eb30e244eff2cfc979ef78ee122a5f417f21e","observation_id":"a8ff1f00-130e-406c-a3c9-8e885e30a1da","resolution":{"observed_at":"2026-08-03T14:15:22.560631Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.566095Z","title":"Mixvpr: Feature mixing for visual place recognition","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.566095Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:7118ae1e982caa64720304137c384ecc307672f8dac0344fea732306540e6fa4","observation_id":"146e3d73-9256-4d50-ae0e-ca83d7c6427e","resolution":{"observed_at":"2026-08-03T14:15:22.566095Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.570436Z","title":"Netvlad: Cnn architecture for weakly supervised place recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.570436Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:cef9c84db801d1c7232ae65104a82d6e864c225cd23c9c9921b0593289d62daf","observation_id":"6c5b3286-f324-4872-b7c9-ab389084b9b5","resolution":{"observed_at":"2026-08-03T14:15:22.570436Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.575365Z","title":"Towards life-long visual localization us- ing an efficient matching of binary sequences from images","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.575365Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:9eec4f0e319d060de897605125481a51cf511b3279fdaa963149a85a411cf573","observation_id":"4f0b0cd7-ea68-4e95-979a-37b7f21c6c16","resolution":{"observed_at":"2026-08-03T14:15:22.575365Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.579898Z","title":"Megaloc: One retrieval to place them all","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.579898Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:3eeb1c3c137d983044108962cafd804f1c5468953fcb055b02dbe22828571d1b","observation_id":"3425d02e-5263-4d29-b7f8-977a96be67fd","resolution":{"observed_at":"2026-08-03T14:15:22.579898Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.584263Z","title":"Re- thinking visual geo-localization for large-scale applications","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.584263Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:daf8a426b976aeb7f3fec7cc61bbf0deedc3efc98ff6395538f79023155886f1","observation_id":"aac23afe-7513-481b-9caa-fc8e376b5778","resolution":{"observed_at":"2026-08-03T14:15:22.584263Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.589884Z","title":"Eigenplaces: Training viewpoint robust models for visual place recognition","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.589884Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:e25b33bbd07a8ab17096487646eaa6d7962209ec1e80d75d3ad48ce27eb06c64","observation_id":"7f127217-4002-44bd-891a-10ee3d0a7054","resolution":{"observed_at":"2026-08-03T14:15:22.589884Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.594162Z","title":"Jist: Joint image and sequence training for sequential visual place recognition.IEEE Robotics and Au- tomation Letters, 9(2):1310–1317, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.594162Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:70105840039907504fa3a9eb9261a398e51a70cbe9f3cd2a59a78cb23fcd047b","observation_id":"ce2ba4e9-3bc4-4825-af08-c6234ccd70ca","resolution":{"observed_at":"2026-08-03T14:15:22.594162Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.598179Z","title":"A survey of optimal trans- port for computer graphics and computer vision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.598179Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:a88929c4d807155186b2dd8100efdfe750625b2f55876c1130642f4cc53ed862","observation_id":"259c61c6-a6ed-4fb0-bdae-05d01545ed9f","resolution":{"observed_at":"2026-08-03T14:15:22.598179Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.602455Z","title":"Learning context flexible attention model for long-term visual place recognition.IEEE Robotics and Au- tomation Letters, 3(4):4015–4022, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.602455Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:ddc3c0a658899ef6a0b4ffb31672cb0b70078d823f2765b3643ba7c07b879a10","observation_id":"9e747a3a-0062-4f54-a8b5-7debf74bc301","resolution":{"observed_at":"2026-08-03T14:15:22.602455Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.606673Z","title":"Sinkhorn distances: Lightspeed computation of optimal transport.Advances in neural information pro- cessing systems, 26, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.606673Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:94ca0188de42b78b3d95ff6436023a5f5a1dd79bbd87e3e3e30191a4d79a69de","observation_id":"8778babe-3ae6-4ac0-80dd-549d7a607b23","resolution":{"observed_at":"2026-08-03T14:15:22.606673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.08691","last_updated":"2023-07-17T17:50:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-17T17:50:36Z","title":"FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.08691","snapshot_observed_at":"2026-08-03T14:15:22.611120Z","title":"Flashattention-2: Faster attention with bet- ter parallelism and work partitioning.arXiv preprint arXiv:2307.08691, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.611120Z"},"links":{"cited_paper":"/paper/2307.08691","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:25510e53df35823c64a58e472b0a3dd14910dff8a827364123acb916d24e39b3","observation_id":"7385a17b-28d9-4a19-af35-8c822881f3dc","resolution":{"observed_at":"2026-08-03T14:15:22.611120Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.09076","last_updated":"2026-07-10T06:33:14Z","snapshot_observed_at":"2026-08-05T14:08:06.248024Z","submitted_at":"2023-12-14T16:11:42Z","title":"ProSGNeRF: Progressive Dynamic Neural Scene Graph with Frequency Modulated Foundation Model in Urban Scenes","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.09076","snapshot_observed_at":"2026-08-03T14:15:22.615745Z","title":"Prosgnerf: Progressive dynamic neural scene graph with frequency modulated auto-encoder in urban scenes.arXiv preprint arXiv:2312.09076, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.615745Z"},"links":{"cited_paper":"/paper/2312.09076","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:6249fbbaabf9953b199bfc4db613766988f06994e4af29568251b9265daf190a","observation_id":"022bc0f6-1b18-4299-aa85-0e682e40cd12","resolution":{"observed_at":"2026-08-03T14:15:22.615745Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.620615Z","title":"Long-term visual simultaneous localization and map- ping: Using a bayesian persistence filter-based global map prediction.IEEE Robotics & Automation Magazine, 30(1): 36–49, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.620615Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:bb102494120b73e26abea0e956b6c448144a698b2c2f98331f4e8948485d892c","observation_id":"16ecbbb7-50fc-4dd2-89ee-b3a3e4486bbc","resolution":{"observed_at":"2026-08-03T14:15:22.620615Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.624772Z","title":"Plgslam: Progressive neural scene represenation with local to global bundle adjustment","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.624772Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:6797ffb1c2e5858aa98d09bb878b4a018749b70775b96354d43c94abe6b04380","observation_id":"a616ff07-7af2-4328-9bd7-af9fb157c313","resolution":{"observed_at":"2026-08-03T14:15:22.624772Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.629016Z","title":"What is the best 3d scene representation for robotics? from geometric to foundation models.arXiv preprint arXiv:2512.03422, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.629016Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:c09b1124276fa02433a69fae95a9e717fee9036c36e420d05fcfb95c632b5e37","observation_id":"a910484a-41b0-4017-8853-1b7a081db8fc","resolution":{"observed_at":"2026-08-03T14:15:22.629016Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.18678","last_updated":"2025-08-19T06:02:44Z","snapshot_observed_at":"2026-07-06T21:46:20.835997Z","submitted_at":"2025-06-23T14:22:29Z","title":"MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.18678","snapshot_observed_at":"2026-08-03T14:15:22.633108Z","title":"Mcn-slam: Multi-agent collaborative neural slam with hybrid implicit neural scene representation.arXiv preprint arXiv:2506.18678, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.633108Z"},"links":{"cited_paper":"/paper/2506.18678","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:6d090fa52ddf978ab87a2dc0568b10694c345c6f7fd8c98132c4c6963c1f8b55","observation_id":"40ad5ce8-8da8-4202-a7b5-3eef5cc4e9a7","resolution":{"observed_at":"2026-08-03T14:15:22.633108Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.637989Z","title":"Mne-slam: Multi-agent neural slam for mobile robots","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.637989Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:c24a7bdeef07e616e8312e4a720f77b3ff736d9627a319eaa7f9c7351a1d32ad","observation_id":"829f867c-0c31-46bd-b087-3c54515eadc5","resolution":{"observed_at":"2026-08-03T14:15:22.637989Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.642336Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.642336Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:98205deaacd4b037e20874fab0abea1883751687f62dc5f20b06ca6cb71fd9d4","observation_id":"a9525291-eda2-428e-960b-33ad1015611a","resolution":{"observed_at":"2026-08-03T14:15:22.642336Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.646387Z","title":"Neslam: Neural implicit mapping and self-supervised feature tracking with depth completion and denoising.IEEE Transactions on Automation Science and Engineering, pages 1–1, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.646387Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:8104fe66eb2f1b6688f49a9c40844877795a5b8d7587970b69b399d827b92cdf","observation_id":"368d217e-b4d1-4cd1-8310-e44991adf812","resolution":{"observed_at":"2026-08-03T14:15:22.646387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.09516","last_updated":"2019-02-25T18:56:55Z","snapshot_observed_at":"2026-08-04T08:36:21.595551Z","submitted_at":"2019-02-25T18:56:55Z","title":"Condition-Invariant Multi-View Place Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.09516","snapshot_observed_at":"2026-08-03T14:15:22.651359Z","title":"Condition-invariant multi-view place recognition","venue":null,"work_id":null,"year":1902},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.651359Z"},"links":{"cited_paper":"/paper/1902.09516","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:e15cb7c30afabf858eb81497f818f9de877d13d62f35b110dd8c80dce16140bf","observation_id":"94371a0f-f717-4518-a0e0-b4b175e9b9d4","resolution":{"observed_at":"2026-08-03T14:15:22.651359Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.655846Z","title":"Bags of binary words for fast place recognition in image sequences.IEEE Transactions on robotics, 28(5):1188–1197, 2012","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.655846Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:205c40504f4eccfbaa27f42d8a40364b625edfd1247bbe0c11bc9e280b4c4e7e","observation_id":"1a2b0f72-3a66-4d11-866f-1684a0bc9f40","resolution":{"observed_at":"2026-08-03T14:15:22.655846Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.660364Z","title":"Seqnet: Learning de- scriptors for sequence-based hierarchical place recognition","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.660364Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:079627886b51e05ccbbc6090ab4347033695f8a6d08b2e4e40ff56f0abb626fc","observation_id":"2b467914-a743-4f24-99e0-41e57c324ae3","resolution":{"observed_at":"2026-08-03T14:15:22.660364Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.664883Z","title":"Delta descriptors: Change-based place representa- tion for robust visual localization.IEEE Robotics and Au- tomation Letters, 5(4):5120–5127, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.664883Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:5f9ef8d15c39f6a2450e2442a19bb575cffd8d6ee747fe110983a94585e6879e","observation_id":"d8467d99-d6fe-4d6b-951f-209f73a61c40","resolution":{"observed_at":"2026-08-03T14:15:22.664883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.06443","last_updated":"2021-11-09T04:10:53Z","snapshot_observed_at":"2026-08-04T20:26:17.064131Z","submitted_at":"2021-03-11T04:11:04Z","title":"Where is your place, Visual Place Recognition?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.06443","snapshot_observed_at":"2026-08-03T14:15:22.669800Z","title":"Where is your place, visual place recognition?arXiv preprint arXiv:2103.06443, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.669800Z"},"links":{"cited_paper":"/paper/2103.06443","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:50f53445dfd75afa6fa0817a6e8f3d1a15f71c32e8371b896d0423c91c4a29ab","observation_id":"0105062f-4821-4319-847a-96c543effaef","resolution":{"observed_at":"2026-08-03T14:15:22.669800Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.674962Z","title":"Seq- matchnet: Contrastive learning with sequence matching for 18 place recognition & relocalization","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.674962Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:32302c3f4dda8944dd371c274c9f3e1955381bf5f23018f2b345a9f3845a2106","observation_id":"3f4775d2-a056-40f2-8046-52a1994f0940","resolution":{"observed_at":"2026-08-03T14:15:22.674962Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.679586Z","title":"Patch-netvlad: Multi-scale fusion of locally-global descriptors for place recognition","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.679586Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:9c3ee604b76f137ee0eca26df5c8a89c7e3274f2384fd5771190a184e8a709c5","observation_id":"873c38b8-a276-4db0-aefd-72f350c0d16d","resolution":{"observed_at":"2026-08-03T14:15:22.679586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06840","last_updated":"2025-07-29T04:18:56Z","snapshot_observed_at":"2026-08-05T06:36:27.462463Z","submitted_at":"2025-03-10T02:01:24Z","title":"Improving Visual Place Recognition with Sequence-Matching Receptiveness Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06840","snapshot_observed_at":"2026-08-03T14:15:22.684549Z","title":"Improving visual place recognition with sequence-matching receptiveness prediction.arXiv preprint arXiv:2503.06840,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.684549Z"},"links":{"cited_paper":"/paper/2503.06840","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:b4d772dfec93134e7937d8dda38ec65411165f460a58271a6c4dbeda48d46bc8","observation_id":"c6fb26cd-4325-4b4e-aab5-afe9ad78960a","resolution":{"observed_at":"2026-08-03T14:15:22.684549Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.689752Z","title":"Close, but not there: Boosting geographic distance sensitivity in visual place recognition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.689752Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:5e0d12cd29452eba58730c91ddf805fc78ad5390b8fc5996d73400550d35d395","observation_id":"6450418b-948b-4221-adc9-5c81b5b94abd","resolution":{"observed_at":"2026-08-03T14:15:22.689752Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.697920Z","title":"Optimal transport ag- gregation for visual place recognition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.697920Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:ca86362a8e5a764839b6c91e65476ecbbaae92d5ed23cefe561278e33d2f2424","observation_id":"df3c1db2-1917-44df-984c-92f964544680","resolution":{"observed_at":"2026-08-03T14:15:22.697920Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.702583Z","title":"Aggregating local descriptors into a compact image representation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.702583Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:d216545f4c321aed95e88ca8898051feb75ff6613139edaf63f35d5b994043a4","observation_id":"156d902d-3399-480d-b592-64e79e224196","resolution":{"observed_at":"2026-08-03T14:15:22.702583Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.707094Z","title":"Anyloc: Towards universal visual place recognition.IEEE Robotics and Automation Letters, 9 (2):1286–1293, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.707094Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:476ee2afd05789d5e7d4c012b3f19a02556f019cff1b4f902580720386bab6e4","observation_id":"8fc88211-7b75-4983-8b81-803479b5d728","resolution":{"observed_at":"2026-08-03T14:15:22.707094Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.711348Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.711348Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:1ff527a7d17182d0a84c3baa3a2e2e07ee72dce8691411384cfd057ef2942e9a","observation_id":"ea1e1b1f-1db2-44f7-992b-383f878dda29","resolution":{"observed_at":"2026-08-03T14:15:22.711348Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.715305Z","title":"Casevpr: Correlation-aware sequential embedding for sequence-to-frame visual place recognition.IEEE Robotics and Automation Letters, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.715305Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:084c77b2ae802ade5011c760897280eb99523da8e6d12f056c033cd4df234bfd","observation_id":"391e71bb-1e06-49bd-ad97-5527cddf7aeb","resolution":{"observed_at":"2026-08-03T14:15:22.715305Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.719604Z","title":"To- ward learning-based visuomotor navigation with neural radi- ance fields.IEEE Transactions on Industrial Informatics, 20 (6):8907–8916, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.719604Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:2874765e5f10b1e5f88f5cfb9fbb425a6fb408ee94ceec555934d3d728d7c017","observation_id":"3615750e-9bfb-4b5b-81bd-d1270107235f","resolution":{"observed_at":"2026-08-03T14:15:22.719604Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.723632Z","title":"In- tegrating neural radiance fields end-to-end for cognitive vi- suomotor navigation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(12):11200–11215, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.723632Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:ab50518791afb5bb5d763756356591dcb8afc0de30ab2517d228f3a857bcd279","observation_id":"c1cfa0e5-1f2c-48c5-a8b8-064417719a97","resolution":{"observed_at":"2026-08-03T14:15:22.723632Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.727640Z","title":"Mg-slam: Structure gaussian splatting slam with manhattan world hy- pothesis.IEEE Transactions on Automation Science and En- gineering, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.727640Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:0565050349a67a688aba22212a62e9471f49a5411c26c452e947b77ccd2bc625","observation_id":"f2bd9be4-8e32-45c0-aad0-d6412a0bbb60","resolution":{"observed_at":"2026-08-03T14:15:22.727640Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.731730Z","title":"Visual place recognition: A survey.IEEE Transactions on Robotics, 32(1):1–19, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.731730Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:6ea7ee06c636faf3f61c9359f40146ffc0fa47e6918fd63f817b46bbdbb276f9","observation_id":"265e0096-6206-4efd-bc03-58f731f3f305","resolution":{"observed_at":"2026-08-03T14:15:22.731730Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.736228Z","title":"Neural network-based nonconservative predefined-time backstep- ping control for uncertain strict-feedback nonlinear systems","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.736228Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:0f36648af1ecd218116f48a051139e823a667aca9844d3e08c6ab16acf22cb3e","observation_id":"c65107bc-d896-4cfd-a8f1-78e15ec7b84c","resolution":{"observed_at":"2026-08-03T14:15:22.736228Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.740241Z","title":"Adaptive dis- tributed observer design for nonlinear multiagent systems","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.740241Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:2a8bb456d82d7afdc1a6d70ec70202a9cdca25dde5f116408a96c98d822dcba5","observation_id":"9c83a54f-4309-4598-8e83-fd07e8bd312c","resolution":{"observed_at":"2026-08-03T14:15:22.740241Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.744263Z","title":"1 year, 1000 km: The oxford robotcar dataset","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.744263Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:3e7cca060f462525f9d0bf3ab772d5c1156e7d048a20fee5a6322530b96158c0","observation_id":"6bcab254-b8ad-4cdc-b99a-6f9c9e458f78","resolution":{"observed_at":"2026-08-03T14:15:22.744263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.12549","last_updated":"2025-05-23T11:59:20Z","snapshot_observed_at":"2026-07-06T21:25:56.796553Z","submitted_at":"2025-05-18T21:33:09Z","title":"VGGT-SLAM: Dense RGB SLAM Optimized on the SL(4) Manifold","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.12549","snapshot_observed_at":"2026-08-03T14:15:22.748747Z","title":"Vggt- slam: Dense rgb slam optimized on the sl (4) manifold.arXiv preprint arXiv:2505.12549, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.748747Z"},"links":{"cited_paper":"/paper/2505.12549","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:8a4dc9bc99762611f0e21ea099ea112e159896f202157869212a65dd1af11e85","observation_id":"442943a0-967c-41fe-b632-24c89e942b72","resolution":{"observed_at":"2026-08-03T14:15:22.748747Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.752883Z","title":"A survey on deep visual place recognition.IEEE Access, 9:19516–19547, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.752883Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:1af586f00e4319ee9003d9975e962f892994dee9a133366847eee47cbb1e8398","observation_id":"694d206e-1892-4bc5-a370-f1f65a16ad0b","resolution":{"observed_at":"2026-08-03T14:15:22.752883Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.757245Z","title":"Learning sequential descrip- tors for sequence-based visual place recognition.IEEE Robotics and Automation Letters, 7(4):10383–10390, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.757245Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:a5ae8240a9871fad0dc29f37debdc822684b6bc61a4f4e3727b1e3b31e2e9dd3","observation_id":"f0652b14-5323-4784-b994-faa6a60b88d6","resolution":{"observed_at":"2026-08-03T14:15:22.757245Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.761387Z","title":"Going places: Place recognition in artificial and natural systems.Annual Review of Control, Robotics, and Autonomous Systems, 9, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.761387Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:4ead494d5ed39fe00d8adb03ecf1a7a832939f67466943ac59cbae1bff03c5a5","observation_id":"e8b08937-8766-4e1e-9ff9-f19cc867792f","resolution":{"observed_at":"2026-08-03T14:15:22.761387Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.765569Z","title":"Seqslam: Visual route-based navigation for sunny summer days and stormy winter nights","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.765569Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:acf8d0d91f293d038364b8cc327c389bfa07feeb4a7db90e13ca4bfb545640a1","observation_id":"1e6b3eae-6fb8-4358-8523-6c62e3233937","resolution":{"observed_at":"2026-08-03T14:15:22.765569Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.769716Z","title":"Localization in urban environments using a panoramic gist descriptor.IEEE Transactions on Robotics, 29(1):146–160, 2012","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.769716Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:c3c02965249b8b1a964150d56217d2d28c52bafbf1d67e73b149ebe1ef5d8c5a","observation_id":"d77fc0df-da53-4ebb-8c75-15f4340401ce","resolution":{"observed_at":"2026-08-03T14:15:22.769716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-03T14:15:22.774215Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.774215Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:cb61635da082613a33d8d57fb1f16c8aaaeea08bde5627d21297e4b14f09717b","observation_id":"799f927f-8868-4a55-a576-c62b14a010d1","resolution":{"observed_at":"2026-08-03T14:15:22.774215Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.778469Z","title":"Fine- tuning cnn image retrieval with no human annotation.IEEE transactions on pattern analysis and machine intelligence, 41(7):1655–1668, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.778469Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:161f6fed7f9fab88f9073f222a173b4075c3e6e22c832427e98266841eae943a","observation_id":"089da0a0-47d9-4cc4-8d2d-5556765ed02e","resolution":{"observed_at":"2026-08-03T14:15:22.778469Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.782610Z","title":"From coarse to fine: Robust hierarchical localization at large scale","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.782610Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:d6baa8dc32e5d0fa2ff88f7057e1c39d214402a6c635a57c089b97088999eb1d","observation_id":"6a63d1fb-7f22-4f5a-bd03-196b45786169","resolution":{"observed_at":"2026-08-03T14:15:22.782610Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.787514Z","title":"Superglue: Learning feature matching with graph neural networks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.787514Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:636c80a12cf043215285ce9763bc0f4f095696f90aa9793f3f1bce7f9a193c7c","observation_id":"ae19dcc8-3091-48d9-875c-b6f025017242","resolution":{"observed_at":"2026-08-03T14:15:22.787514Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.792583Z","title":"Fast and memory efficient graph optimization via icm for visual place recognition","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.792583Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:d571c2477b36473de15ff2b97bc06ba4b6ea94b42816edea6d908e759fe95959","observation_id":"661cdebb-9481-43f4-8447-72967e74a2b5","resolution":{"observed_at":"2026-08-03T14:15:22.792583Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.796824Z","title":"Visual Place Recognition: A Tuto- rial.IEEE Robotics & Automation Magazine, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.796824Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:e7d13b6280c041afd49f7f71aaf71c9ad2192ab65948cdb8d8765d1273d9aa21","observation_id":"0fc5a780-c197-407d-a437-4588a82bdb03","resolution":{"observed_at":"2026-08-03T14:15:22.796824Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.800934Z","title":"Grs-slam3r: Real-time dense slam with gated recurrent state.arXiv preprint arXiv:2509.23737, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.800934Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:6cbc43ce6b9b3c1773085c9b28cfd1a68e82bd22ca9b10091d1ecc2cec3f4fb4","observation_id":"456b3886-8a5a-4189-a8d8-13595c31e4ee","resolution":{"observed_at":"2026-08-03T14:15:22.800934Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.804967Z","title":"Unilgl: Learning uniform place recognition for fov- limited/panoramic lidar global localization.arXiv preprint arXiv:2507.12194, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.804967Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:dbf0d6b9eae1f51645e1b15fbc195913dee9eb751d68bbd337eb0b9ce0e9cae8","observation_id":"5b870b2b-25dd-489a-b08e-8f650bc63720","resolution":{"observed_at":"2026-08-03T14:15:22.804967Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.809005Z","title":"Video google: A text retrieval approach to object matching in videos","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.809005Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:10d1e8c3fc429b09da399df8be4909a02d38876a278254a9769bbf14312af754","observation_id":"e0ea6854-198d-4058-9d10-c5583c87a3a5","resolution":{"observed_at":"2026-08-03T14:15:22.809005Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.814016Z","title":"Brief-gist-closing the loop by simple means","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.814016Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:28a7deff5ef75fe0156bad4e2288ee55ef10a5c19948dd5be02d099b2660cb65","observation_id":"511f9eb5-4982-4414-9ac1-f4d327d20a12","resolution":{"observed_at":"2026-08-03T14:15:22.814016Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.818383Z","title":"Are we there yet? challenging seqslam on a 3000 km journey across all four seasons","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.818383Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:f01c1ecb223cae83a0242224a5d6c4a83c1fdafb64dc43fc750abe4adbaa58c2","observation_id":"8ef9d422-2f6c-4be7-8485-0878fb6ce062","resolution":{"observed_at":"2026-08-03T14:15:22.818383Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.822656Z","title":"Inloc: Indoor visual localization with dense matching and view synthesis","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.822656Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:92cb10c3f32299336fd1df180474f7ecddc719fd9f2e42079536c410a8feaa2a","observation_id":"3e379cae-71cc-480d-92a0-0d1d19e3e110","resolution":{"observed_at":"2026-08-03T14:15:22.822656Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.826966Z","title":"Visual place recognition with repetitive structures","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.826966Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:f7c885c7bc09cb3aace39111beb0243bfcb4261cb9c1f72fbab5556419012eb2","observation_id":"e47fab49-bdf2-4fbd-8e91-d893a526cb06","resolution":{"observed_at":"2026-08-03T14:15:22.826966Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.830965Z","title":"Vggt: Vi- sual geometry grounded transformer","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.830965Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:6e104534ecb56c76b5b6eb2973f6ec64bb06001aced699ffd7d6e3193bfc224b","observation_id":"282bc040-3df9-4a94-9fd1-c35f2e09d768","resolution":{"observed_at":"2026-08-03T14:15:22.830965Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.834998Z","title":"Transvpr: Transformer-based place recognition with multi-level attention aggregation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.834998Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:2644521f45ef338c833b5b9e207c84a80af7978dc55594159c454242d8f2f5a3","observation_id":"a689dca0-8c95-4a5b-bd6d-44cd26d90f29","resolution":{"observed_at":"2026-08-03T14:15:22.834998Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.839441Z","title":"Multi-similarity loss with general pair weighting for deep metric learning","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.839441Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:95be29e1a9b08376cae9b3ed493f70a71d3504b815c388e185db63af93ceaa88","observation_id":"58038de4-f0d5-4d16-b3ef-9dbf46dc0c2e","resolution":{"observed_at":"2026-08-03T14:15:22.839441Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.843803Z","title":"Sfpnet: Sparse fo- cal point network for semantic segmentation on general lidar point clouds","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.843803Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:dd60fa5c0ec3e0bdf1d28cb8e5421687a30702fa4fa1704cc9a705262e446150","observation_id":"18ddb16a-0071-4aab-af4a-315bde7536ae","resolution":{"observed_at":"2026-08-03T14:15:22.843803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.11001","last_updated":"2025-07-15T05:37:24Z","snapshot_observed_at":"2026-07-06T21:57:22.011378Z","submitted_at":"2025-07-15T05:37:24Z","title":"Learning to Tune Like an Expert: Interpretable and Scene-Aware Navigation via MLLM Reasoning and CVAE-Based Adaptation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.11001","snapshot_observed_at":"2026-08-03T14:15:22.848771Z","title":"Learning to tune like an expert: Interpretable and scene- aware navigation via mllm reasoning and cvae-based adapta- tion.arXiv preprint arXiv:2507.11001, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.848771Z"},"links":{"cited_paper":"/paper/2507.11001","citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:3aa35d2b8e4e034122d1a45e2317adc2171f1127218bb069efff6cf4358bcf5d","observation_id":"092d156f-85c0-4cef-8ccb-5ee12c017932","resolution":{"observed_at":"2026-08-03T14:15:22.848771Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.853584Z","title":"Mapillary street-level sequences: A dataset for lifelong place recognition","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.853584Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:1a313817f48a6adc90b63ef3f72e1a93d7a68c637d94ee86d23ce442d9509b7d","observation_id":"96f95255-df0b-469f-9a00-82d77e571b9b","resolution":{"observed_at":"2026-08-03T14:15:22.853584Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.857654Z","title":"Stgcnformer: Spatio-temporal dual-stream graph convolutional networks and transformers for traffic forecasting.IEEE Transactions on Vehicular Technology, 74(10):15254–15263, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.857654Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:cf47fb944b1d303baef5904a9a73d26d3aa9b4011340995d62f066328d0bbaa2","observation_id":"dc44905f-7474-4358-b099-68e0e0275d88","resolution":{"observed_at":"2026-08-03T14:15:22.857654Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.862584Z","title":"Trajdiff: Trajectory prediction with diffusion probabilistic models.IEEE Transactions on Image Processing, pages 1– 14, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.862584Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:285972af0c738c1dab25bb77a879f4b950efdca5371a1e7189a9af214b1c0f9a","observation_id":"c288f125-434e-4a3a-b73f-1516155d4bdf","resolution":{"observed_at":"2026-08-03T14:15:22.862584Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.867070Z","title":"Visual place recog- nition: A survey from deep learning perspective.Pattern Recognition, 113:107760, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.867070Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:583587a6d14d45da7f08f05eada9546cee9bdb5c69aa41c975116ef1710060fa","observation_id":"ac272450-f151-4d4e-94bc-2b215ecebb5e","resolution":{"observed_at":"2026-08-03T14:15:22.867070Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.871451Z","title":"Learning sequence descriptor based on spatio-temporal attention for visual place recognition.IEEE Robotics and Automation Let- ters, 9(3):2351–2358, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.871451Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:3665cbc99e14c641693c07eaf938bd9f37c260c51d46bb9551228b63f1f4b1c7","observation_id":"f5cc252b-4c76-433f-92d0-b5676edfddb5","resolution":{"observed_at":"2026-08-03T14:15:22.871451Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.876320Z","title":"The nerfect match: Exploring nerf features for visual localization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.876320Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:09cc0c0f5cce9b3ed06cf47f89a9e437eea591826b3369775da2bbd7f83f394b","observation_id":"914b6d9c-ac1c-4778-9205-9c5137cb60be","resolution":{"observed_at":"2026-08-03T14:15:22.876320Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T14:15:22.880265Z","title":"R2former: Unified retrieval and reranking transformer for place recognition","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer","version":3},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-03T14:15:22.880265Z"},"links":{"citing_paper":"/paper/2512.21078"},"observation_digest":"sha256:dfbd58e07fd6e9db5e445fbbbf1f1db13a4e1b045f063a779486a9eec9b310f8","observation_id":"bb9852a5-2b05-46a6-a650-4e048c0acf64","resolution":{"observed_at":"2026-08-03T14:15:22.880265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2512.21078","last_updated":"2026-06-29T16:02:29Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-04T02:44:13.278161Z","submitted_at":"2025-12-24T09:55:16Z","title":"UniPR-3D: Towards Universal Visual Place Recognition with Visual Geometry Grounded Transformer"},"reference_resolution":{"displayed":72,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":72,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":72},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 4 inbound Pith citation observations for arXiv:2512.21078."}