{"as_of":"2026-08-21T00:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fd992647f972d3caa4898882d7022899233788bdfd4bf049df5b958d8330b9ed","coverage":[{"denominator":83,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":83,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T13:27:19.380528Z","state":"measured"},{"denominator":83,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":83,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.19120/citation-record","integrity":"/paper/2607.19120/integrity","json":"/paper/2607.19120/citation-record.json","paper":"/paper/2607.19120"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T13:27:12.245052Z","title":"In: Proceedings of the IEEE/CVF international conference on computer vision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.245052Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:2086e01bc5e1b29241f698748d2b233004a39332af5216579696d69e0fa51231","observation_id":"fb201c52-ea36-45a7-8e3e-6fe8e1f187c5","resolution":{"observed_at":"2026-08-01T13:27:12.245052Z","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":"2026-08-01T13:27:12.333515Z","title":"In: The Twelfth International Conference on Learning Representations (2024) 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.333515Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:9a613905f29d72014068ceea1b6fb867f10305eaf66263a5592cebf7fca263fc","observation_id":"12423731-1065-48e2-afe8-fa11b1536771","resolution":{"observed_at":"2026-08-01T13:27:12.333515Z","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":"2026-08-01T13:27:12.431559Z","title":"Cambridge University Press (2023) 18","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.431559Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:0f2bb0041744c596ce7f2e63f17b1a55dc3b98254105c9349475f4d4e56f6727","observation_id":"55d8782a-94fc-4f35-9f19-bf111ed47ee9","resolution":{"observed_at":"2026-08-01T13:27:12.431559Z","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":"2026-08-01T13:27:12.502881Z","title":"arXiv preprint arXiv:2506.07198 (2025) 4","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.502881Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:438aa4a0fd26af4a1015c8e80535d6a27992a69b71286ffb69d55332538b80de","observation_id":"c7cb767e-5534-4e50-af1c-d23e2dd14d7d","resolution":{"observed_at":"2026-08-01T13:27:12.502881Z","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":"2026-08-01T13:27:12.557905Z","title":"In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.557905Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:3eb70b5d6bc49812a8024bef150c34c29560c4a78585624dc128a65e6b0365ed","observation_id":"0ab951be-4013-4dbb-aeca-692fa7f248e9","resolution":{"observed_at":"2026-08-01T13:27:12.557905Z","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":"2026-08-01T13:27:12.623347Z","title":"In: Proceedings of the IEEE/CVF international conference on computer vision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.623347Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:7a31a6509c991bb3ef5c8cb48ea93f2cbf2dd381c4dc353100350f310c26a50d","observation_id":"c37c646b-0641-4f36-908a-8a4b064b1173","resolution":{"observed_at":"2026-08-01T13:27:12.623347Z","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":"2026-08-01T13:27:12.691073Z","title":"In: The Twelfth International Conference on Learning Representations (2024) 2, 4, 17","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.691073Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:5c028cde2480d34c4f7633eaaea766112651a70f90a3834903b930536597a48d","observation_id":"141077cd-a5e8-45f1-a3f8-4f9c6a48d045","resolution":{"observed_at":"2026-08-01T13:27:12.691073Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.10981","last_updated":"2026-06-16T07:00:04Z","snapshot_observed_at":"2026-08-13T09:07:05.908102Z","submitted_at":"2025-06-12T17:59:56Z","title":"SceneCompleter: Dense 3D Scene Completion for Generative Novel View Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.10981","snapshot_observed_at":"2026-08-01T13:27:12.758528Z","title":"arXiv preprint arXiv:2506.10981 (2025) 2, 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.758528Z"},"links":{"cited_paper":"/paper/2506.10981","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:8cce5d7774ad35c502d568adbab0fecf2929b3e4aad39ce65454891fecd8c570","observation_id":"ea62818c-a145-4325-b7c5-8e62815781cb","resolution":{"observed_at":"2026-08-01T13:27:12.758528Z","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":"2026-08-01T13:27:12.822249Z","title":"In: European conference on computer vision","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.822249Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:22ff833a9933777235787b199c208a8c4e71bffbdd5e884c7943cc00ef492f3a","observation_id":"d848884c-dfd8-4804-a639-f1387262a531","resolution":{"observed_at":"2026-08-01T13:27:12.822249Z","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":"2026-08-01T13:27:12.892884Z","title":"In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.892884Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:52340581c2b3f21e6d208c731bd7b4432408be7306e210531d4f6a284d075625","observation_id":"b6620afc-7028-4a41-b59c-64c1f8e726ac","resolution":{"observed_at":"2026-08-01T13:27:12.892884Z","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":"2026-08-01T13:27:12.965132Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:12.965132Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:86ccbdc361a1b5de2b30f093276b232b40a7f6d3a765e534e0b48b67ad2f5cab","observation_id":"84ceb504-b92a-4fb8-b394-7aa77b0b32f3","resolution":{"observed_at":"2026-08-01T13:27:12.965132Z","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":"2026-08-01T13:27:13.045576Z","title":"In: Proceedings of the IEEE/CVF International Conference on Computer Vision","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.045576Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:a8f0c04c4dd8b6920174f35c93e98ad931a36fd3ff698bd91dba510366e273cd","observation_id":"3364ee49-03db-493d-85d8-7863a8b39a66","resolution":{"observed_at":"2026-08-01T13:27:13.045576Z","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":"2026-08-01T13:27:13.097569Z","title":"arXiv preprint arXiv:2510.14586 (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.097569Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:18937d623202b91690c7cef8e31f92256f0cb6868b5b369afe0b11be5a97db31","observation_id":"79017376-a7f8-44e5-8f2d-4b29270294d5","resolution":{"observed_at":"2026-08-01T13:27:13.097569Z","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":"2026-08-01T13:27:13.145745Z","title":"Advances in Neural Information Processing Systems (2024) 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.145745Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:aced6f9388ea1f8356825f75f1637c76398de823f05da52dcbbb1eff390cd21e","observation_id":"7f8482dd-0a1a-4f80-ab0d-a942657ce806","resolution":{"observed_at":"2026-08-01T13:27:13.145745Z","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":"2026-08-01T13:27:13.212199Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.212199Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:c3e38467d7471adf8d0c9f52f3cdda633113afc80109be1c70fa60b00179d09c","observation_id":"59886e27-6fcd-4f4e-89d6-ac268e79b5ed","resolution":{"observed_at":"2026-08-01T13:27:13.212199Z","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":"2026-08-01T13:27:13.261447Z","title":"Advances in neural information processing systems30(2017) 7","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.261447Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:cc0f96367697fe93bf703a85c59a0ab9a6957cfb968597a846e17df338c4af60","observation_id":"4eafb7f0-de77-4cea-9b84-ba89890b8ea8","resolution":{"observed_at":"2026-08-01T13:27:13.261447Z","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":"2026-08-01T13:27:13.306404Z","title":"In: ACM SIGGRAPH 2024 conference papers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.306404Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:ce2683cd073cd6ee86811dc6e00349e23a259441195bba43cc999bfef0231071","observation_id":"367af4ad-fbe3-4971-9dad-d147f1c914e1","resolution":{"observed_at":"2026-08-01T13:27:13.306404Z","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":"2026-08-01T13:27:13.363229Z","title":"arXiv preprint arXiv:2601.04090 (2026) 2, 3, 6, 7, 19 12","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.363229Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:dfb3aebfbcfd8bbfb89e623b0bdb2d172aab90189dd99287f7f16af61c5b4936","observation_id":"c6423a54-939a-4fde-a791-84cf189f4ded","resolution":{"observed_at":"2026-08-01T13:27:13.363229Z","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":"2026-08-01T13:27:13.426658Z","title":"Advances in neural information processing systems37, 33007–33036 (2024) 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.426658Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:42e60f1a161a13a3c54d901ccb243da68f6b283c462f70e52f348666f625d115","observation_id":"e6ec5612-5a0b-478d-bee5-4ca043555539","resolution":{"observed_at":"2026-08-01T13:27:13.426658Z","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":"2026-08-01T13:27:13.480067Z","title":"In: Proceedings of the IEEE/CVF international conference on computer vision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.480067Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:32139fb156cf0cdaf45e16e96b6b2df4ae05caac05315550ac70fe6be56d7a0a","observation_id":"587a33a5-33a8-4897-8ed8-f514a23fdcda","resolution":{"observed_at":"2026-08-01T13:27:13.480067Z","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":"2026-08-01T13:27:13.536828Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog- nition (CVPR)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.536828Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:ed360e33bd7426bd926a2a52e1ae361449838a6b8d77934fdfd3842bc50c631a","observation_id":"0f39674d-a796-48e7-9260-dd8923b86833","resolution":{"observed_at":"2026-08-01T13:27:13.536828Z","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":"2026-08-01T13:27:13.586753Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.586753Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:42c2643f2e05989a5c2c8cbacfa27447d3a31e19b53cdc1fd34c601c36e6f01a","observation_id":"cfe89762-4771-4c9c-a302-43d5ca8da097","resolution":{"observed_at":"2026-08-01T13:27:13.586753Z","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":"2026-08-01T13:27:13.648442Z","title":"arXiv preprint arXiv:2603.22275 (2026) 3","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.648442Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:f89275706738023388a039a50bfa6c5f58ed249920eaadebd71ae7b6b9030196","observation_id":"78c1badf-1cfd-46f1-8012-fbaea510b331","resolution":{"observed_at":"2026-08-01T13:27:13.648442Z","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":"2026-08-01T13:27:13.704457Z","title":"In: The Thirteenth Interna- tional Conference on Learning Representations (2025),https://openreview.net/forum? id=QQBPWtvtcn1, 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.704457Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:e4aa63dfe699055e454cdfc66b8445b665c2060cece025b2b7402729ee12d7fc","observation_id":"3209298c-1c17-44ef-9426-056c845c2408","resolution":{"observed_at":"2026-08-01T13:27:13.704457Z","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":"2026-08-01T13:27:13.760566Z","title":"ACM Trans","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.760566Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:84e2b3589a2b6bf63ca0c8bcd812bfeb75b0ac65211b7a8e0cf3fc9e42f7a515","observation_id":"46e2d593-f56d-48d7-9641-0a9410abf6d7","resolution":{"observed_at":"2026-08-01T13:27:13.760566Z","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":"2026-08-01T13:27:13.847886Z","title":"In: arXiv preprint arXiv:2602.21341 (2026) 1, 3","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.847886Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:f52c32348cf72341757d10750cc217f93a5bf8e6f6d861a9b09c03bdf6d0ff16","observation_id":"038f0c4c-2284-4b7e-b24c-ac283cd776e2","resolution":{"observed_at":"2026-08-01T13:27:13.847886Z","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":"2026-08-01T13:27:13.929523Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:13.929523Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:1e0824f88d2567b40786811fb14847e52929783b1251905a1c6e8ac035b81f42","observation_id":"87542e9b-d4f5-44b7-ba75-03c152e59ad6","resolution":{"observed_at":"2026-08-01T13:27:13.929523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17270","last_updated":"2025-03-19T06:42:21Z","snapshot_observed_at":"2026-08-20T13:13:36.545144Z","submitted_at":"2024-10-07T13:51:58Z","title":"MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.17270","snapshot_observed_at":"2026-08-01T13:27:14.008356Z","title":"arXiv preprint arXiv:2410.17270 (2024) 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.008356Z"},"links":{"cited_paper":"/paper/2410.17270","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:9dd2a42eae5c9f5cea91ed46896100f238f51b61c115dfa4d175bc8e9c65b302","observation_id":"4d474327-591a-4163-a3e2-a2e970190edb","resolution":{"observed_at":"2026-08-01T13:27:14.008356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-01T13:27:14.110454Z","title":"arXiv preprint arXiv:1412.6980 (2014) 7","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.110454Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:2a1e05aed5c9e2f96ef306e06f21c8f442aebe528edc10d71a9f8231d6b055a4","observation_id":"524488b6-1c27-4c2c-9d55-0518ba623a12","resolution":{"observed_at":"2026-08-01T13:27:14.110454Z","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":"2026-08-01T13:27:14.121905Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.121905Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:bfa03e73acdcda05420ec3a4744c1d7c487100ce6aa3153ae1e5013b4bc92d4e","observation_id":"3c56bcca-55e3-4c36-ae98-af7697be6c6c","resolution":{"observed_at":"2026-08-01T13:27:14.121905Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.10099","last_updated":"2026-07-03T15:19:24Z","snapshot_observed_at":"2026-08-17T13:12:50.611733Z","submitted_at":"2026-02-10T18:58:04Z","title":"Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.10099","snapshot_observed_at":"2026-08-01T13:27:14.205124Z","title":"arXiv preprint arXiv:2602.10099 (2026) 2, 3, 4, 5","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.205124Z"},"links":{"cited_paper":"/paper/2602.10099","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:cf24d5b8485ea0904cc5d01dbad2e691d6c0575f4e4ba7d94292337a3d2586ea","observation_id":"88c9440e-8d78-49ac-bb48-08962577f69a","resolution":{"observed_at":"2026-08-01T13:27:14.205124Z","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":"2026-08-01T13:27:14.359005Z","title":"In: Proceed- ings of the European Conference on Computer Vision (2024) 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.359005Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:1d8d220d02906e405bc10b006bc0162a5eef13060649b0258270ed296cdc8188","observation_id":"675ce60a-0cc5-4f38-9c19-815cb043bf61","resolution":{"observed_at":"2026-08-01T13:27:14.359005Z","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":"2026-08-01T13:27:14.516714Z","title":"arXiv preprint arXiv:2507.10496 (2025) 6","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.516714Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:6b4f8a6ff0aa99a656145183f068d755ba53ca0019f105fa97f27cee0631efbf","observation_id":"9009ea6c-1657-4636-8d07-67563d5e68a0","resolution":{"observed_at":"2026-08-01T13:27:14.516714Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.13720","last_updated":"2026-01-07T05:36:57Z","snapshot_observed_at":"2026-08-18T02:11:41.876479Z","submitted_at":"2025-11-17T18:59:57Z","title":"Back to Basics: Let Denoising Generative Models Denoise","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.13720","snapshot_observed_at":"2026-08-01T13:27:14.630787Z","title":"arXiv preprint arXiv:2511.13720 (2025) 4","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.630787Z"},"links":{"cited_paper":"/paper/2511.13720","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:2d5bdbbe5584e81089cb4de70c0f3903ca638813bee21c98dcc1c96f4b679bf3","observation_id":"43eee339-2d17-4f7e-8241-1dca2808fa33","resolution":{"observed_at":"2026-08-01T13:27:14.630787Z","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":"2026-08-01T13:27:14.784859Z","title":"In: 8th Annual Conference on Robot Learning (2024) 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.784859Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:25f84af747bbdaae496a929b043563cf1bbe5d5307aba48af27d90f1ead92c33","observation_id":"14fbd0ca-6cb3-464a-9ff1-cff1f8b098f7","resolution":{"observed_at":"2026-08-01T13:27:14.784859Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.10647","last_updated":"2025-11-13T18:59:53Z","snapshot_observed_at":"2026-08-15T23:16:19.228206Z","submitted_at":"2025-11-13T18:59:53Z","title":"Depth Anything 3: Recovering the Visual Space from Any Views","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.10647","snapshot_observed_at":"2026-08-01T13:27:14.921960Z","title":"arXiv preprint arXiv:2511.10647 (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:14.921960Z"},"links":{"cited_paper":"/paper/2511.10647","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:fdf3b1bb20687b73fa648e20618b36e78d3da8c39ac08745c485d3320f99e4ac","observation_id":"6ee92fe9-5aa2-4c97-a691-84d1e6676e8a","resolution":{"observed_at":"2026-08-01T13:27:14.921960Z","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":"2026-08-01T13:27:15.070015Z","title":"In: The Eleventh International Conference on Learning Representations (2023) 2, 3, 5","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.070015Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:44b17847d2cc84d1319b51e6599c48779dbc8ec4bc596e3afc863ff49f0d3b46","observation_id":"0626a372-2416-44f9-80c4-a6678e80c82e","resolution":{"observed_at":"2026-08-01T13:27:15.070015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.16767","last_updated":"2025-06-25T07:19:44Z","snapshot_observed_at":"2026-08-18T09:25:14.498467Z","submitted_at":"2024-08-29T17:59:40Z","title":"ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.16767","snapshot_observed_at":"2026-08-01T13:27:15.174611Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.174611Z"},"links":{"cited_paper":"/paper/2408.16767","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:7a8ba3dde05789d67f9c1d843c4bb3f0f2e0f42671ca355b6433c491f9a8b9f5","observation_id":"b5f1f9ae-2869-464e-aa82-384dff7f99f0","resolution":{"observed_at":"2026-08-01T13:27:15.174611Z","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":"2026-08-01T13:27:15.286863Z","title":"In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.286863Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:824e691c5b9451583d7998c9abf87505cce98603be56055cba8fde311af45e66","observation_id":"4842a797-e422-41bd-9919-aa1201f9dc15","resolution":{"observed_at":"2026-08-01T13:27:15.286863Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07670","last_updated":"2025-06-09T11:45:50Z","snapshot_observed_at":"2026-08-15T06:17:54.529384Z","submitted_at":"2025-06-09T11:45:50Z","title":"ProSplat: Improved Feed-Forward 3D Gaussian Splatting for Wide-Baseline Sparse Views","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.07670","snapshot_observed_at":"2026-08-01T13:27:15.382043Z","title":"arXiv preprint arXiv:2506.07670 (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.382043Z"},"links":{"cited_paper":"/paper/2506.07670","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:e635438509e0733e23bd9022ed7d9125e0adce086e5cf02ff3769d5672624e39","observation_id":"32f659d0-0e97-4cc0-9aab-c2af449469d6","resolution":{"observed_at":"2026-08-01T13:27:15.382043Z","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":"2026-08-01T13:27:15.460831Z","title":"Communications of the ACM 65(1), 99–106 (2021) 1, 3","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.460831Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:41c7fc0a828c1ef4eddc8be2309ca6855feae5c3facd3c72721af890d49d79a7","observation_id":"1c2ce45a-eeef-44d2-8476-b1b6ecaeee50","resolution":{"observed_at":"2026-08-01T13:27:15.460831Z","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":"2026-08-01T13:27:15.567393Z","title":"In: International Conference on Machine Learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.567393Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:4bcd5658f63be84945095a4c59e94bae48a9ddca68f20e457232b485c1996cdd","observation_id":"2e643403-e781-4cec-a552-d8aba5727daf","resolution":{"observed_at":"2026-08-01T13:27:15.567393Z","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":"2026-08-01T13:27:15.691729Z","title":"In: Intelligent Systems for Molecular Biology (ISMB) (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.691729Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:6cf602b88200e2e0c4ecb4514181596ef1af92697e0285a8f99793c518c14990","observation_id":"135e2d80-a1fd-482f-8047-c6c70b9c6649","resolution":{"observed_at":"2026-08-01T13:27:15.691729Z","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":"2026-08-01T13:27:15.801136Z","title":"ACM transactions on graphics (TOG)41(4), 1–15 (2022) 3","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.801136Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:c30c6a66e684fae5a53e224dff4b1179d8b94300594a05781460d41f37a2f9b3","observation_id":"d46a3926-10cc-423f-81d0-b01257efd6d2","resolution":{"observed_at":"2026-08-01T13:27:15.801136Z","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":"2026-08-01T13:27:15.921164Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recogni- tion","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:15.921164Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:b8c3fbd6847607ded679a7ff7a0f040f94488a5377fe30b6c64d5108d99385b1","observation_id":"88503037-9869-46be-9c4b-9fa10300f623","resolution":{"observed_at":"2026-08-01T13:27:15.921164Z","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":"2026-08-01T13:27:16.036112Z","title":"In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.036112Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:300bf4ca00cbb27b4f708a1459ed7ff842dce5ba51ab19170dfefe320f58481f","observation_id":"3edea52f-3cbc-4391-a21e-95862daff04b","resolution":{"observed_at":"2026-08-01T13:27:16.036112Z","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":"2026-08-01T13:27:16.167367Z","title":"In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.167367Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:dffe9a8c90fa16e1b00dbc7aeea795df8f2c0b64ce47893a6eaacd08f9ec3e0a","observation_id":"5f8819e2-624d-4e88-839c-374dc1eb77ea","resolution":{"observed_at":"2026-08-01T13:27:16.167367Z","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":"2026-08-01T13:27:16.376200Z","title":"In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.376200Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:e4e9a280960619bc055873f138fa15029b30ab117607be48e1f6e6653f81d19b","observation_id":"8328a7cc-3247-4196-90a5-6366b3c0e15b","resolution":{"observed_at":"2026-08-01T13:27:16.376200Z","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":"2026-08-01T13:27:16.456927Z","title":"In: Proceed- ings of the IEEE/CVF international conference on computer vision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.456927Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:bbd514dcf8615650866a5f7ae7d1aeef81e5dd097c15d86fc51b4aceb32eb81f","observation_id":"20a570bd-6caa-4abc-8006-b88290481fb4","resolution":{"observed_at":"2026-08-01T13:27:16.456927Z","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":"2026-08-01T13:27:16.582043Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recog- nition (CVPR)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.582043Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:77834b2075e6a92f59819e4041e0a2f40c95a9ac30644b326d1e7c348157573a","observation_id":"2766da83-7a97-4c09-8223-deeadd28d6ba","resolution":{"observed_at":"2026-08-01T13:27:16.582043Z","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":"2026-08-01T13:27:16.706355Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.706355Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:868fcfd12fc0ea7691e82ab198db01eae868fab90b95d4994a7a55982ac762c4","observation_id":"d724f6c1-5d4d-4d45-8ebc-317d77ada6ad","resolution":{"observed_at":"2026-08-01T13:27:16.706355Z","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":"2026-08-01T13:27:16.823421Z","title":"In: Conference on Computer Vision and Pattern Recognition (CVPR) (2016) 3","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.823421Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:9c31faa825cc94d8499429622784c8ec44b854130042806be59f579f18befb34","observation_id":"ffac1f25-6255-4cee-9b0f-88ed3a695f8f","resolution":{"observed_at":"2026-08-01T13:27:16.823421Z","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":"2026-08-01T13:27:16.888507Z","title":"In: European Conference on Computer Vision (ECCV) (2016) 3","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.888507Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:a2026e8b2b48aea274fc72d6ea059f1c547bd7ec44791e93153b1d6aa7ba4138","observation_id":"2855eb3f-8853-4b0b-ac9e-a9b489e0acc3","resolution":{"observed_at":"2026-08-01T13:27:16.888507Z","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":"2026-08-01T13:27:16.969371Z","title":"In: Proceedings of the IEEE conference on computer vision and pattern recognition","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:16.969371Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:f2a6f8936a6afdaed84e8e571f387c85bc72f751cc5cf5be1f7a178e4ae95d23","observation_id":"23b82f3c-139e-4320-a3f6-9cde32a5a036","resolution":{"observed_at":"2026-08-01T13:27:16.969371Z","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":"2026-08-01T13:27:17.040629Z","title":"Advances in Neural Information Processing Systems (NeurIPS) (2024) 2, 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.040629Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:bb17f98ec7a565aca2dafd8d8137b4a2dae0ca12ae7f90b1525bef838730da8f","observation_id":"b1445b2d-c061-4bb4-8f56-fb0a29014fef","resolution":{"observed_at":"2026-08-01T13:27:17.040629Z","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":"2026-08-01T13:27:17.109654Z","title":"Neurocomputing568, 127063 (2024) 6 14","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.109654Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:66014075fc1b8a24c6885559bbfc26bf5ce10c6173e4ae70b9a3e0f3616023a8","observation_id":"cb765f99-62b4-4009-81ed-514600db00cf","resolution":{"observed_at":"2026-08-01T13:27:17.109654Z","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":"2026-08-01T13:27:17.173875Z","title":"arXiv preprint arXiv:2603.12655 (2026) 3","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.173875Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:af4cad1324dc2d618a750a26a5b30b94ee5e5c94950f92492d86e55fc05e117e","observation_id":"9944ba8d-e9fa-4f08-88f4-ba18efbf9475","resolution":{"observed_at":"2026-08-01T13:27:17.173875Z","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":"2026-08-01T13:27:17.247967Z","title":"IEEE Transactions on pattern analysis and machine intelligence13(4), 376–380 (1991) 6, 22","venue":null,"work_id":null,"year":1991},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.247967Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:13c818339312802c93e9060948c6d766fbc9fe8b7de3ddd632cfe1c439c06c63","observation_id":"d47ed5e0-d3ee-4991-ae2f-3cfbfc31cbe0","resolution":{"observed_at":"2026-08-01T13:27:17.247967Z","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":"2026-08-01T13:27:17.337772Z","title":"In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.337772Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:9906c12e2d1b480573feaf101bae80bbcd8a9701f47bece1e58b066968e177cd","observation_id":"de327b90-2401-4008-ab4d-bacbbf5ca4c7","resolution":{"observed_at":"2026-08-01T13:27:17.337772Z","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":"2026-08-01T13:27:17.436592Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2025) 2, 3, 4, 7, 19","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.436592Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:3f0e3807ef378dd27a3911f56497e608e26ed6049fbd850c6161dc5fc88e7c4a","observation_id":"7c03138b-a702-4768-98dc-a787bf1e7b52","resolution":{"observed_at":"2026-08-01T13:27:17.436592Z","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":"2026-08-01T13:27:17.525317Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (2024) 2, 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.525317Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:b9d78d41581e00c16e80c4b24a4c1f4dd3b1f3dff1ea376e1efdd7279cf0a664","observation_id":"5e64324a-4ee3-4848-9576-905ce6c7454f","resolution":{"observed_at":"2026-08-01T13:27:17.525317Z","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":"2026-08-01T13:27:17.623490Z","title":"IEEE transactions on image processing13(4), 600–612 (2004) 7","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.623490Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:a149a8f3109d58e998676cf2eb4abb220f5544c0cbceb2d303df7dd96bc29c61","observation_id":"126cdfe7-2be9-4289-91c9-a169cd468621","resolution":{"observed_at":"2026-08-01T13:27:17.623490Z","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":"2026-08-01T13:27:17.703129Z","title":"In: ACM SIGGRAPH 2024 Con- ference Papers (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.703129Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:cba065917f1beef4916fdb570cbe6fd295a90b1a559ff0bf7783a527277abb78","observation_id":"b8aafc85-42ba-4149-af62-fe97f3f99d7e","resolution":{"observed_at":"2026-08-01T13:27:17.703129Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.14717","last_updated":"2025-08-20T13:49:53Z","snapshot_observed_at":"2026-08-16T00:07:03.087862Z","submitted_at":"2025-08-20T13:49:53Z","title":"GSFix3D: Diffusion-Guided Repair of Novel Views in Gaussian Splatting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.14717","snapshot_observed_at":"2026-08-01T13:27:17.768346Z","title":"arXiv preprint arXiv:2508.14717 (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.768346Z"},"links":{"cited_paper":"/paper/2508.14717","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:d0b17582cbc76baed8aef9a548bb741ef7d687a74197718adf4746bd8a829cc6","observation_id":"47472e2e-f82c-4905-9f82-122051526526","resolution":{"observed_at":"2026-08-01T13:27:17.768346Z","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":"2026-08-01T13:27:17.853268Z","title":"In: European conference on computer vi- sion","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.853268Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:22c548be356d37c4457d577680733283b3493932beb85a08aaa377f6c9346d28","observation_id":"86fc13a4-6ee4-405f-ab94-238d5fabef21","resolution":{"observed_at":"2026-08-01T13:27:17.853268Z","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":"2026-08-01T13:27:17.928305Z","title":"International Conference on Learning Representations (ICLR) (2026) 2, 3","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:17.928305Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:21741863e2f8c9580d1357c18bb3d6b6944c794a7bd85542bd78619014c6c490","observation_id":"c0c5815d-0e66-408c-96f4-6ba32465e3d6","resolution":{"observed_at":"2026-08-01T13:27:17.928305Z","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":"2026-08-01T13:27:18.021068Z","title":"In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.021068Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:8feaaad3ef30704ebfe6b4e38a3ac7ed6ec0210383f917dd7a89dbbfb0c70a92","observation_id":"4e2ae90e-35a6-4f18-a17e-210d8e8b1b5f","resolution":{"observed_at":"2026-08-01T13:27:18.021068Z","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":"2026-08-01T13:27:18.115414Z","title":"In: Proceedings of the IEEE/CVF Conference on Com- puter Vision and Pattern Recognition","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.115414Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:eecea3d1b3fc7920af3ac7cf878441b16f8834ff5a3e350d4d2525c286d471d1","observation_id":"c62a6f23-df0c-42b7-9467-8ddcb81bf093","resolution":{"observed_at":"2026-08-01T13:27:18.115414Z","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":"2026-08-01T13:27:18.206942Z","title":"In: Proceedings of the Computer Vision and Pattern Recognition Conference","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.206942Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:ed18c394efd02453d48dfdcb8dd9e6ed3a5822e208ac6fd376a367e43ea92641","observation_id":"eb10ca82-38b6-4206-8b4c-b26f647c85f8","resolution":{"observed_at":"2026-08-01T13:27:18.206942Z","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":"2026-08-01T13:27:18.307632Z","title":"generation: Taming optimization dilemma in latent diffusion models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.307632Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:f6cf9a1953e709336287530353a9ebb191a1a4bc255792280ca65d33fa084cb5","observation_id":"bd6cc6de-73ca-4480-bd98-faeb2eb7af22","resolution":{"observed_at":"2026-08-01T13:27:18.307632Z","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":"2026-08-01T13:27:18.408926Z","title":"In: Proceedings of the IEEE/CVF International Conference on Computer Vision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.408926Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:35c1c34994a0beea3b652b101fb04130738498a202e0fba23c7ec75007e8265e","observation_id":"7f554886-159a-4daf-94ae-6316ef2c9698","resolution":{"observed_at":"2026-08-01T13:27:18.408926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.05297","last_updated":"2023-10-10T19:01:24Z","snapshot_observed_at":"2026-08-18T18:18:17.500992Z","submitted_at":"2023-10-08T21:55:00Z","title":"Fast protein backbone generation with SE(3) flow matching","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.05297","snapshot_observed_at":"2026-08-01T13:27:18.484742Z","title":"arXiv preprint arXiv:2310.05297 (2023) 3","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.484742Z"},"links":{"cited_paper":"/paper/2310.05297","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:7842224b73d90b441d898cdc9c049c55acb2734bee19d8ad35973d0bf0640b21","observation_id":"274fd6fd-73eb-4680-8fa2-bec8d4431043","resolution":{"observed_at":"2026-08-01T13:27:18.484742Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.09667","last_updated":"2025-08-13T09:56:28Z","snapshot_observed_at":"2026-08-05T20:57:39.135931Z","submitted_at":"2025-08-13T09:56:28Z","title":"GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.09667","snapshot_observed_at":"2026-08-01T13:27:18.568211Z","title":"arXiv preprint arXiv:2508.09667 (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.568211Z"},"links":{"cited_paper":"/paper/2508.09667","citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:7465e4fc3d62e4d76d9a35d4cf40d087b0b53f550d9bf1aa233469aa89a6e034","observation_id":"6db8af50-3745-44f2-87ca-814b57fdb79f","resolution":{"observed_at":"2026-08-01T13:27:18.568211Z","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":"2026-08-01T13:27:18.675490Z","title":"In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.675490Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:7c9bfc7c1f691e804ccb4634c239c1b84d49670b96c5fc66a4fe689820578d6c","observation_id":"69338f4a-47ec-40ab-874a-5714327b5a87","resolution":{"observed_at":"2026-08-01T13:27:18.675490Z","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":"2026-08-01T13:27:18.775817Z","title":"IEEE Transactions on Pattern Analysis & Machine Intelligence (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.775817Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:833bbda67ae0a002daa090fd4534d08efd9861e787ba5a54432148934fa1eebb","observation_id":"4dd6c27a-9b04-413b-ae76-03e350293ef7","resolution":{"observed_at":"2026-08-01T13:27:18.775817Z","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":"2026-08-01T13:27:18.863354Z","title":"In: European Conference on Computer Vision","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.863354Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:8e31156ed3e5e93b828cf3110d3c0fe997ca8e90374eb52153c60b4cd7b8a2a9","observation_id":"203bb07d-2a38-4e53-9015-ea36b2e6a4e5","resolution":{"observed_at":"2026-08-01T13:27:18.863354Z","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":"2026-08-01T13:27:18.959157Z","title":"In: Proceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition (CVPR)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:18.959157Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:f8bc51e09af61f9bcf8968fd7e4e4cc70abe9e9c6ee2d1e92af4d9bcc142e2af","observation_id":"9ed06449-2478-46b3-bb5a-693ad6381d60","resolution":{"observed_at":"2026-08-01T13:27:18.959157Z","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":"2026-08-01T13:27:19.015673Z","title":"In: Proceedings of the IEEE conference on computer vision and pattern recognition","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:19.015673Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:596c22f84f831ef79ae4a4b3f46d02ae2e35f8fca8fffca4323b3aa71a52e971","observation_id":"0011266a-797a-4f20-a3ad-2a12f2f2407f","resolution":{"observed_at":"2026-08-01T13:27:19.015673Z","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":"2026-08-01T13:27:19.075485Z","title":"In: The Fourteenth International Conference on Learning Representations (2026) 2, 3, 4","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:19.075485Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:32294514ac6851a0747a62e848757a25a80f192ba5e2eb3e4bd805c9848c6fd2","observation_id":"df989370-c8fe-462c-88fe-6573423ad389","resolution":{"observed_at":"2026-08-01T13:27:19.075485Z","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":"2026-08-01T13:27:19.156992Z","title":"In: Advances in Neural Information Processing Systems (2024) 3","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:19.156992Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:4703c6796677325f148eb0c908eea050fb81bf2db5891e2ebde4d56512697ee7","observation_id":"603d0626-f953-4fdf-8cae-8e94c7b0ef9c","resolution":{"observed_at":"2026-08-01T13:27:19.156992Z","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":"2026-08-01T13:27:19.269967Z","title":"In: SIGGRAPH (2018) 6","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:19.269967Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:6aac29beb724e130a09ebd37f37132bb1dd0d37fb504e2f0f1e644e1be71353a","observation_id":"731a0391-0363-4a1a-a0f6-b3be418a28fe","resolution":{"observed_at":"2026-08-01T13:27:19.269967Z","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":"2026-08-01T13:27:19.331682Z","title":"In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2025) 3","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:19.331682Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:f1f279302214210b47ce36ce11b39f58a406f0b436250e452a25f282559634c2","observation_id":"27632d1b-0769-46f5-a711-800f3a2ee974","resolution":{"observed_at":"2026-08-01T13:27:19.331682Z","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":"2026-08-01T13:27:19.380528Z","title":"a realistic scene","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-01T13:27:19.380528Z"},"links":{"citing_paper":"/paper/2607.19120"},"observation_digest":"sha256:3585ce26fb3ca3fdfe3355c29373691a18c48a11e5d1ed2cb4c465652b0acf91","observation_id":"0b155604-31a9-4463-9667-6a547cf35ff4","resolution":{"observed_at":"2026-08-01T13:27:19.380528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.19120","last_updated":"2026-07-21T14:06:04Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-18T17:28:49.715104Z","submitted_at":"2026-07-21T14:06:04Z","title":"Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models"},"reference_resolution":{"displayed":83,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":83,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":83},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2607.19120."}