{"as_of":"2026-08-11T19:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a5ef4caa9d053ffff1274f07a42c1bc368168a4c7066f3f405add8e1972ff740","coverage":[{"denominator":36,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":36,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T08:32:40.226275Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2604.16680/citation-record","integrity":"/paper/2604.16680/integrity","json":"/paper/2604.16680/citation-record.json","paper":"/paper/2604.16680"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Foundation models defining a new era in vision: a survey and outlook.IEEE Trans- actions on P attern Analysis and Machine Intelligence","venue":null,"work_id":"29a713b8-e04b-4cdc-be5b-fa5297f1c192","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:8eac661611b85150b83412e01977114857c65ae23e29438d275c9f53f5461ace","observation_id":"fd81b2a9-8749-4b86-8702-900b1fb4bdd7","resolution":{"observed_at":"2026-05-20T22:14:06.976657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Method for registration of 3-d shapes","venue":null,"work_id":"4ad0ab78-829a-40d0-871f-d3fd904bd489","year":1992},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:80b152dafa0e3c2edaf797b48f9fb83cdb27d3454a8e8e52e9dc23fff69f9d9b","observation_id":"95152c02-9e01-4f9f-bd38-37cb3edcffbc","resolution":{"observed_at":"2026-05-20T22:14:06.985642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sc2-pcr: A sec- ond order spatial compatibility for efficient and robust point cloud registration","venue":null,"work_id":"5d7c67da-4627-4ca4-b17a-d78b7f43ca4c","year":2022},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:e7a638750f219ca099030a739e9718b79e314425ed228d4998ce4296b6eefeeb","observation_id":"74c54364-ea24-4224-8db1-e9112c1c9df8","resolution":{"observed_at":"2026-05-20T22:14:07.054959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Fully convolutional geometric features","venue":null,"work_id":"bf72b58e-8c32-4c0b-9291-45367b528fac","year":2019},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:27936734412c341928819a30fb42170fa24a520ad6dac83706f57000be811a2a","observation_id":"30cd12f1-3cb2-4f7d-b6a9-292d52b2bbb9","resolution":{"observed_at":"2026-05-20T22:14:07.039942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A generic fisheye camera model for robotic applica- tions","venue":null,"work_id":"aec7f7cf-709d-474a-b72d-a1a15d96af1f","year":2007},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:71e4b213337f6c0a5b9209b5fde23ead26130547cf91f175578469f602d93986","observation_id":"72d9296e-d4c7-4efe-8e87-efb6769add23","resolution":{"observed_at":"2026-05-20T22:14:07.045859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A volumetric method for building complex models from range images","venue":null,"work_id":"65476f87-fb0b-4f9a-92e4-3ec2e6804ec8","year":1996},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:6791728f51fe66e3c8e57a357edee460168db825c3bbf6b769daa2778598786c","observation_id":"1290bd0b-2ef8-4c37-abda-ecf8cb040ef5","resolution":{"observed_at":"2026-05-20T22:14:07.050508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scannet: Richly- annotated 3d reconstructions of indoor scenes","venue":null,"work_id":"6609a188-a861-4a16-a155-86890b543470","year":2017},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:e32b53f4658bf8ed12655069ba3993bfbb4668e60bf5622d4effa115f771480d","observation_id":"9f6674df-5e88-45fc-bb32-99249d365e6b","resolution":{"observed_at":"2026-05-20T22:14:07.031248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Roma: Robust dense feature matching","venue":null,"work_id":"7ef5690e-bf16-477f-95a6-203faf257fdd","year":2024},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:56d398bfb6260e74c166021ab24f79c57aaeeabfaca87ca0dca603bd94bd333d","observation_id":"a6f9834b-52fa-4102-8727-880354d6ce1c","resolution":{"observed_at":"2026-05-20T22:14:07.033395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395","venue":null,"work_id":"752367ec-4288-4cb4-96d8-48fb921b7781","year":1981},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:73b3e18601cb61728df7b1188787bb2317767fe7ccd9d78f901bf8e8c32e113b","observation_id":"42ee3f8e-7dd1-4398-83c3-1644a18e6940","resolution":{"observed_at":"2026-05-20T22:14:07.037823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vision meets robotics: The kitti dataset.International Journal of Robotics Research (IJRR)","venue":null,"work_id":"5faae8ad-02ac-4395-a0b9-3a906c87dcd7","year":2013},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:3265dbc74a60015faae98fa35558c10dc5cd0ef938a4146515522dcae9439b62","observation_id":"faa94e1b-b833-4020-aca4-b32f326a5fd0","resolution":{"observed_at":"2026-05-20T22:14:07.026970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Closed-form solution of absolute orientation using unit quaternions.Journal of the optical society of America A, 4(4):629–642","venue":null,"work_id":"52d5afbc-cf03-435b-a75e-60d107f2018b","year":1987},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:56a9f657d43655078f27936f2e9ba85e054478714ac3965712f9b120d08abf50","observation_id":"4da57907-4956-41ce-b205-4513a62f8bb2","resolution":{"observed_at":"2026-05-20T22:14:07.029271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Predator: Registration of 3d point clouds with low overlap","venue":null,"work_id":"6f7d021a-b47b-4a68-9a64-7e3148788057","year":2021},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:32cfac0136a7975a56dce9a443aa43203ff42b6a012b1f812a578c8d6065b73c","observation_id":"4d7a39c2-74ed-4cfe-9a1c-7204932d6f5f","resolution":{"observed_at":"2026-05-20T22:14:07.022099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Generative point cloud registration","venue":null,"work_id":"5391c403-4d83-4969-81f7-ebe9259e9661","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:0b07d13c6c7f3051411749a780a3e62ed0207e72168d55a739081dad4ed3f0d7","observation_id":"d45eda41-ab4f-479f-a8c5-a34afb991270","resolution":{"observed_at":"2026-05-20T22:14:07.019944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Zero-shot rgb-d point cloud registration with pre-trained large vision model","venue":null,"work_id":"41364fc5-6010-4d6d-a042-039472fea1b8","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:511cbc0c158a58fb54a584d0b1d1702e0b3dbcb9f7b5078f0e6aca3bc41ff173","observation_id":"95f759d3-645d-4b9b-aa12-24fcffb1dc2b","resolution":{"observed_at":"2026-05-20T22:14:07.043882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Distilling cosmos transfer 1 models","venue":null,"work_id":"3a26798e-a970-4457-8521-a373519d7a6b","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:b1d2ae443fc2b84323e8a49df0c0a813bdb9dcd156d52150fea4590a6230d67e","observation_id":"39254d13-ec8c-4e68-b958-e7d8c80012c1","resolution":{"observed_at":"2026-05-20T22:14:07.024340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Grounding image matching in 3d with mast3r","venue":null,"work_id":"801b4e94-abc9-4b28-9c8c-aa32e233a24b","year":2024},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:9000259a33e6fd753c66a7e41eaf24882ca6c573c750dbd35d0013ea556d7094","observation_id":"9fdc1163-acd6-4999-8504-63e5613c1ad0","resolution":{"observed_at":"2026-05-20T22:14:07.042002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Unsupervised deep probabilistic approach for partial point cloud registration","venue":null,"work_id":"3038a292-a903-4c16-a17d-ddb72d484e9c","year":2023},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:0f98dfdd14ba12e5dda8cc6df6ae0c7b9f8a5d32c0095e26e18f0375798feb2f","observation_id":"146428e5-b8f5-4efe-bd08-a9de75ff90a0","resolution":{"observed_at":"2026-05-20T22:14:07.048275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Colorpcr: Color point cloud registration with multi-stage geometric-color fusion","venue":null,"work_id":"5887215d-ce6d-496e-8e9c-142ad8c2a8fc","year":2024},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:df9c75472028647b74410a8fbcd6b82ec4be7c27c4dbd65b6e592b7bf3b919db","observation_id":"4ddfa0b8-573a-4026-8844-cd65befe2778","resolution":{"observed_at":"2026-05-20T22:14:07.057379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cosmos world foundation model platform for physical ai","venue":null,"work_id":"f39e9fc7-d71f-4d2a-a712-bb615f1a350a","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:f1636fb2659009176265a811ea344f4e104582dc3f9e055c1c2ea9c590dacfb8","observation_id":"157dfcac-95b2-4236-8680-e41f901f53f2","resolution":{"observed_at":"2026-05-20T22:14:06.979238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cosmos-transfer1: Conditional world generation with adaptive multimodal control","venue":null,"work_id":"4ce0769b-eb40-474a-9a8a-adfb9c8d6785","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:d41a9112419a967377e5d43f063d69642120f1978d4ec6f0bddae5633178b9ed","observation_id":"6ff1d726-dc4a-496f-9fd4-7e2b6fed79b6","resolution":{"observed_at":"2026-05-20T22:14:07.007264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"dce27be0-68a6-478e-bf84-a617ab79b59a","year":2024},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:fd07683419c3110f95e7f6a4f46d828d9ead77a387cb680acbafc7b908afd3b6","observation_id":"4ef3b291-a87b-4e93-a9b5-0030feb93721","resolution":{"observed_at":"2026-05-20T22:14:07.017788Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Geometric transformer for fast and robust point cloud registration","venue":null,"work_id":"7bb4c510-6326-499b-be83-4102d5a70b38","year":null},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:8560b7e089fd9e9294a48427e778a28b3f8474a523cf7001c65691500b1497cf","observation_id":"f47d66b3-bfff-4c29-92bf-38ff234c17e2","resolution":{"observed_at":"2026-05-20T22:14:06.999278Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cosmos-drive-dreams: Scalable synthetic driving data generation with world foundation models","venue":null,"work_id":"544dfe04-f4ff-4b22-8e10-84734d0a5b4f","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:2447cabe50ee7451242a6aefccf8d731066ccc8f7e107d44e4152dcba511db71","observation_id":"e21717e8-e0eb-45f7-9e17-2f2556c27afd","resolution":{"observed_at":"2026-05-20T22:14:07.035496Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T20:17:33.960726Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"c59f9959-3acd-48cd-84cb-88cf730e1f83","year":2022},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:3c36eb2a80f37eddc46f226b0f099c131b75011c415323fbbdb6097b1803a880","observation_id":"f466f0be-07d1-44b0-ad62-67b4c5fee81e","resolution":{"observed_at":"2026-05-20T22:14:06.996514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Fast point feature histograms (fpfh) for 3d registration","venue":null,"work_id":"c244959b-bd06-4dc5-8bca-7fbfb88d822c","year":2009},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:be35002ed4ae5dbdf472712f041478876d81abc92159ebd644f6c7ea6e67d13b","observation_id":"9c0b7cf6-9754-4851-beb3-02720eb5c00f","resolution":{"observed_at":"2026-05-20T22:14:07.003026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Superglue: Learning feature matching with graph neural networks","venue":null,"work_id":"8de6284e-38ed-445c-bdaf-22af4059bd60","year":2020},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:170636f56ad9eeb9c4860c9b212286d2940a8c6027359837dd5d920676878950","observation_id":"c3c895ad-90f3-46ba-87ba-46832f83b6fd","resolution":{"observed_at":"2026-05-20T22:14:06.994127Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A flexible technique for accurate omnidirectional camera cali- bration and structure from motion","venue":null,"work_id":"a3bc3bec-0589-4033-9887-61ee8a219c2e","year":2006},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:36054abe49ff6f7604a2399b9250694401e14338a14b1608a2d6088961b56cef","observation_id":"3abf454a-4eb9-4283-aa94-941ca734e7f5","resolution":{"observed_at":"2026-05-20T22:14:07.001224Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scalability in perception for autonomous driving: Waymo open dataset","venue":null,"work_id":"f3392060-6962-4b0e-8a67-cfed0d796715","year":2020},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:bf88fea5c8ebd48e7d26ef97be6cb94f408bc6c77e28699f2883047e628e3a8f","observation_id":"13f6d526-6517-46b5-ab42-6a4369f68cf3","resolution":{"observed_at":"2026-05-20T22:14:07.015670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18594","last_updated":"2025-01-30T18:59:43Z","snapshot_observed_at":"2026-08-10T21:33:12.435265Z","submitted_at":"2025-01-30T18:59:43Z","title":"Foundational Models for 3D Point Clouds: A Survey and Outlook","version":1},"cited_work":{"arxiv_id":"2501.18594","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18594","snapshot_observed_at":"2026-06-29T22:54:01.275994Z","title":"Foundational models for 3d point clouds: A survey and outlook","venue":null,"work_id":"ee4b8039-786b-451d-a8fc-cd69ace1b5ee","year":2025},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"cited_paper":"/paper/2501.18594","citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:ad50f714fe786fe6c1c77c5ef767dc1029ec5017abd22b70b1e271ecca788045","observation_id":"1546e849-d941-4bfb-b0dd-51e0b67025ea","resolution":{"observed_at":"2026-05-10T08:32:51.680468Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Unique signatures of histograms for local surface description","venue":null,"work_id":"79ae255b-bbc7-46c5-8919-d461e9a5eac3","year":2010},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:73d7aaad754c1a2da16573cf812d423b96fa931147eadde0fa1aec7503ec6ca6","observation_id":"474b4ca7-d48c-426f-a231-8427ea63d8a3","resolution":{"observed_at":"2026-05-20T22:14:07.052774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Freereg: Image-to- point cloud registration leveraging pretrained diffusion models and monocular depth estimators","venue":null,"work_id":"c7d1a6fe-667a-447a-8c15-3d9de32360fe","year":2024},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:325582d1ef8c75cfe49706c102766163a748c43c3638f50264d8871950b9888c","observation_id":"9bd06611-6308-4bff-8caa-153a9685e9a3","resolution":{"observed_at":"2026-05-20T22:14:06.992060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dust3r: Geometric 3d vision made easy","venue":null,"work_id":"7398a0d8-18ce-476f-a60b-a47596e548fb","year":2024},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:aaeb8c3d906c9031bfcac6a2c4fe330009dd07067ff289ead252f5177d54e23c","observation_id":"130abb3d-f0ce-4da6-8397-58cba6fea610","resolution":{"observed_at":"2026-05-20T22:14:07.004984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rotation-invariant transformer for point cloud matching","venue":null,"work_id":"bc6de850-7601-4a41-a470-149d4527bf5b","year":2023},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:87edc0e2287298a3fc11086c074cf6d25c6409d58ed7b736aeced903ddd078e3","observation_id":"c83f6b41-9d76-4022-af99-054521d73bd5","resolution":{"observed_at":"2026-05-20T22:14:06.990072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pointmbf: A multi-scale bidirectional fusion network for unsupervised rgb-d point cloud registration","venue":null,"work_id":"298202c2-bab1-44d7-914a-9dbd296c7441","year":2023},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:d753eb82780ffb523bac8a07c567faaf60b8c5bff2df28b00c0d025a8b0bdde8","observation_id":"bfb74df2-d95b-4d1b-8c77-04879fe78076","resolution":{"observed_at":"2026-05-20T22:14:06.987657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3dmatch: Learning local geometric descriptors from rgb-d reconstructions","venue":null,"work_id":"abef0f5a-1f2d-4bba-90ca-7fa080912b2c","year":2017},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:3b163adafc31612a87a865286aebc5fade3c8934b9ea9e463e531101ac67553c","observation_id":"c45bc710-b01d-46c2-be9c-56a1a743f07f","resolution":{"observed_at":"2026-05-20T22:14:06.981606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"safeguard","venue":null,"work_id":"3985b4ee-4b1c-49d5-ab7f-79e8434815bc","year":2023},"citing_paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-10T08:32:40.226275Z"},"links":{"citing_paper":"/paper/2604.16680"},"observation_digest":"sha256:90ddf036186df5da553a2af78b75d75588bda929b4d96f24d9286a71bd209575","observation_id":"584d1e42-5c63-4126-940a-b31b839c4ef4","resolution":{"observed_at":"2026-05-20T22:14:06.983665Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.16680","last_updated":"2026-04-17T20:29:32Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T23:03:57.199731Z","submitted_at":"2026-04-17T20:29:32Z","title":"C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion"},"reference_resolution":{"displayed":36,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":1,"verified_fuzzy":33},"total_outbound_references":36},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2604.16680."}