{"as_of":"2026-08-05T10:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c939f5b03bea40a860ad45c535aaceb8c1b8db432f952553de0641fdd9412494","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-28T15:42:27.248927Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+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/2606.01573/citation-record","integrity":"/paper/2606.01573/integrity","json":"/paper/2606.01573/citation-record.json","paper":"/paper/2606.01573"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Large-scale data for multiple-view stere- opsis","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:76ec9adc309b5994b2836fb88ea7c100a3e1de0266a645d443325be8014bf8bc","observation_id":"f15ad03f-a8af-43c1-9ed0-4c814c2d35f6","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:e4c085debbe9c87bd9f225d49ae0c8a74f6950f1ac953d03ad6a6dc5ad623a48","observation_id":"4e196d7c-7033-4980-93d2-dcf817f73417","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"5470–5479","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:5cb82d102cd0afac53792ab65042174935d7ca22743b1616c5730034de2d9df3","observation_id":"c447b7b8-ab65-4f43-b2d4-e176fadfb67e","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.14627","last_updated":"2024-07-18T13:10:22Z","snapshot_observed_at":"2026-07-06T17:48:35.724692Z","submitted_at":"2024-03-21T17:59:58Z","title":"MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images","version":2},"cited_work":{"arxiv_id":"2403.14627","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2403.14627","snapshot_observed_at":"2026-07-04T00:29:15.985127Z","title":"Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images","venue":null,"work_id":"7623c115-f61f-4ba4-9efa-a611ab5fec93","year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2403.14627","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:fac58501e76c27b91a597f35ee7fd63ae70cc238cbd12505055ef7f9f2a202ce","observation_id":"ceafdde9-22b9-4ed2-8699-c609f636e5a4","resolution":{"observed_at":"2026-07-01T22:06:16.904127Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Scannet: Richly-annotated 3d reconstructions of indoor scenes, in: Proc","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:50f92d5b5ced417d01c3b757afe4d96165313e82490efbd85b77d6f91eed5feb","observation_id":"dc16f611-f8e8-4681-be96-3adaf594880c","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"FlashAttention-2: Faster attention with better paral- lelism and work partitioning, in: International Conference on Learn- ing Representations (ICLR)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:8aa85f83300020b8f778c4d137ca557cd1e49e73b9ebe2ca4275bd5712472c53","observation_id":"34f3a86a-5dc1-4d67-b9c8-8adbbfe476c6","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Superpoint:Self- supervised interest point detection and description, in: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:bf7eac1491ff3e2901146061c8ddf1a24cb21e523447046376696495f7d26de9","observation_id":"76c8075f-480e-4143-bede-06b741c4118b","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Real-time plane-sweeping stereo with multiple sweeping directions, J.K","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:fbd5f8d180502c006995b42a7e4419f0599ffcf49b68a2355d146c878692b35d","observation_id":"20431c5d-d8a3-44fd-9f8f-a20556023f98","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Vision meets robotics:Thekittidataset","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:33f8f87c219d026959a0d7a0e963c4dfba7df6c8f491f7f2788a6686f002f50b","observation_id":"02bcaac7-a794-4003-8710-c72605332989","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Rgbd gs-icp slam, in: European conference on computer vision, Springer","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:998905a784decc2fe8095996d28246c29f69ef621de652f39fdffdb79e976e83","observation_id":"af30bcdb-ca5d-4eb3-b54b-62987719701e","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"1519.365742","doi":"10.1145/3641519.3657422","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"In: SIGGRAPH 2024 Conference Papers (2024)","venue":null,"work_id":"8d7e57a2-6c0a-417c-a9e9-c721b02e7ed5","year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:4dd5ca3107d4da06f848d58c5e2123432b8bf4ba3dd52791def70da99826fbb0","observation_id":"7d9b4cfb-1388-4378-b811-1bf0972917e0","resolution":{"observed_at":"2026-06-28T15:52:21.849474Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:26459d448138c746cbb91cab6128354f5353d2bc7003b0d8b5ea46433c096f02","observation_id":"73c87e5e-06dc-48c0-aee8-2fae667a733d","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Anysplat: Feed-forward 3d gaussian splatting from unconstrained views","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:8863bcbdfd71f8f3f45e361da7613f59746a88fa644ff889f4024395a3f8770d","observation_id":"139cb4a2-4f8a-4b2c-a0ec-0d001bcf2c77","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Splatam: Splat track & map 3d gaussians for dense rgb-d slam, in: Proceedings of the IEEE/CVF J.K","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:334e50d526c38e56a0ee3c45b3a14c9b6cb37524dc3a086027c4db6db5ce8752","observation_id":"14e17822-5780-4676-90b3-4d1d56c8bdfc","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"MapAnything: Universal feed-forward metric 3D reconstruction, in: International Conference on 3D Vision (3DV), IEEE","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:b9938d1097540520b48ffb4dcfbad049375abc60fa9eb472e63b1c5a6f98cf27","observation_id":"ccb887ce-2e5e-437e-be85-17ad64e51a34","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"3d gaussiansplattingforreal-timeradiancefieldrendering","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:138eff48f25ee72c392a6019454edea9e91f4d893831d83c2a09a06bcb8f4669","observation_id":"53b4402c-bdb9-41e9-8f2e-3dd8d4228ded","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Tanks and temples: Benchmarking large-scale scene reconstruction","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:028bc8bca8d1ac8b60026f5cadd106ba3ce5baaf28bc4aae7bb13e1b0ed32a03","observation_id":"8a673171-2b9c-4a96-b657-494e62f0a120","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2510.22706","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-01T22:06:16.940888Z","title":"Iggt: Instance- grounded geometry transformer for semantic 3d reconstruc- tion","venue":null,"work_id":"6e016eeb-2868-4753-b835-22089e21fd18","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:0527dd5ce5fb02b03caa0952793e809a45763edcace2bf344cb07ed8da1ce9c3","observation_id":"afea1c82-63bd-4beb-b811-046c318b5c63","resolution":{"observed_at":"2026-07-01T22:06:16.942398Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2603.00697","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T20:00:08.275685Z","title":"Tokensplat: Token- aligned 3d gaussian splatting for feed-forward pose-free reconstruction","venue":null,"work_id":"7d92f2d7-eb91-4560-ad40-ed5a36ab55f3","year":2026},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:736178fc96aec9f84f643bd5a5f53619ddac2daec69bce7c086d694cb0d93a20","observation_id":"e6d84514-4ef1-4b66-ba37-5ce3e3ef2934","resolution":{"observed_at":"2026-07-01T22:06:16.938938Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.10647","last_updated":"2025-11-13T18:59:53Z","snapshot_observed_at":"2026-07-06T22:35:46.018050Z","submitted_at":"2025-11-13T18:59:53Z","title":"Depth Anything 3: Recovering the Visual Space from Any Views","version":1},"cited_work":{"arxiv_id":"2511.10647","doi":"10.48550/arxiv.2511.10647","metadata_source":"pith","pith_arxiv_id":"2511.10647","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Depth Anything 3: Recovering the Visual Space from Any Views","venue":"cs.CV","work_id":"0a54b500-1e9d-46c2-85eb-8e16cbac8461","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2511.10647","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:4b9a59e24fa9d69b371eb1b5895b9bd8fcd91f11e3b4237f8d4e73992c66b52a","observation_id":"ea9cfaa9-f6af-48c9-bebf-0dba92c39cad","resolution":{"observed_at":"2026-07-01T22:06:16.939817Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Scale invariant feature transform","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:ebe4afaafcf209db58fe4e172b25726268e40f5925ad01fc95f3630c57b9bbc5","observation_id":"f0bc9228-4216-4199-aeb3-96f87b6826b4","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Scaffold-gs: Structured 3d gaussians for view-adaptive rendering, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:4f1dcd9e72e85b178240b05dd3d4453efbe94347adad0464767dddc1a5b4dd4d","observation_id":"0598125c-9eae-4699-a642-d649d1bc67e0","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.07123","last_updated":"2022-11-29T07:07:37Z","snapshot_observed_at":"2026-08-02T22:08:27.106810Z","submitted_at":"2022-02-15T01:39:07Z","title":"Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework","version":2},"cited_work":{"arxiv_id":"2202.07123","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2202.07123","snapshot_observed_at":"2026-07-04T20:00:07.697178Z","title":"Rethinking network design and local geometry in point cloud: A simple resid- ual mlp framework","venue":null,"work_id":"64512226-f7fd-4e43-8731-9b00608d193e","year":2022},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2202.07123","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:2a7d57be9534e029669ced50c00f609974e6eb18c155f450764534e911b22ad2","observation_id":"ce1f02cf-0f3f-44ec-a968-c88cb1f99d77","resolution":{"observed_at":"2026-07-01T22:06:16.945039Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Gnerf: Gan-based neural radiance field without posed camera, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:73ba49efcfade24d209f9c62a6b5fc5a08556d35363842d5714b9d6a9d1481f1","observation_id":"88fc664d-dc9e-45f6-a2f8-ed982a317140","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Nerf: Representing scenes as neural radiance fields for view synthesis, in: ECCV","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:61a8f8ee8fdcf4652161d023416d85ddae75aafc1cf4a615dc94b220e7fb76f2","observation_id":"02e3b9c0-aab3-494f-bcac-9597e34c8255","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Objects as volumes: A stochastic geometry view of opaque solids","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:0101cbc8fc0132844db2713f5f5307b56e61da4196f8815f96f8a8429ab0e173","observation_id":"b07e4a8b-ba94-4460-9c17-819fe18ce095","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:9b60dd2a01cb5c6221a6b5a089b1840b8a31f0029cd91c129e1bdb0be2c0cee3","observation_id":"0f67a7c6-7eb8-49d4-857a-051ff63021b2","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Global structure-from-motion revisited, in: European Conference on Com- puter Vision, Springer","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:15f3d9497c07d9a54c5831c60b0eeccd3abf0746e6fe622ba21ad2906934f850","observation_id":"970272b2-5eb0-497b-8246-c9bf8a975ae2","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Vision transformers for dense prediction","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:65f2886ae3d540a5d34f308415f6ab7c020a5c9bab2c0f97746c4e9becaf665c","observation_id":"b5f1e73a-39c1-4f22-bcb8-ba79766907fe","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2511.04283","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T16:58:42.375388Z","title":"arXiv preprint arXiv:2511.04283 , year=","venue":null,"work_id":"a7a9f296-0926-4260-aa25-46d1a58d2232","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:d2114c9a9dd337ba086e628fa7e6848b3c09124ccd1aef8867a0faefcda6cde8","observation_id":"468464d2-6cba-4528-9ad1-38f814bf4619","resolution":{"observed_at":"2026-07-01T22:06:16.936222Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Superglue: Learning feature matching with graph neural networks, in:ProceedingsoftheIEEE/CVFconferenceoncomputervisionand pattern recognition, pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:9c3674b6f569803b9ba962fcd28b65dea4d580b506d3b922abd078739de3dd0e","observation_id":"44299ed9-e111-4798-ba88-321052c840d7","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Structure-from-motion revis- ited, in: Conference on Computer Vision and Pattern Recognition (CVPR)","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:d7822cd60b45107c01309a7bdacf2e8297d52e9614a281baa4dbc40623fe14de","observation_id":"709014f5-c52d-4236-bd63-49c36540de59","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Pixel- wise view selection for unstructured multi-view stereo, in: European Conference on Computer Vision (ECCV)","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:1ba26918575cd5e27f184347ef488419a76f0e36647e0fcb860b2191120b56d7","observation_id":"afbd4999-7d01-4190-8adb-9a492e39d237","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.05797","last_updated":"2019-06-13T16:29:58Z","snapshot_observed_at":"2026-08-01T13:51:16.469557Z","submitted_at":"2019-06-13T16:29:58Z","title":"The Replica Dataset: A Digital Replica of Indoor Spaces","version":1},"cited_work":{"arxiv_id":"1906.05797","doi":"10.48550/arxiv.1906.05797","metadata_source":"pith","pith_arxiv_id":"1906.05797","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"The Replica Dataset: A Digital Replica of Indoor Spaces","venue":"cs.CV","work_id":"8145b3bf-a202-46d8-a3bc-fad366dd5d4a","year":2019},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/1906.05797","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:b2c73c957a1145a37da7e5d4e02b1702c9d199b4765f6511c0239da960a407f8","observation_id":"8007a02a-17d3-4575-9117-6e285be9f919","resolution":{"observed_at":"2026-07-01T22:06:16.933929Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-23T17:23:43.390569+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T17:23:43.390569+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Sparsityinvariantcnns,in:InternationalConferenceon3D Vision (3DV)","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:4a081f95bc7d41dfa4afe2c78a92d6721a28a2219ef9ba1a7195333074340f9e","observation_id":"21927f48-c8b7-4439-9d58-f5114d3ba3b8","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2511.20343","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T16:38:39.687516Z","title":"Amb3r: Accurate feed-forward metric-scale 3d reconstruc- tion with backend","venue":null,"work_id":"e23363c6-4f1f-4098-a563-5577e086b3c8","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:a8fd5f6c69b9df87567f9910f57524e5ba992a9bda6c739f9e806cc264096982","observation_id":"930fd03f-83b4-4390-b51c-9e0b6b1eb0e3","resolution":{"observed_at":"2026-07-01T22:06:16.944238Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Vggt:Visualgeometrygroundedtransformer,in:Proceed- ings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:1010ce555823fda69cafa2cee6db0aa51d3270410d8bb2e0fe1cbf58b2cdbc7e","observation_id":"5abb65f4-0592-46e6-857e-a3dc2c659df3","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.15195","last_updated":"2026-05-14T17:59:51Z","snapshot_observed_at":"2026-07-06T23:26:32.979566Z","submitted_at":"2026-05-14T17:59:51Z","title":"VGGT-$\\Omega$","version":1},"cited_work":{"arxiv_id":"2605.15195","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.15195","snapshot_observed_at":"2026-07-08T13:14:53.219391Z","title":"VGGT-$\\Omega$","venue":"cs.CV","work_id":"a436a79f-669d-4c92-9350-254bbcbf3fee","year":2026},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2605.15195","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:3b218e07d7c06d6338f54079dfe9a4f2f7492cba4e0de00af4952faf97161bc7","observation_id":"65b8be9b-c055-4d82-a09a-e603b31593e8","resolution":{"observed_at":"2026-07-01T22:06:16.919345Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Vggsfm: Visual geometry grounded deep structure from motion, in: Proceed- ings of the IEEE/CVF conference on computer vision and pattern recognition, pp","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:5ed914f90f706a035696fcca3baa725e6a4d58d8e357950db30245ad76a3e287","observation_id":"5ce4cd6b-2770-4b90-b8f6-86250eceae5e","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Dust3r: Geometric 3d vision made easy, in: CVPR","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:e6b076e312e44d0a224b432c4ab0812663468a8a187400dad3d131ef66061f72","observation_id":"36762155-430a-4493-a499-f4a2b13bdb1b","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.19297","last_updated":"2026-06-24T10:16:56Z","snapshot_observed_at":"2026-08-04T15:39:12.973533Z","submitted_at":"2025-09-23T17:59:02Z","title":"VolSplat: Rethinking Feed-Forward 3D Gaussian Splatting with Voxel-Aligned Prediction","version":3},"cited_work":{"arxiv_id":"2509.19297","doi":null,"metadata_source":"pith","pith_arxiv_id":"2509.19297","snapshot_observed_at":"2026-07-04T13:19:51.046437Z","title":"V olsplat: Rethinking feed-forward 3d gaussian splatting with voxel-aligned prediction","venue":"cs.CV","work_id":"a1117a19-eb44-4a5b-866c-4918d06fbdd5","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2509.19297","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:b8b489db817b38eb6465b9453d35c7ea3f57097aaf5e7bd77b57f9e7367c2626","observation_id":"d09adeb5-0882-43ef-8f20-246c0eb0aa2a","resolution":{"observed_at":"2026-07-01T22:06:16.921884Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.13347","last_updated":"2026-03-07T07:01:59Z","snapshot_observed_at":"2026-08-02T12:12:15.465550Z","submitted_at":"2025-07-17T17:59:53Z","title":"$\\pi^3$: Permutation-Equivariant Visual Geometry Learning","version":3},"cited_work":{"arxiv_id":"2507.13347","doi":"10.48550/arxiv.2507.13347","metadata_source":"pith","pith_arxiv_id":"2507.13347","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"$\\pi^3$: Permutation-Equivariant Visual Geometry Learning","venue":"cs.CV","work_id":"8ab9cfd6-a60d-45e6-a572-9b4db82b8527","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2507.13347","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:e6fb0ae7711870b1d4397d393e67ed9fbd6f453ca8b9d76e77754ea5ffc639c0","observation_id":"ae0a2682-bfe5-4654-838d-56fe6abc5c5e","resolution":{"observed_at":"2026-07-01T22:06:16.924386Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Image qualityassessment:fromerrorvisibilitytostructuralsimilarity","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:16e780b9d056fff6906c87c459b2810d17e3b1ab1b95eab920131d408b546bca","observation_id":"e82320c8-bf8e-470d-81ef-b270c8207ae3","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Image qualityassessment:fromerrorvisibilitytostructuralsimilarity","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:249b681af4a5eeb1373d71272a54d9c2882267ad56e1523c5a0148ed7a1b335b","observation_id":"3b1e7ac9-023e-4fdb-8e31-7bcff8211496","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Nerf–: Neural radiance fields without known camera parameters","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:f1f9dcd4fde1e8d42c51924deefb8e11ff3f70949c95ae6a46c3d0598c4662bb","observation_id":"df14dc40-feba-40c7-ac4a-2b57da3db028","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"4d gaussian splatting for real-time dynamic scene rendering,in:ProceedingsoftheIEEE/CVFConferenceonComputer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:e5e6c73ce1919d955e27c2df57b197338907581bb114df4300739412a1b41fdd","observation_id":"84d0ca94-b49a-48e7-9956-847de4cddad2","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.20378","last_updated":"2025-04-29T02:47:02Z","snapshot_observed_at":"2026-08-05T02:52:13.854952Z","submitted_at":"2025-04-29T02:47:02Z","title":"Sparse2DGS: Geometry-Prioritized Gaussian Splatting for Surface Reconstruction from Sparse Views","version":1},"cited_work":{"arxiv_id":"2504.20378","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.20378","snapshot_observed_at":"2026-07-01T22:06:16.911924Z","title":"Sparse2dgs: Geometry-prioritized gaussian splatting for surface reconstruction from sparse views","venue":null,"work_id":"9ae7c4bd-5a00-4f28-baa5-ba4fc25757e2","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2504.20378","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:56c9d77b4cb62e27b654acfd847cb1d41c68d40bc0f3c3216245709014252132","observation_id":"2eae4c4e-af33-4119-b144-d6c16d1513f0","resolution":{"observed_at":"2026-07-01T22:06:16.913636Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Point transformer v3: Simpler, faster, stronger, in: CVPR","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:5ca50b3129f266e705613c410172909e14952167452185d5241fd2ce3a883371","observation_id":"8fba2c6d-5f9b-44cb-a429-80f89be83e45","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Depthsplat: Connecting gaussian splatting and depth, in: CVPR","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:1e4b29e86910d12815523a0bc3fb8b36cbdfd6e0917f22e726e151b42d61ebd9","observation_id":"4eedb847-e50e-433e-a56f-4ba1d7cae9d1","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.09573","last_updated":"2025-09-01T06:27:11Z","snapshot_observed_at":"2026-08-05T01:31:46.796529Z","submitted_at":"2024-12-12T18:52:53Z","title":"FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D Reconstruction","version":2},"cited_work":{"arxiv_id":"2412.09573","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.09573","snapshot_observed_at":"2026-07-01T22:06:16.914710Z","title":"Freesplatter: Pose- free gaussian splatting for sparse-view 3d reconstruction","venue":null,"work_id":"9b153c5f-41a0-4eb6-9c34-24911a930f71","year":2024},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"cited_paper":"/paper/2412.09573","citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:86e8c6765f4c31c719dee09f228ae0c46dd8e9510d638fbd0ac8776eae66ad4b","observation_id":"d0811f41-739e-45a0-9836-0bb2117003f5","resolution":{"observed_at":"2026-07-01T22:06:16.916195Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"Mvsnet: Depth inference for unstructured multi-view stereo","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:febb2171f0f167bab8029fe4f1a2185eb8dd41e529290ba9e639aa8b851246b1","observation_id":"252fe1d5-97e3-4f28-b9ed-26016ff57925","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2511.07321","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T02:27:49.168609Z","title":"Yonosplat: You only need one model for feedforward 3d gaussian splatting","venue":null,"work_id":"c74dc8a8-a9a5-4820-bc2f-178f184a4986","year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:e206c62a9190b08fa38a3a80d5c5622e4a81edc4241540244784f2e212925da4","observation_id":"e38c99b2-ec6d-4a2b-b5ad-65f1c696c5c8","resolution":{"observed_at":"2026-07-01T22:06:16.910728Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.17835","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T10:46:11.609977Z","title":"arXiv preprint arXiv:2601.17835 (2026)","venue":null,"work_id":"7e223080-6345-469d-8653-97f4b5cbac65","year":2026},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:09a0a1170dcd5ed660e63729210c0c4061d78f9c76c4097302ea0ead37a6f4b3","observation_id":"687dfbea-0a90-4e99-9b0f-9e4e1bd3efd6","resolution":{"observed_at":"2026-07-01T22:06:16.927279Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T15:42:27.248927Z","title":"The unreasonable effectiveness of deep features as a perceptual metric","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:4c1947fdbad5778e804165d1ac89fce5fbf132c14595740cf8db816ca7310307","observation_id":"c1f0e6a9-fcf2-4b6a-aa62-19d30aa4d267","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Applied Intelligence 55, 1118","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:3ea53a71d8381443c14c34a677e7b63042001773852901941ddd9a1340a2c3f1","observation_id":"df9d5649-d18a-4826-b5e1-b6f8d631f2dd","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","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":"2026-06-28T15:42:27.248927Z","title":"Voxel- splat: Dynamic gaussian splatting as an effective loss for occupancy and flow prediction, in: Proceedings of the Computer Vision and Pattern Recognition Conference, pp","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-06-28T15:42:27.248927Z"},"links":{"citing_paper":"/paper/2606.01573"},"observation_digest":"sha256:d11d0ecd96f70dba5dc911e34de4824db3c137d4a09be7667212ec7706baab17","observation_id":"0849dc9e-7273-45f6-a19e-3684cb7fff76","resolution":{"observed_at":"2026-06-28T15:42:27.248927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.01573","last_updated":"2026-06-03T09:16:45Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-03T19:10:31.578056Z","submitted_at":"2026-06-01T02:21:28Z","title":"$\\text{VG}^2$GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":4,"parse_uncertain":0,"unresolved":40,"verified_exact":12,"verified_fuzzy":0},"total_outbound_references":56},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2606.01573."}