{"as_of":"2026-08-09T14:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:97fdc744ab2fd9c2431767ce41ba1f0b8ceb0fad3e33fd4865f1c9095b375e83","coverage":[{"denominator":70,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":70,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:09:48.465236Z","state":"measured"},{"denominator":70,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":70,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2505.19813/citation-record","integrity":"/paper/2505.19813/integrity","json":"/paper/2505.19813/citation-record.json","paper":"/paper/2505.19813"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:57.313823Z","title":"Where and how: Mitigating con- fusion in neural radiance fields from sparse inputs","venue":null,"work_id":"9e6ed72f-b52d-4190-9b77-a4561fa5d5ab","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:40.732270Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:4e1b43165dff08e4e4f37852d4e0f15192f848ecc5de10dcc20e7aca4be473de","observation_id":"40243878-6f05-4fbd-b07a-06d263f3cef1","resolution":{"observed_at":"2026-08-07T14:09:57.378552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:40.822381Z","title":"Mip-nerf: A multiscale representation for anti-aliasing neu- ral radiance fields","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:40.822381Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:98401473c3853593a8a2891f941a4f933d40148376bd2b86f53ded1306ff43df","observation_id":"f549ffd7-30e2-4e3d-8bc4-590adf190e5c","resolution":{"observed_at":"2026-08-07T14:09:40.822381Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:40.869558Z","title":"Mip-nerf 360: Unbounded anti-aliased neural radiance fields","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:40.869558Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:b11d8c57fd52f2a29aad6b74ccdde7c2340205030a4809cd89ac3c7c3bbabc78","observation_id":"6bbb6bec-b890-4804-b9cf-1a667b0ad8b4","resolution":{"observed_at":"2026-08-07T14:09:40.869558Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:40.944979Z","title":"Zip-nerf: Anti-aliased grid-based neural radiance fields","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:40.944979Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:8677a0b02141c7041e2c17b2bb23238984c1178cf4a0c6dc8815db63c426ea7e","observation_id":"afd37a39-f096-451a-9bc9-4aafe78d3941","resolution":{"observed_at":"2026-08-07T14:09:40.944979Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:57.120389Z","title":"pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction","venue":null,"work_id":"699ba7aa-29b3-448b-9450-bff0c6448366","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.016372Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:c7f1229b3355aa7edad1cb573292589936905092d9cbc83a5ee08943db0b9108","observation_id":"3c08dc13-c831-4dc2-bf6a-feab40d944b1","resolution":{"observed_at":"2026-08-07T14:09:57.175026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:41.092788Z","title":"Mvsnerf: Fast general- izable radiance field reconstruction from multi-view stereo","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.092788Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:30bc916ca9ca41b54576d2c91b3e87a4175d5c787ddc6ee3e4e1003be68bfa20","observation_id":"fbe0a8e1-1c49-4e93-9a45-516316587497","resolution":{"observed_at":"2026-08-07T14:09:41.092788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:41.216098Z","title":"Tensorf: Tensorial radiance fields","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.216098Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:638d626800af3f5a51b8773a990d0b8e27f49d05609885aa5f71230715b18583","observation_id":"6c5359f8-5f0b-49f3-99dd-c6a64e0b615a","resolution":{"observed_at":"2026-08-07T14:09:41.216098Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12294","last_updated":"2025-08-22T17:46:35Z","snapshot_observed_at":"2026-08-09T01:41:31.765617Z","submitted_at":"2023-04-24T17:46:01Z","title":"Explicit Correspondence Matching for Generalizable Neural Radiance Fields","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12294","snapshot_observed_at":"2026-08-07T14:09:41.302381Z","title":"Explicit correspondence matching for generalizable neural radiance fields.arXiv preprint arXiv:2304.12294, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.302381Z"},"links":{"cited_paper":"/paper/2304.12294","citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:57f193e1e601bc502cc56e43ef8d6c40279c495c6ddf0b9db578d4c9291f8673","observation_id":"fd1e9693-9564-476c-9a9d-d41e7089106f","resolution":{"observed_at":"2026-08-07T14:09:41.302381Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:56.919766Z","title":"Mobilenerf: Exploiting the polygon ras- terization pipeline for efficient neural field rendering on mo- bile architectures","venue":null,"work_id":"e01f53e2-d706-4e31-b468-ef5bb6fd5bc9","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.399915Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:c6d1198a5145218d5168f7d87b2f74a4c22fa576f4e998e8106468a15d17d03a","observation_id":"ab879746-f5f7-4c81-b527-7f171c1bb0d7","resolution":{"observed_at":"2026-08-07T14:09:57.011632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:56.763568Z","title":"Stereo radiance fields (srf): Learning view syn- thesis for sparse views of novel scenes","venue":null,"work_id":"b621469e-fab7-4e5f-aa5b-2de35f7b5b29","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.541568Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:6e78ad899aacfbdf6985c866caa43eed4de32c1d51bf10c61fe6feb8c5b2a108","observation_id":"edb2ab76-d737-4f22-b067-f06724fe6d49","resolution":{"observed_at":"2026-08-07T14:09:56.820549Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:56.584870Z","title":"Enhancing nerf akin to enhancing llms: Generalizable nerf transformer with mixture-of-view-experts","venue":null,"work_id":"20a05fd6-dcee-45b9-a2d3-bbd3a6d09ec6","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.652081Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:266577ff13a6f6df3f75cc5a9332b7967364639f64b4307ce48e88dca2011c4a","observation_id":"5f5e45d3-2a43-4f11-afc9-7cb3001d4610","resolution":{"observed_at":"2026-08-07T14:09:56.675107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:56.465936Z","title":"Depth-supervised nerf: Fewer views and faster train- ing for free","venue":null,"work_id":"5e0ed86f-b51b-4289-9e56-efa3fdae62a0","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.773124Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:8e9e873ebc90473c85cd9d798feab739c3ad06c19966ed7a656757bd13021c5e","observation_id":"41d65586-e746-4684-a58d-3432dddb0fab","resolution":{"observed_at":"2026-08-07T14:09:56.531129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:41.872915Z","title":"Google scanned objects: A high- quality dataset of 3d scanned household items","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.872915Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:b3d2ee6a561eb15fefcce739ca092b62c98f48389639af0b9374b420f2fbbc2d","observation_id":"4263e8b1-14a1-4127-8286-7cd0d3c7eaca","resolution":{"observed_at":"2026-08-07T14:09:41.872915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:56.321415Z","title":"Deepview: View synthesis with learned gra- dient descent","venue":null,"work_id":"b5c4add5-b26f-4109-8b8f-270c70e96431","year":2019},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:41.994224Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:ad4006561778297d6c354fda7c996978c5ecf58926d4f6b8ebf09eb7841fa391","observation_id":"31277b93-56cb-4649-9cd4-8f6c71a3a0a5","resolution":{"observed_at":"2026-08-07T14:09:56.366960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:56.160266Z","title":"Surfelnerf: Neu- ral surfel radiance fields for online photorealistic reconstruc- tion of indoor scenes","venue":null,"work_id":"db05513e-9f1c-4b83-9031-367268fc8399","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.070391Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:6890ebf41ca64820335fef80511e227a9c1077b5d05747aa4a412dff0376829e","observation_id":"3cf73789-9547-4200-9301-4a6c7cf3d1e9","resolution":{"observed_at":"2026-08-07T14:09:56.210495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:56.042967Z","title":"Baking neural ra- diance fields for real-time view synthesis","venue":null,"work_id":"0eb10b35-77d1-40fc-a27f-8aaf9b73dd7e","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.221177Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:fddf8a6fef15733d5389b90bf528305a790915b5b9f95f809d5ffa4eddb9673a","observation_id":"532d5b4f-63a0-4d2e-8db3-99d21a146c4c","resolution":{"observed_at":"2026-08-07T14:09:56.099871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:42.283329Z","title":"Tri-miprf: Tri-mip represen- tation for efficient anti-aliasing neural radiance fields","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.283329Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:8199df202dab9688bd65c9dfd0dc0d2e8a26790197d2c0a0e46f46d0458fb5c7","observation_id":"dbeb9a2b-1bda-43cd-bda8-c4a40c11abfc","resolution":{"observed_at":"2026-08-07T14:09:42.283329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:55.828552Z","title":"Local implicit ray function for gener- alizable radiance field representation","venue":null,"work_id":"108d9392-74d2-4c4b-a4c9-3e1b12e2598c","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.418609Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:25267a42982802dcb1840359393d8648a155023cdc6578197b02cb30d98c81e5","observation_id":"3a8d7758-e95b-48de-aa5c-6b71bd2b5281","resolution":{"observed_at":"2026-08-07T14:09:55.918499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:55.670117Z","title":"Putting nerf on a diet: Semantically consistent few-shot view synthesis","venue":null,"work_id":"80fa8472-8eb0-4c9c-9c4a-90415adb4ff0","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.538177Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:3381d0df85e113c1a37c7bac246c0dafffd58c35e305bdfec5a10322fb795cce","observation_id":"864d40f6-b07e-44a1-8dae-2a16974ce392","resolution":{"observed_at":"2026-08-07T14:09:55.751731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:55.478455Z","title":"Lvsm: A large view synthesis model with minimal 3d inductive bias, 2024","venue":null,"work_id":"e0d0f8dd-a5b7-4780-9e7c-5f8c9fe574b2","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.686569Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:5168c6d0ebd2a3d21c60216226c99e50d96af9ae676fb2c51824c1675e54f103","observation_id":"4606dd29-3850-453a-b14d-3b19ed1b0c1b","resolution":{"observed_at":"2026-08-07T14:09:55.564006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:55.309481Z","title":"Geonerf: Generalizing nerf with geometry priors","venue":null,"work_id":"cfd00f03-cd78-4694-b985-2eb33911a7ab","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.804368Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:b4806821ab6974cf4995bf08744343db293600aa64a964ba53f0a3ca294e79fe","observation_id":"08a8663c-fb32-4b34-96a5-e662d35bb4be","resolution":{"observed_at":"2026-08-07T14:09:55.378914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:55.105707Z","title":"Ray tracing volume densities.ACM SIGGRAPH computer graphics, 18(3):165– 174, 1984","venue":null,"work_id":"7d4df83e-a659-4ad5-a026-a25a2298e7b1","year":1984},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.904965Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:d8be2c69cebf2cc380ccda0891bbafe73a55c638823773255269efabbe72b706","observation_id":"5a5c67ea-5fcc-477e-823d-718c6d2d117d","resolution":{"observed_at":"2026-08-07T14:09:55.199874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:54.954171Z","title":"Viewformer: Nerf-free neural rendering from few images using transformers","venue":null,"work_id":"a76fea73-59c6-4d3c-bf47-de8d2d6aab3c","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:42.991026Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:020dea3c40273cff8b263f2cb09afab78e6e6070fb101c2f03a957c899eca721","observation_id":"11ffd298-848c-436b-ac5c-75f3cc66a5a1","resolution":{"observed_at":"2026-08-07T14:09:54.997464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10941","last_updated":"2023-04-27T05:34:01Z","snapshot_observed_at":"2026-07-06T14:44:45.326057Z","submitted_at":"2023-01-26T05:14:12Z","title":"GeCoNeRF: Few-shot Neural Radiance Fields via Geometric Consistency","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10941","snapshot_observed_at":"2026-08-07T14:09:43.129631Z","title":"Gecon- erf: Few-shot neural radiance fields via geometric consis- tency.arXiv preprint arXiv:2301.10941, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.129631Z"},"links":{"cited_paper":"/paper/2301.10941","citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:f66183a29dc9b177f499be8ec3b696cdbe9fdab6f675d114abba1275a0a0b6fe","observation_id":"bee9787d-9167-45d0-aa14-a167702deb8c","resolution":{"observed_at":"2026-08-07T14:09:43.129631Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:54.748338Z","title":"Mine: Towards continuous depth mpi with nerf for novel view synthesis","venue":null,"work_id":"d17a9863-41bd-41fe-81ca-82880bfbfe9a","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.235956Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:e623f4b154b5323b869ee50feeda62a07b86af0a4ecad499b9e2643be122956c","observation_id":"0609e81a-e87a-457a-9dab-f9bfa2e1a241","resolution":{"observed_at":"2026-08-07T14:09:54.844987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:54.614393Z","title":"Feature pyramid networks for object detection.IEEE Computer Society, 2017","venue":null,"work_id":"2771dfce-e171-447d-9b48-991144452389","year":2017},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.295895Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:821e2a11b4063f5f1e3f6a6e10241ef36270e3279c658e9e712f0df4ad326cde","observation_id":"6fbb0c9c-b4fa-4459-b018-26ba20c43f61","resolution":{"observed_at":"2026-08-07T14:09:54.683703Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:54.452857Z","title":"Editing condi- tional radiance fields","venue":null,"work_id":"bb694258-4905-44dc-8f3a-f32562cb4286","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.445224Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:a88cbaa3b969dfeae95f8bef266ece3ca7adb697a304b68dfa1f9ce6177e3e7c","observation_id":"c4b1a8b7-12d9-4aed-a7a0-9aa3793b409b","resolution":{"observed_at":"2026-08-07T14:09:54.531079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:54.286134Z","title":"Mvsgaussian: Fast generalizable gaussian splatting recon- struction from multi-view stereo","venue":null,"work_id":"fcfab63d-65e1-4dd8-9061-cdb0a9278e96","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.569474Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:b3c8507beb4477fae2d5d4490d7e916bb9e7bc0a91e23d4363bcebf5de69fe08","observation_id":"dff1e373-efa0-47c9-9088-4fb102efb4b0","resolution":{"observed_at":"2026-08-07T14:09:54.377857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:43.666072Z","title":"Neural rays for occlusion-aware image-based render- ing","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.666072Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:002b74f7f4a7c7719b1c35c9261e5cc298f82abfe85e65554537981d48a48323","observation_id":"277e596e-5128-4dbc-ae5c-3f05ef1e8160","resolution":{"observed_at":"2026-08-07T14:09:43.666072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:54.099283Z","title":"Local light field fusion: Practical view syn- thesis with prescriptive sampling guidelines.ACM Transac- tions on Graphics (ToG), 38(4):1–14, 2019","venue":null,"work_id":"7507bda6-0f6d-4e6e-a77b-0dbb617d391c","year":2019},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.766989Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:267372087b871a0757b25973facc19f53efc4514c058a5df356140b7f3b8f010","observation_id":"e433dc71-d27e-4d00-89d8-b90450ea7e7e","resolution":{"observed_at":"2026-08-07T14:09:54.178351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:43.915268Z","title":"Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:43.915268Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:08fb4250f5a23cd6e1e85b07059cef26ee96b6fe9ce12fbee5693a65a168de67","observation_id":"2aca162f-ddba-45b1-a7f9-11a0b53a43cc","resolution":{"observed_at":"2026-08-07T14:09:43.915268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:53.892067Z","title":"Entangled view-epipolar information aggregation for generalizable neural radiance fields","venue":null,"work_id":"ab8e988b-b1c8-4b51-a58a-10a797611715","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.026549Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:48cf39168873352d8e8ba0c1769e4deaf1d1b1d96061d9e76619b3fbb8cdd04f","observation_id":"d583025f-bf6b-4510-9e69-7ee9dc14c304","resolution":{"observed_at":"2026-08-07T14:09:53.974597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:53.737516Z","title":"Reg- nerf: Regularizing neural radiance fields for view synthesis from sparse inputs","venue":null,"work_id":"563b5b98-3e95-47f2-be21-9914de6f0704","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.154446Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:89af2b0b072b9a6cf874604d154712119d28f8e4b34900869b659d7bba48f4a6","observation_id":"27c30f82-70c7-4556-b6e7-e05563996b3e","resolution":{"observed_at":"2026-08-07T14:09:53.815930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:53.549102Z","title":"Merf: Memory-efficient radiance fields for real- time view synthesis in unbounded scenes.ACM Transactions on Graphics (TOG), 42(4):1–12, 2023","venue":null,"work_id":"e5b7942a-fd2e-4f03-a232-f2d093b08e3e","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.227239Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:a78b7ce065969bc9bab9294c80b100a88c4c0a5c6ed87482f251f7aa3cee546f","observation_id":"b0a54456-d2cc-485f-8cd0-f712bb9190c5","resolution":{"observed_at":"2026-08-07T14:09:53.658415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:53.433546Z","title":"Com- mon objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction","venue":null,"work_id":"247d7797-ac31-4fd8-b0fe-3a5f6462a5ac","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.305656Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:b67409f086d0138d767fbcba7961b3c5f96bcdb26ac8002e544f2c9588ac7960","observation_id":"e08ffbc1-e2c8-4b87-8fb1-c975433412bb","resolution":{"observed_at":"2026-08-07T14:09:53.490943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:53.270392Z","title":"Dense depth pri- ors for neural radiance fields from sparse input views","venue":null,"work_id":"4520f5eb-1a72-453f-a756-ea8e9529f9ac","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.447217Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:02536ec6d91966f079dc9c8cccfb3d4ee177fd9c9df99f17fc379e5e4febc514","observation_id":"7e94a87e-90ac-4538-8923-c6f59c2e15f4","resolution":{"observed_at":"2026-08-07T14:09:53.364295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:53.042254Z","title":"Scene representation transformer: Geometry-free novel view syn- thesis through set-latent scene representations","venue":null,"work_id":"eadba271-16e6-4292-8f3c-31c5a4b1dbd8","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.558989Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:0785fe8044db7c371b9c92ae319b713bbb8ae9a7ac3780e4a1acce1815229b9e","observation_id":"58bf4efe-39ca-4d91-9967-f7e4b29e06e8","resolution":{"observed_at":"2026-08-07T14:09:53.146639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:52.899060Z","title":"Generalizable patch-based neural render- ing","venue":null,"work_id":"d0d04e82-3f79-4586-9fcf-8a23d4a28c54","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.657603Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:4d072de8a2d399512d93f492ddbaa0dfd15be2a03b8e1371b309191f20485347","observation_id":"f7432d1a-cd20-4612-aaad-1d7c41be391f","resolution":{"observed_at":"2026-08-07T14:09:52.959238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:44.766793Z","title":"Light field neural rendering","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.766793Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:d91dcc242a1c3d99777dc4a19ca5d88097b1f0c91ce569d47cdc4b347a2eb365","observation_id":"d633c245-e4dd-4b86-baae-704644bfb084","resolution":{"observed_at":"2026-08-07T14:09:44.766793Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:52.714917Z","title":"Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction","venue":null,"work_id":"87b63e19-1485-403f-b8fa-e4639fabda0a","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.887494Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:d417611cc493ffc7c328e9619f498222fdb2e25ec25f74ba3afe61f94c3f40d0","observation_id":"976178ca-df03-44cf-aaad-d9744a9b3455","resolution":{"observed_at":"2026-08-07T14:09:52.810226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:52.539476Z","title":"Fenerf: Face editing in neural radiance fields","venue":null,"work_id":"2efba0a9-6417-451a-80fc-801a1252b97b","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:44.992750Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:50278bf34823dfc51d062cd87f7edae5f5efeb1243a558dbffd3e839f3a8b158","observation_id":"ca6293b5-7e39-4918-b446-5e8381167caa","resolution":{"observed_at":"2026-08-07T14:09:52.614411Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:52.358158Z","title":"Recent advances in im- plicit representation-based 3d shape generation.Visual Intel- ligence, 2(1):9, 2024","venue":null,"work_id":"2b791310-a4ae-4202-9ff1-20fc4993b0bf","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.054609Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:40c88007a43a47303284d0a5900143d0ac6003a596141b8d767157b49cf87481","observation_id":"7c58bbe5-06e3-4532-a993-9eea9b1d96ef","resolution":{"observed_at":"2026-08-07T14:09:52.434861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:52.201093Z","title":"Splatter image: Ultra-fast single-view 3d recon- struction","venue":null,"work_id":"8fa58fa5-8e56-4833-9335-0edf1b2a2da2","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.136837Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:836bb9d57ea48031b71882cd773dfd40b99340bd19feac7811d005d7f011bd1c","observation_id":"00b50891-3e4d-415d-abdc-61e15c9cc9e5","resolution":{"observed_at":"2026-08-07T14:09:52.254649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:52.014014Z","title":"Image denoising by adaptive kernel regression.Circuits Systems & Computers .conference Record.asilomar Conference on, 2005, 2005","venue":null,"work_id":"62f0e528-a8bb-4f08-bac9-174a9f118c1e","year":2005},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.262225Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:78e3f5c609b0ca56eac4488d3ad5b2da4c8766d607759875aea2472ce174d452","observation_id":"bc918ae8-0103-4df1-a486-10cf62f1a16c","resolution":{"observed_at":"2026-08-07T14:09:52.116488Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:51.854379Z","title":"Ro- bust kernel regression for restoration and reconstruction of images from sparse noisy data.IEEE, 2006","venue":null,"work_id":"6d150e29-e94d-4eb6-ac3d-980a23eff54c","year":2006},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.398903Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:e8d11fa7ed6178c09d0af2144cc6d0e007864f757b8e93a9d9667d612d939b6a","observation_id":"edf80675-8513-4edb-bb31-7e730e103190","resolution":{"observed_at":"2026-08-07T14:09:51.938215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:51.664030Z","title":"Takeda, S","venue":null,"work_id":"7476cc25-c306-43fb-a3c6-3a09796a644c","year":2007},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.568021Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:091908e7f1993eb3175af075647b9837fbb9a6be2f5f660aa8640688ee71575e","observation_id":"f385e9db-8468-4a80-9744-f627d3a9a398","resolution":{"observed_at":"2026-08-07T14:09:51.753047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:51.505266Z","title":"Grf: Learning a general radi- ance field for 3d representation and rendering","venue":null,"work_id":"6f5ecb57-8c8d-4e42-88ae-b5168cb0293e","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.660608Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:143941a935f5df2499f9f3ff9cc3ed79ccc0302ac2de7a15f4705f3509f335f5","observation_id":"415dc863-1a52-4fdb-a743-7706a97991aa","resolution":{"observed_at":"2026-08-07T14:09:51.579196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:51.298417Z","title":"Maxvit: Multi-axis vision transformer.arXiv e- prints, 2022","venue":null,"work_id":"b3e0cec5-60d2-4d8a-81e4-f10cd2d57c7d","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.795268Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:e6f686f8241a77c3543318f6bf22e3c7413814e19fdef638133a6dd8125ce35e","observation_id":"768332d8-94a5-4c89-8c5e-dcc36af3c608","resolution":{"observed_at":"2026-08-07T14:09:51.406565Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:51.079091Z","title":"Is attention all that nerf needs? InThe Eleventh International Confer- ence on Learning Representations, 2022","venue":null,"work_id":"2a542594-ff93-49a8-8c63-da0835de106e","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:45.900141Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:a783192fee0967d806af6d7f3c9efe49ed59607d21edb5ccbbd7b899e778c9e6","observation_id":"d69eee82-9ed6-4342-930f-01166ec7e9e7","resolution":{"observed_at":"2026-08-07T14:09:51.182524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:46.014172Z","title":"Attention is all you need.Advances in neural information processing systems, 30, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.014172Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:8a74cac8f8b018a265f73a664a7185695d678198ef0f75792143cef8aaa22990","observation_id":"e3f08b26-5254-4ae4-97b9-674f4edcdc8a","resolution":{"observed_at":"2026-08-07T14:09:46.014172Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.04650","last_updated":"2023-01-11T18:59:56Z","snapshot_observed_at":"2026-07-06T14:40:27.937537Z","submitted_at":"2023-01-11T18:59:56Z","title":"Geometry-biased Transformers for Novel View Synthesis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.04650","snapshot_observed_at":"2026-08-07T14:09:46.096273Z","title":"Geometry-biased transformers for novel view synthesis.arXiv preprint arXiv:2301.04650, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.096273Z"},"links":{"cited_paper":"/paper/2301.04650","citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:8e8c575e023eeefc3ca94511d64c444605de71658e1b7374a1206d6975f7d611","observation_id":"ab751eb0-b5da-4bb1-87ca-2d2ed287cc3d","resolution":{"observed_at":"2026-08-07T14:09:46.096273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:50.881828Z","title":"Clip-nerf: Text-and-image driven manip- ulation of neural radiance fields","venue":null,"work_id":"cabf065d-9a91-4291-9c77-e08407ba2716","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.269471Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:aaab1b156e73bf94402f59b74f7177a4a053e820211ec8ebcffbf1154372efd9","observation_id":"47441541-2ee4-4029-995e-c703cf3cb81c","resolution":{"observed_at":"2026-08-07T14:09:50.979540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.05375","last_updated":"2022-06-10T23:16:43Z","snapshot_observed_at":"2026-07-06T13:19:40.561842Z","submitted_at":"2022-06-10T23:16:43Z","title":"Generalizable Neural Radiance Fields for Novel View Synthesis with Transformer","version":1},"cited_work":{"arxiv_id":"2206.05375","doi":null,"metadata_source":"pith","pith_arxiv_id":"2206.05375","snapshot_observed_at":"2026-08-07T14:09:48.634158Z","title":"Generalizable Neural Radiance Fields for Novel View Synthesis with Transformer","venue":"cs.CV","work_id":"2fd92e4a-d810-40ad-9ee6-395a00292ece","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.394076Z"},"links":{"cited_paper":"/paper/2206.05375","citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:802610e781b2ac627cb63fdc61e87625404bf34f5087d3748d6ba06073c2eb8b","observation_id":"5d5ac4b0-8af0-47d3-b60c-bcdba53b2416","resolution":{"observed_at":"2026-08-07T14:09:48.699919Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:50.730310Z","title":"Sparsenerf: Distilling depth ranking for few-shot novel view synthesis","venue":null,"work_id":"33e8719a-d247-4295-adce-df61bf8649dd","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.534510Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:f58c37db7d97152964eaa9c264fe35da6c274191418e525e65557202347316f7","observation_id":"330c6b33-cc26-4681-bb88-7c9fffd3dfc9","resolution":{"observed_at":"2026-08-07T14:09:50.798246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:46.657060Z","title":"Ibr- net: Learning multi-view image-based rendering","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.657060Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:b371916bbd0d49263b3c2cf9c4e6ff31bcf3f105ed79fb8548f7c6ebf82295f6","observation_id":"ee31a5e6-e1e6-4ec0-b0bc-b0f40901954d","resolution":{"observed_at":"2026-08-07T14:09:46.657060Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:46.776024Z","title":"Image quality assessment: from error visibility to structural similarity.IEEE transactions on image processing, 13(4):600–612, 2004","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.776024Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:528f6051fdf551333f072ee4e68ef196a5915b76b5f26250a261c4b85063cda1","observation_id":"10d85e54-e55c-459a-ab06-d265b5e264a9","resolution":{"observed_at":"2026-08-07T14:09:46.776024Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:50.523568Z","title":"Nex: Real-time view synthesis with neural basis expansion","venue":null,"work_id":"53b8f7ed-d285-48d4-8bee-080e2cd2090f","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.868399Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:ec5f41dd3b063d380c46cb61423378125a99193f0b7b7986ab7b31c0bad58e7e","observation_id":"4f905b52-4870-44a7-bbb8-202b96507397","resolution":{"observed_at":"2026-08-07T14:09:50.628354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:50.335278Z","title":"Neutex: Neural texture mapping for volumetric neural rendering","venue":null,"work_id":"ae4fa8e0-1f4d-4852-bcb3-cd41e894aa37","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:46.950487Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:2840402e82f95bc2e28fea67708c41007808abee7ad051eb3b162b5837c243d9","observation_id":"82bf9bdb-d1a1-4cee-bfb7-d9d0d779f0b9","resolution":{"observed_at":"2026-08-07T14:09:50.420530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:50.157391Z","title":"Sinnerf: Training neural radiance fields on complex scenes from a single image","venue":null,"work_id":"3ce936f4-14fe-456c-ad0a-95e275a67d2e","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:47.054494Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:b0bd154e0f5a770bfa4650157a7cb6dd7901478110b372036cce291e570515b9","observation_id":"f2be882d-86fd-427e-96b8-d67a394dc90d","resolution":{"observed_at":"2026-08-07T14:09:50.203688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:47.206289Z","title":"Murf: Multi-baseline radiance fields","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:47.206289Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:fe7a8ebfac0c97f6598afaacc9792ef384c4955585b220b943c709903a8a1da4","observation_id":"a0ea6a28-2e0e-4c37-a304-6022ae2e3312","resolution":{"observed_at":"2026-08-07T14:09:47.206289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:49.950427Z","title":"Deforming radiance fields with cages","venue":null,"work_id":"de028634-08cc-4ab8-815f-095a5598ca32","year":2022},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:47.327648Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:bc5094228c01fe3a4e6346ae42385d5fa4242712151054a245c0ac025214ea8a","observation_id":"3e4b3ad5-ae79-48b1-923e-e3dfe977b85e","resolution":{"observed_at":"2026-08-07T14:09:50.024098Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:49.780529Z","title":"Contranerf: Gen- eralizable neural radiance fields for synthetic-to-real novel view synthesis via contrastive learning","venue":null,"work_id":"4d4a59e7-a39a-419e-ad09-45e0e8506e0d","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:47.458270Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:c7fa8961e230254601481afa349b6bacceee2e6ac571b6b919607b421acae1b6","observation_id":"1fa52343-9dd4-4798-94ed-a31f8a867f92","resolution":{"observed_at":"2026-08-07T14:09:49.859788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:49.629095Z","title":"Freenerf: Im- proving few-shot neural rendering with free frequency reg- ularization","venue":null,"work_id":"3469d69c-6fd7-4939-aa83-02967edfa6a5","year":2023},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:47.574661Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:6ff3e87e4aff0119693a1fed53f9442d5f0854e61ff487a1eaa51fe84fafd1d8","observation_id":"02539d17-515a-4dde-956b-15eb5720c7f7","resolution":{"observed_at":"2026-08-07T14:09:49.694069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:47.733129Z","title":"Plenoctrees for real-time rendering of neural radiance fields","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:47.733129Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:88fe76443b2cf15e9f8ecea51049324262b4fe3f517cf0145f6660c48e9fbb8e","observation_id":"103adec0-4494-46f1-8971-9e104a114204","resolution":{"observed_at":"2026-08-07T14:09:47.733129Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:47.895522Z","title":"pixelnerf: Neural radiance fields from one or few images","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:47.895522Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:57e2b21cf7ae7badd7679b683df15173be94b6ee5796bb811b1d018621ad3781","observation_id":"4b8e83b6-b37d-41ce-8f52-5e9811ca446a","resolution":{"observed_at":"2026-08-07T14:09:47.895522Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:49.383192Z","title":"Ners: Neural reflectance surfaces for sparse-view 3d reconstruction in the wild.Advances in Neural Informa- tion Processing Systems, 34:29835–29847, 2021","venue":null,"work_id":"08a9222a-5c31-4131-8a5a-045732929520","year":2021},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:48.027225Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:2890ca26c6a7556212961fd79b9f26fd9ed29d948676bb9c591459f8b09d755d","observation_id":"314e6a37-55e5-41db-a335-d00e63eb4aa6","resolution":{"observed_at":"2026-08-07T14:09:49.518352Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T14:09:48.141400Z","title":"The unreasonable effectiveness of deep features as a perceptual metric","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:48.141400Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:ba54e253eb58008387ade32817b44fa724dbaf6316b7a63ff8d587392e00cd41","observation_id":"e062502b-c820-4a04-b9de-a3a6d24ebebe","resolution":{"observed_at":"2026-08-07T14:09:48.141400Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:49.124502Z","title":"Gps- gaussian: Generalizable pixel-wise 3d gaussian splatting for real-time human novel view synthesis","venue":null,"work_id":"df6195b8-33d3-406f-9a78-e08dcfac6389","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:48.251174Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:112ee3360a38986e888a0713ad8824954dbd7d7e11ed952e3ae1162fec097bdf","observation_id":"850ab491-c77d-42f0-b337-199e21c6d665","resolution":{"observed_at":"2026-08-07T14:09:49.234343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.09817","last_updated":"2018-05-24T17:58:02Z","snapshot_observed_at":"2026-07-06T06:41:05.545426Z","submitted_at":"2018-05-24T17:58:02Z","title":"Stereo Magnification: Learning View Synthesis using Multiplane Images","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.09817","snapshot_observed_at":"2026-08-07T14:09:48.337527Z","title":"Stereo magnification: Learning view synthesis using multiplane images.arXiv preprint arXiv:1805.09817, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:48.337527Z"},"links":{"cited_paper":"/paper/1805.09817","citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:82ef05dcdc5f00c4f91b6e09e4069745a5d9a91b3514097abb9e75cf82bc6fda","observation_id":"27015c21-2d05-4bb2-a129-9c927c651384","resolution":{"observed_at":"2026-08-07T14:09:48.337527Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:09:48.894867Z","title":"Caesarnerf: Calibrated semantic representation for few-shot generalizable neural rendering","venue":null,"work_id":"ac9d2dab-093b-406c-9ef5-f71f6ed8e0c7","year":2024},"citing_paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:48.465236Z"},"links":{"citing_paper":"/paper/2505.19813"},"observation_digest":"sha256:603cdcbf8e4a7d0dad78efd53b1335d5275eb09d2eca76e4e3d840592476274f","observation_id":"e5805d11-af44-4e8c-910c-9f0830c7e420","resolution":{"observed_at":"2026-08-07T14:09:49.005212Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.19813","last_updated":"2025-05-26T10:50:25Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T04:47:46.239847Z","submitted_at":"2025-05-26T10:50:25Z","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis"},"reference_resolution":{"displayed":70,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":1,"verified_fuzzy":48},"total_outbound_references":70},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2505.19813."}