{"as_of":"2026-08-10T01:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5262ef55408baa9c7f7bc5363f2c90149e3296c1e03a42792f3048d527ce0386","coverage":[{"denominator":54,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T20:23:25.451131Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"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/2509.08685/citation-record","integrity":"/paper/2509.08685/integrity","json":"/paper/2509.08685/citation-record.json","paper":"/paper/2509.08685"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T20:23:22.388533Z","title":"A volumetric approach to point cloud compression—part i: Attribute compres- sion,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.388533Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:ff8c28a9f9af88df5e27d0ec40daaccad2e4cb80ff5936b04182c01d6393c539","observation_id":"3f7572ba-6f7d-42d2-a25e-225b9d0727a9","resolution":{"observed_at":"2026-08-04T20:23:22.388533Z","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":"2026-08-04T20:23:22.455907Z","title":"Compression of 3d point clouds using a region-adaptive hierarchical transform,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.455907Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:6e74522677d10774ae59aa6acbd65044f761665c926280e23e5e9436b512d121","observation_id":"0b348a88-8124-4b17-a17d-c44d7a65c65d","resolution":{"observed_at":"2026-08-04T20:23:22.455907Z","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":"2026-08-04T20:23:22.533895Z","title":"Integer alternative for the region-adaptive hierarchical trans- form,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.533895Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:dad36da5fcba998c555f9a9624d52cbd01c4477445b5768d16bc3d78282170de","observation_id":"34ad5b80-ddac-4031-a76b-81ac4ed65c63","resolution":{"observed_at":"2026-08-04T20:23:22.533895Z","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":"2026-08-04T20:23:22.585420Z","title":"Emerging MPEG standards for point cloud compression,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.585420Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:211d7e1eba87b942bc671cbddc1c7e2f738519c4fdd70c871ed732761ba55999","observation_id":"5a66d3b1-8768-4756-aad4-6db7d56c5f66","resolution":{"observed_at":"2026-08-04T20:23:22.585420Z","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":"2026-08-04T20:23:22.684900Z","title":"Saad,Iterative methods for sparse linear systems","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.684900Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:89cba752902b705476ecc91b8bcb9f46d879d02944301a578ddda4b6b25f23e8","observation_id":"92d0c56e-5bad-4b3d-9d0c-032c53207546","resolution":{"observed_at":"2026-08-04T20:23:22.684900Z","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":"2026-08-04T20:23:22.739823Z","title":"Proximal algorithms,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.739823Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:a417adc1dba18a648437df23f0e924198343ce1501cf6455392cd0e537d5b812","observation_id":"311093f8-ef98-4124-aad5-df8113832935","resolution":{"observed_at":"2026-08-04T20:23:22.739823Z","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":"2026-08-04T20:23:22.805673Z","title":"Nonlinear transform coding,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.805673Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:256c59983523f07e165d3e8c4938fea110dfe76c0f1b1571ddbca308a5aac4b0","observation_id":"cc95e99c-7d8c-465e-9e7a-19828e84363b","resolution":{"observed_at":"2026-08-04T20:23:22.805673Z","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":"2026-08-04T20:23:22.828608Z","title":"On an improvement of RAHT to ex- ploit attribute correlation,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.828608Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:7f68f71a85f4d88315c989f4a517125e06adaae6f369890078a284a44b8641c6","observation_id":"de0d04b0-505c-4001-9511-537f988c575f","resolution":{"observed_at":"2026-08-04T20:23:22.828608Z","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":"2026-08-04T20:23:22.878566Z","title":"Point cloud attribute compression with graph transform,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.878566Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:b96d543cd5cec31b2a9b0564d50f13d2ef12185f8a5c5d5207952a951de7e339","observation_id":"be17ea37-05ff-4400-bb01-9c5bb909842c","resolution":{"observed_at":"2026-08-04T20:23:22.878566Z","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":"2026-08-04T20:23:22.932367Z","title":"Attribute compression for sparse point clouds using graph transforms,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.932367Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:e6c29891ed720c1a17fde90ff0b5a51eec353fd723439c17b7481d2f50f74b02","observation_id":"66e5f3e8-e102-4167-ae8d-b7ff2b450f4d","resolution":{"observed_at":"2026-08-04T20:23:22.932367Z","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":"2026-08-04T20:23:22.957622Z","title":"Spectral folding and two-channel filter-banks on arbitrary graphs,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:22.957622Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:d26edd804a77cde9e6a26126419222b3fb8afab23d789b0a785d8bfe76057161","observation_id":"75e6acde-15a0-458f-bfb1-544d56be5f0a","resolution":{"observed_at":"2026-08-04T20:23:22.957622Z","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":"2026-08-04T20:23:23.004548Z","title":"Ray tracing volume densities,","venue":null,"work_id":null,"year":1984},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.004548Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:2b7660d99f9b810ef7ee92355bcc26d7ee1427e2698a76a4b7718e3f40a522c2","observation_id":"ec3e6bb9-5235-4d82-a50a-16cacd1eaec4","resolution":{"observed_at":"2026-08-04T20:23:23.004548Z","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":"2026-08-04T20:23:23.021793Z","title":"Nerf: Representing scenes as neural radiance fields for view synthesis,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.021793Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:995688833d6e0539890d34bc873ad3fcc2f822375fc9400fd7a9364f7b6942c4","observation_id":"1f7a98cd-9eb2-4657-ab6e-984c9084f707","resolution":{"observed_at":"2026-08-04T20:23:23.021793Z","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":"2026-08-04T20:23:23.071926Z","title":"Ewa splatting,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.071926Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:5ea626186426d446469f8764d8f3c29b1958dd566fa129aad4c2d1e0f82b8acc","observation_id":"8ff9c693-e9cd-45a3-b35d-7d6a5dbd877c","resolution":{"observed_at":"2026-08-04T20:23:23.071926Z","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":"2026-08-04T20:23:23.151308Z","title":"3d gaussian splatting for real-time radiance field rendering","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.151308Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:e4db81dbc77615682a922d73b42a3fcc77f53fc76a76513ce61f043780af6413","observation_id":"6e5069e8-a044-407e-92a9-6a44ca39dd41","resolution":{"observed_at":"2026-08-04T20:23:23.151308Z","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":"2026-08-04T20:23:23.205275Z","title":"Com- pressed 3d gaussian splatting for accelerated novel view synthe- sis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.205275Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:38c1a4de1954859327c66bfda7e7b967a409bcf427879a6c6d33858467f64118","observation_id":"2cf14927-5c61-4960-8726-c2a5b6ff04cc","resolution":{"observed_at":"2026-08-04T20:23:23.205275Z","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":"2026-08-04T20:23:23.269438Z","title":"Mesongs: Post-training compression of 3d gaussians via efficient attribute transformation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.269438Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:bde6ed6aaf334eb66ac1d82e7fb3509b5f94b09e780eb62a8e2613ed0c77275d","observation_id":"c2d92d24-f916-41a8-bfac-7c8ad27f4f8e","resolution":{"observed_at":"2026-08-04T20:23:23.269438Z","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":"2026-08-04T20:23:23.330879Z","title":"Hac: Hash- grid assisted context for 3d gaussian splatting compression,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.330879Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:f118d43163340d9a7fdfbb89efe0e8226be1bc4bb831763ddef51d9e7a3e56a8","observation_id":"7d3485a3-12fb-4ad1-a8fa-3b77caf20bd3","resolution":{"observed_at":"2026-08-04T20:23:23.330879Z","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":"2026-08-04T20:23:23.420216Z","title":"Compgs: Efficient 3d scene representation via compressed gaussian splatting,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.420216Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:7d6eb6a325bb989eca4c14e8a3b7aec3ca2bd2087c2e2a60a2ef932483707e68","observation_id":"8eb5164a-ff3b-429d-a544-427761e7cfb0","resolution":{"observed_at":"2026-08-04T20:23:23.420216Z","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":"2026-08-04T20:23:23.594110Z","title":"Deep learning-based point cloud geometry coding: RD control through implicit and explicit quantization,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.594110Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:66a7ed4092bfc13d4a8872708ca495c4c639ffd3ee16da31b42f56f124b36f92","observation_id":"8d498756-4cac-4505-bf69-3442fa5e7e86","resolution":{"observed_at":"2026-08-04T20:23:23.594110Z","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":"2026-08-04T20:23:23.615235Z","title":"Deep implicit volume compression,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.615235Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:83d17df93914639c380d86378511614ac6a158935029d0e3395524a1c04bbc2c","observation_id":"0a84438d-b8ad-40b4-9297-9f372d61462a","resolution":{"observed_at":"2026-08-04T20:23:23.615235Z","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":"10.1117/12.2569115","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Towards neural network approaches for point cloud compression,","venue":null,"work_id":"48b84ba4-e0f4-4a74-9709-0ed6cac44338","year":2020},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.656472Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:2a03ed6e9d56f5a7e36a594148dcea7599b5a2ce25d2eeec2c9a037ee1258dba","observation_id":"a4f9e28c-a62a-48e3-98de-12191b710006","resolution":{"observed_at":"2026-08-04T20:28:50.024832Z","resolver_source":"doi","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T20:23:23.736374Z","title":"Lvac: Learned volumetric attribute compression for point clouds using coordinate based networks,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.736374Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:3cad0055ec6c771f106af59f8e8b0897c60107b15505dc784ccf091931cf87d3","observation_id":"9280d346-1da5-4308-ae34-86f2e83baa91","resolution":{"observed_at":"2026-08-04T20:23:23.736374Z","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":"2026-08-04T20:23:23.786735Z","title":"Sparse tensor-based point cloud attribute compression,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.786735Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:560c1d809af1a5fadbe61e8afbb6c6072cd0fd39a6bf8f167e6d1d950b51a773","observation_id":"3e4904c3-9186-49bc-8340-8830e7273b04","resolution":{"observed_at":"2026-08-04T20:23:23.786735Z","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":"2026-08-04T20:23:23.813834Z","title":"Scalable point cloud at- tribute compression,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.813834Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:0ba04bc274297eb21a5c7cd96eb7e43fe8877d63e8ad5e3389b72924ce6164bd","observation_id":"b595b473-d7d6-4372-9128-66f06b5024ff","resolution":{"observed_at":"2026-08-04T20:23:23.813834Z","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":"2026-08-04T20:23:23.849231Z","title":"Entropy-constrained vector quantization,","venue":null,"work_id":null,"year":1989},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.849231Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:2af9b08468544fa910859d24c5238422367ca8b9e3366959bf2cfb8b98ef736c","observation_id":"b7d032c3-12cc-4ab3-b1fe-f5275d722874","resolution":{"observed_at":"2026-08-04T20:23:23.849231Z","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":"2026-08-04T20:23:23.939405Z","title":"Variational image compression with a scale hyperprior,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:23.939405Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:4b44c1a7f8c972da1ecd82bf9dda6c908d5e8301a3de4b100922959e68100814","observation_id":"1ef91500-6de5-40fc-b9cf-79a32ae58f75","resolution":{"observed_at":"2026-08-04T20:23:23.939405Z","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":"2026-08-04T20:23:24.089667Z","title":"Algorithm unrolling: Inter- pretable, efficient deep learning for signal and image processing,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.089667Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:ddeb1bcf5185e9921ddf0ad53f1073c24ca7a190ae5de086ee7d742a6074f99c","observation_id":"49b0edad-914d-457b-a5f7-d3007acce536","resolution":{"observed_at":"2026-08-04T20:23:24.089667Z","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":"2026-08-04T20:23:24.117458Z","title":"Learning fast approximations of sparse coding,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.117458Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:088897ab07211b8abddd6d3087df55c9f295181f870fb5e9bf17ae37a116c77d","observation_id":"a73d40f3-de0f-4d8c-adc9-4ed695217aff","resolution":{"observed_at":"2026-08-04T20:23:24.117458Z","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":"2026-08-04T20:23:24.167076Z","title":"White-box transformers via sparse rate reduction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.167076Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:9aff4e2fb2462236fc357dfb19dcf1f93fa9484e0b49a1b1fe981e7d0d58321b","observation_id":"ca8f66bf-1ade-4f83-9d38-12db9ae872e9","resolution":{"observed_at":"2026-08-04T20:23:24.167076Z","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":"2026-08-04T20:23:24.224643Z","title":"Interpretable lightweight transformer via unrolling of learned graph smoothness priors,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.224643Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:031bcc508f8c350251a97ad1a4dc6804d140197a2fb33485bea3ac57a5a3d364","observation_id":"6c136dbe-2e06-48db-a9db-ee2c11e750e8","resolution":{"observed_at":"2026-08-04T20:23:24.224643Z","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":"2026-08-04T20:23:24.312011Z","title":"V olumetric attribute compression for 3d point clouds using feedforward network with geometric attention,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.312011Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:3a6ebf167d90727d0d78b82dbfa6b0a23e8169a34af006fb2fe588563cdcbcaf","observation_id":"dc3d1ea9-6a18-498c-81d4-9800b1bf20da","resolution":{"observed_at":"2026-08-04T20:23:24.312011Z","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":"2026-08-04T20:23:24.371215Z","title":"Learned nonlinear predictor for critically sampled 3d point cloud attribute compression,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.371215Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:a3608de03efa13e7285b2558955e986b14f53af84a1f355e3e1db1a7c91e1f59","observation_id":"2336e457-1c7d-44b6-a8d6-95ed60733ab7","resolution":{"observed_at":"2026-08-04T20:23:24.371215Z","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":"2026-08-04T20:23:24.406706Z","title":"V olumetric 3d point cloud attribute compression: Learned polynomial bilateral filter for prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.406706Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:cd2411d9040cd47a63d648882a089266d6877fb7e5833b804d996e884a12e839","observation_id":"ea9d0e7c-7a49-4c60-ae0c-670ae61b1b66","resolution":{"observed_at":"2026-08-04T20:23:24.406706Z","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":"2026-08-04T20:23:24.451521Z","title":"Equivalence class — Wikipedia, the free encyclopedia,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.451521Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:6b835170666aa28d3a8572bcf8eec55802926d6c2492d1c9a6626acaf39eaebc","observation_id":"a033aa9b-e0be-41bb-a863-8b117f3918f1","resolution":{"observed_at":"2026-08-04T20:23:24.451521Z","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":"2026-08-04T20:23:24.509991Z","title":"Hilbert space — Wikipedia, the free encyclope- dia,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.509991Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:695613c73933530c5445cb768f120aa68424b2160d32a16843dd2ea96bc3b613","observation_id":"40d3120e-819d-4d20-8886-092544f945e7","resolution":{"observed_at":"2026-08-04T20:23:24.509991Z","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":"2026-08-04T20:23:24.604926Z","title":"G-PCC codec description v12,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.604926Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:f6458c772932271dcc80346abf5febc78bc44cc5dd5a476c2dbf37b3588d63d2","observation_id":"88c5b585-098a-4e93-8ea4-3e6c86a15005","resolution":{"observed_at":"2026-08-04T20:23:24.604926Z","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":"2026-08-04T20:23:24.663203Z","title":"Gram matrix — Wikipedia, the free encyclopedia,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.663203Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:a6cac69912e264738cdcbf2eef56b9ced5ffd9a0602de75c9ebdb3a8f1b1792d","observation_id":"aa89ba65-d048-4866-936a-dc2b36dde070","resolution":{"observed_at":"2026-08-04T20:23:24.663203Z","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":"2026-08-04T20:23:24.677340Z","title":"Daubechies,Ten Lectures on Wavelets","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.677340Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:3a51301ebfb2bc71fe919eeaa42c30142882cda67ec2c5f4bb34ee5f2d0a9dd4","observation_id":"9f4d0c4a-e68d-4b85-9803-b08add5d776c","resolution":{"observed_at":"2026-08-04T20:23:24.677340Z","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":"2026-08-04T20:23:24.704821Z","title":"Vetterli and J","venue":null,"work_id":null,"year":1995},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.704821Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:2c75a961899c2def08572b6d3c9a871aaf7c5e653e0f1330fd1e62f836c07f6c","observation_id":"25744736-ad35-47ed-92c5-925434ec1fab","resolution":{"observed_at":"2026-08-04T20:23:24.704821Z","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":"2026-08-04T20:23:24.757701Z","title":"Conjugate gradient method — Wikipedia, the free encyclopedia,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.757701Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:cbed31432e9177fa07a1eac53551aab9bb21494c5a7c1e4abf33834272cf47fe","observation_id":"15d06e17-46e4-4efa-b090-ce557a51bdca","resolution":{"observed_at":"2026-08-04T20:23:24.757701Z","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":"2026-08-04T20:23:24.811117Z","title":"Deepsdf: Learning continuous signed distance functions for shape representation,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.811117Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:c3714f04f38dfd3953a8f39928bd4cdb972de80585c3188474b8f383ace9d72c","observation_id":"139730be-1cfc-47de-8fd8-4de4cc3296fd","resolution":{"observed_at":"2026-08-04T20:23:24.811117Z","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":"2026-08-04T20:23:24.908481Z","title":"Nerf: Representing scenes as neural radiance fields for view synthesis,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.908481Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:937d872a3f67aba294e904b8b8567fb3221de60f9c4ea818ff96e3566cda1a4a","observation_id":"bf40dfa1-b89d-4b18-ab3a-c5ee396da55d","resolution":{"observed_at":"2026-08-04T20:23:24.908481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.08988","last_updated":"2021-11-17T09:11:09Z","snapshot_observed_at":"2026-07-06T12:09:23.278166Z","submitted_at":"2021-11-17T09:11:09Z","title":"LVAC: Learned Volumetric Attribute Compression for Point Clouds using Coordinate Based Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.08988","snapshot_observed_at":"2026-08-04T20:23:24.957583Z","title":"Lvac: Learned volumetric attribute compression for point clouds using coordinate based networks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:24.957583Z"},"links":{"cited_paper":"/paper/2111.08988","citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:98c5819d9f07ea35693ddb57d1efb024a014d72a499ed8c211c43849b55d8aac","observation_id":"2ad34aa5-05d7-46b4-9a08-f989aecd27ce","resolution":{"observed_at":"2026-08-04T20:23:24.957583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.03123","last_updated":"2021-04-10T16:36:00Z","snapshot_observed_at":"2026-08-04T01:48:45.750015Z","submitted_at":"2021-03-03T10:58:39Z","title":"COIN: COmpression with Implicit Neural representations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.03123","snapshot_observed_at":"2026-08-04T20:23:25.016563Z","title":"Coin: Compression with implicit neural representations,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.016563Z"},"links":{"cited_paper":"/paper/2103.03123","citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:d246aa41ffd0992177fef96ecbf27607fb98cdfdba25dd4c81690a2b698dc026","observation_id":"6cd37ca6-1e74-4eeb-8ba9-a0c293a40a1c","resolution":{"observed_at":"2026-08-04T20:23:25.016563Z","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":"2026-08-04T20:23:25.073428Z","title":"D’oh: Decoder-only random hypernetworks for implicit neural representations,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.073428Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:53d799a19d218bae27a907974da50bd2801af42e40a946e26a47aa44eb224590","observation_id":"38b6c897-1b49-4876-bd2a-430757ad2b36","resolution":{"observed_at":"2026-08-04T20:23:25.073428Z","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":"2026-08-04T20:23:25.112356Z","title":"Proximal algorithms,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.112356Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:9df1ff5fd511d99fa2bad04efe8f82ca3101243cbe97a2787c3ae836f001cdec","observation_id":"e072f6e3-1233-495a-a476-69109f2d1b31","resolution":{"observed_at":"2026-08-04T20:23:25.112356Z","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":"2026-08-04T20:23:25.172081Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.172081Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:1c4512a0129de99b4f2de4e20dbb77dba4a2657b14302f2552fc64645cc45ac0","observation_id":"407450e8-b300-4d69-b343-4f3d85a111f2","resolution":{"observed_at":"2026-08-04T20:23:25.172081Z","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":"2026-08-04T20:23:25.223663Z","title":"A fast iterative shrinkage-thresholding algorithm for linear inverse problems,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.223663Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:c21c6cdb2f6428cbe5e089bc4db0914b8677ba4ad70b5f887d7fdb3734650e8a","observation_id":"02a98260-baf8-4039-9507-584c3187d9bf","resolution":{"observed_at":"2026-08-04T20:23:25.223663Z","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":"2026-08-04T20:23:25.285321Z","title":"Multi- resolution intra-predictive coding of 3d point cloud attributes,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.285321Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:d6bba267ba0bb9296799bc5fbc01a0542eceebc00bb7c0aab69a474b03981efb","observation_id":"4889c4d6-0020-42c8-b402-dfda7d5057f4","resolution":{"observed_at":"2026-08-04T20:23:25.285321Z","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":"2026-08-04T20:23:25.327138Z","title":"Adaptive run-length/golomb-rice encoding of quan- tized generalized gaussian sources with unknown statistics,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.327138Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:032a671c70d523c6b7e172d75f66da09bf9e23349fc1a682701eaf9229b980ce","observation_id":"d81c76c4-64a9-410f-bf67-f8e19fc2c949","resolution":{"observed_at":"2026-08-04T20:23:25.327138Z","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":"2026-08-04T20:23:25.376616Z","title":"8i vox- elized full bodies — a voxelized point cloud dataset,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.376616Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:5938f273a73124290991d4e9b28f32a54bb9d46b7a7cdbaf312bd264d0c66497","observation_id":"5cba77bd-c537-45d4-bfbd-83aa92752df6","resolution":{"observed_at":"2026-08-04T20:23:25.376616Z","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":"2026-08-04T20:23:25.422377Z","title":"Peer upsampled transform domain prediction for g-pcc,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.422377Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:4aa3b33afbbbec7bd0969f63de18f0354a0c2b0116ff3228d0c22156a31113e0","observation_id":"679cdcd1-7baf-4512-bf2a-488ebd396c9f","resolution":{"observed_at":"2026-08-04T20:23:25.422377Z","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":"2026-08-04T20:23:25.451131Z","title":"1 + x0 −x x0 + x0 −x x0 2 +· · · # = 1 x0","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-04T20:23:25.451131Z"},"links":{"citing_paper":"/paper/2509.08685"},"observation_digest":"sha256:3c9dfdd7c86d62713765dfdb93b9583f644323e95ad83921efce826d5bb4f205","observation_id":"5d42bdb7-f01c-40c6-9292-ab5bf3c80f87","resolution":{"observed_at":"2026-08-04T20:23:25.451131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.08685","last_updated":"2026-07-14T23:52:31Z","latest_version":2,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-09T09:57:54.798817Z","submitted_at":"2025-09-10T15:23:21Z","title":"Deep Unrolling of Sparsity-Induced RDO for 3D Point Cloud Attribute Coding"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":53,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":54},"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 10 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2509.08685."}