{"as_of":"2026-08-07T22:33:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:775bd0f18cef27056ea8f05c0a2c8e6fd88294c46b7ccf8439e92c33a0ca2824","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:57:15.310716Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T15:58:37.359871Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-08-07T12:57:15.310716Z","title":"Pointocc: Cylindrical tri-perspective view for point-based 3d semantic occupancy predic- tion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23115","last_updated":"2025-07-03T06:55:33Z","snapshot_observed_at":"2026-08-07T12:50:40.403121Z","submitted_at":"2025-05-29T05:34:22Z","title":"Diffusion-Based Generative Models for 3D Occupancy Prediction in Autonomous Driving","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T12:57:15.310716Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2505.23115"},"observation_digest":"sha256:95c67310f53c3686f14c3a2e7c6d5cf33ddc8fe1b6f998e11e3a024bd9f7b387","observation_id":"d01033f5-3d87-4404-8131-1495621982e6","resolution":{"observed_at":"2026-08-07T12:57:15.310716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-08-07T04:19:25.958289Z","title":"Pointocc: Cylin- drical tri-perspective view for point-based 3d semantic occupancy prediction","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10977","last_updated":"2025-06-12T17:59:45Z","snapshot_observed_at":"2026-08-07T04:10:21.770276Z","submitted_at":"2025-06-12T17:59:45Z","title":"QuadricFormer: Scene as Superquadrics for 3D Semantic Occupancy Prediction","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:19:25.958289Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2506.10977"},"observation_digest":"sha256:cf01689229189aa905046c612ed50b568cced20d685e0d7e5a63c99ca325e59b","observation_id":"4a78af71-a75f-4f3b-85fc-04c4da779d65","resolution":{"observed_at":"2026-08-07T04:19:25.958289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-08-06T12:56:39.847772Z","title":"Pointocc: Cylindrical tri-perspective view for point-based 3d semantic occupancy predic- tion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.21358","last_updated":"2025-08-03T22:46:43Z","snapshot_observed_at":"2026-08-06T14:04:59.980600Z","submitted_at":"2025-07-28T21:56:43Z","title":"Collaborative Perceiver: Elevating Vision-based 3D Object Detection via Local Density-Aware Spatial Occupancy","version":4},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T12:56:39.847772Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2507.21358"},"observation_digest":"sha256:9db1b72655b04018ac2c91093c820c4b7e8a2f174be7b6c611359ce3762c47ba","observation_id":"e1b54154-2157-4200-8d79-4209ad7ebf42","resolution":{"observed_at":"2026-08-06T12:56:39.847772Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-07-14T22:26:59.909815Z","title":"pixel-voxel-text","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.12144","last_updated":"2026-07-23T16:36:32Z","snapshot_observed_at":"2026-08-07T06:06:26.373603Z","submitted_at":"2026-03-12T16:45:42Z","title":"O3N: Omnidirectional Open-Vocabulary Occupancy Prediction for Urban Autonomous Agents","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-07-14T22:26:59.909815Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2603.12144"},"observation_digest":"sha256:931bb4686d4ae7754376745920277e0dbaf6273845dfac90ffabb57fd17ba23d","observation_id":"c58a2439-a50a-4983-9c47-3403a8460445","resolution":{"observed_at":"2026-07-14T22:26:59.909815Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-08-02T18:24:22.365030Z","title":"pixel-voxel-text","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2603.12144","last_updated":"2026-07-23T16:36:32Z","snapshot_observed_at":"2026-08-07T06:06:26.373603Z","submitted_at":"2026-03-12T16:45:42Z","title":"O3N: Omnidirectional Open-Vocabulary Occupancy Prediction for Urban Autonomous Agents","version":4},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-02T18:24:22.365030Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2603.12144"},"observation_digest":"sha256:799a2c97f6d58862add27e9ce691753825fa985a7c65ef351165063ade7e940c","observation_id":"94f84866-9670-4b19-a2f4-db13a8ea16a5","resolution":{"observed_at":"2026-08-02T18:24:22.365030Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":"2308.16896","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-07-03T15:58:37.359871Z","title":"arXiv preprint arXiv:2308.16896 (2023)","venue":null,"work_id":"b4747a90-0c97-4a4e-a1f4-73c40df732ff","year":2023},"citing_paper":{"arxiv_id":"2606.31688","last_updated":"2026-06-30T14:01:52Z","snapshot_observed_at":"2026-08-02T23:16:16.914306Z","submitted_at":"2026-06-30T14:01:52Z","title":"Semantic Occupancy Prediction with Dual Range-Voxel Representation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-01T05:49:03.009651Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2606.31688"},"observation_digest":"sha256:b59c11c549608041255337155b7b278da2e0ba619323418c8473c7938d1b31fe","observation_id":"16514d83-f915-428c-b220-8e91c23d3e4c","resolution":{"observed_at":"2026-07-01T10:05:41.540439Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":"2308.16896","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-07-03T15:58:37.359871Z","title":"arXiv preprint arXiv:2308.16896 (2023)","venue":null,"work_id":"b4747a90-0c97-4a4e-a1f4-73c40df732ff","year":2023},"citing_paper":{"arxiv_id":"2607.01928","last_updated":"2026-07-02T09:23:23Z","snapshot_observed_at":"2026-07-07T00:07:28.231599Z","submitted_at":"2026-07-02T09:23:23Z","title":"Sparse-Aware Vector Quantization for Bandwidth-Efficient Collaborative 3D Semantic Occupancy Prediction","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-03T15:54:07.772840Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2607.01928"},"observation_digest":"sha256:860f06079c4e296da9dec7146f442fcd44d55648aaf3ee795d2cfd2c8def340a","observation_id":"8a6b5325-1923-41b3-9524-64df51bf89cf","resolution":{"observed_at":"2026-07-03T15:58:37.361300Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16896","snapshot_observed_at":"2026-07-11T14:25:21.264423Z","title":"Pointocc: Cylindrical tri-perspective view for point-based 3d semantic occupancy prediction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04732","last_updated":"2026-07-06T07:10:00Z","snapshot_observed_at":"2026-08-07T08:39:49.817125Z","submitted_at":"2026-07-06T07:10:00Z","title":"SparseOcc++: Geometry-Aware Sparse Latent Representation for Semantic Occupancy Prediction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-11T14:25:21.264423Z"},"links":{"cited_paper":"/paper/2308.16896","citing_paper":"/paper/2607.04732"},"observation_digest":"sha256:a807f25702b8ee9181ca844e9568482c749ea6586238d5f776218fd481b179a1","observation_id":"0fbbd99a-645e-42f8-8614-3570077e6851","resolution":{"observed_at":"2026-07-11T14:25:21.264423Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2308.16896/citation-record","integrity":"/paper/2308.16896/integrity","json":"/paper/2308.16896/citation-record.json","paper":"/paper/2308.16896"},"outbound":[],"paper":{"arxiv_id":"2308.16896","last_updated":"2023-08-31T17:57:17Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-03T00:19:11.236614Z","submitted_at":"2023-08-31T17:57:17Z","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2308.16896."}