{"as_of":"2026-08-08T11:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8d75848a5343668e2a7dc102e2b24f1f9a68c22919b41362bc50e861821d73e8","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":"2026-08-07T13:11:46.033877Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-21T11:50:37.423645Z","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":"2026-05-21T11:54:09.175194Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"cited_work":{"arxiv_id":"2505.22461","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.22461","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Shtocc: Effective 3d occupancy prediction with sparse head and tail voxels","venue":null,"work_id":"d2ef75e1-4341-40db-9b70-ba067464c5da","year":2025},"citing_paper":{"arxiv_id":"2602.22667","last_updated":"2026-05-18T07:52:01Z","snapshot_observed_at":"2026-07-06T22:47:06.893212Z","submitted_at":"2026-02-26T06:37:43Z","title":"Monocular Open Vocabulary Occupancy Prediction for Indoor Scenes","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-21T11:50:37.423645Z"},"links":{"cited_paper":"/paper/2505.22461","citing_paper":"/paper/2602.22667"},"observation_digest":"sha256:433672b525e8485b9902412582cf4982318ef78236f3a46332304cec4a58be09","observation_id":"aa2cf667-f298-412d-952d-5ee3c7d461c7","resolution":{"observed_at":"2026-05-21T11:54:09.177283Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.22461/citation-record","integrity":"/paper/2505.22461/integrity","json":"/paper/2505.22461/citation-record.json","paper":"/paper/2505.22461"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:11:51.648061Z","title":"Se- mantickitti: A dataset for semantic scene understanding of lidar sequences,","venue":null,"work_id":"609e45f8-8e70-41d8-a2b5-1e658e283176","year":2019},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.210234Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:0603d39e0806330f7c452bd649692bd5e23129370072384c6f776a5c07cda042","observation_id":"21f55780-0720-41b1-a05b-e42efd5e9358","resolution":{"observed_at":"2026-08-07T13:11:51.719720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:40.310333Z","title":"Openoccupancy: A large scale benchmark for surrounding semantic occupancy perception,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.310333Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:c394aa33da2d4cbb9ade8e9c96dc9e02cdc19053a1ff4e53601f8eb0dc52fcd0","observation_id":"5ff1894f-5bcd-4ecd-bc67-9bd38eb13ebe","resolution":{"observed_at":"2026-08-07T13:11:40.310333Z","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":"2026-08-07T13:11:40.398079Z","title":"nuscenes: A multimodal dataset for autonomous driving,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.398079Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:d3d59e7afa06118f42369c82665d900052cdc07b7d82b25fb7359a163c237f98","observation_id":"8c388381-f6f8-49b7-a805-074ab874e3d6","resolution":{"observed_at":"2026-08-07T13:11:40.398079Z","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":"2026-08-07T13:11:51.346537Z","title":"Inversematrixvt3d: An efficient projection matrix-based approach for 3d occupancy prediction,","venue":null,"work_id":"4b8a76f6-38e2-4ac4-b377-6a2d1fcd5c80","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.475104Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:a031968c1516be1be43d712f64f2e28c8c92e3c79f6edee7f423f1e77f2ed329","observation_id":"1a0ed39b-8aab-40de-8a67-1ed8d24da623","resolution":{"observed_at":"2026-08-07T13:11:51.500728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:51.135007Z","title":"Surroundocc: Multi-camera 3d occupancy prediction for autonomous driving,","venue":null,"work_id":"90c86701-34f0-4728-b49c-f09f7b9a6940","year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.570335Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:aa81413e6c27a6eb461d81e978f87d75afdbae0f0992e81b7ffc3596fde6abeb","observation_id":"75accbdf-9a16-4c3c-b3f3-16bd332d22e7","resolution":{"observed_at":"2026-08-07T13:11:51.206215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:40.734800Z","title":"Occformer: Dual-path transformer for vision-based 3d semantic occupancy prediction,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.734800Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:493760fa0aaa28fc42b9ade8b414980950d3ff800373a1d2ca7ab41734e0a9b5","observation_id":"ecf45bff-2b6d-409a-9bf0-e06003d92b79","resolution":{"observed_at":"2026-08-07T13:11:40.734800Z","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":"2026-08-07T13:11:50.921553Z","title":"Fastocc: Accelerating 3d occupancy prediction by fusing the 2d bird’s-eye view and perspective view,","venue":null,"work_id":"8ded0d7c-3a5f-4d89-9e22-b51bfe4da364","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.825468Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:1023f7cd53ed5dee7000e48b6c0f4bbfa0265dcbfdffc0c692019ed9edc4ca0b","observation_id":"f2a56f83-9446-488e-9b1d-987d9cf3cc7f","resolution":{"observed_at":"2026-08-07T13:11:51.011393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.07163","last_updated":"2024-12-10T03:46:03Z","snapshot_observed_at":"2026-08-05T04:32:58.812111Z","submitted_at":"2024-12-10T03:46:03Z","title":"Fast Occupancy Network","version":1},"cited_work":{"arxiv_id":"2412.07163","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.07163","snapshot_observed_at":"2026-08-07T13:11:47.321885Z","title":"Fast Occupancy Network","venue":"cs.CV","work_id":"8302f7fd-aaa1-4d79-9108-38132f8b593e","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:40.976628Z"},"links":{"cited_paper":"/paper/2412.07163","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:cf068a74874e26edd58f1a3f366b8eb09b0e410121bd5e2789089d45b57a4b87","observation_id":"8887eb1b-217a-470c-8cfe-85cee1e0c91c","resolution":{"observed_at":"2026-08-07T13:11:47.394085Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.11464","last_updated":"2024-08-21T09:29:45Z","snapshot_observed_at":"2026-07-06T19:03:56.484389Z","submitted_at":"2024-08-21T09:29:45Z","title":"MambaOcc: Visual State Space Model for BEV-based Occupancy Prediction with Local Adaptive Reordering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.11464","snapshot_observed_at":"2026-08-07T13:11:41.238293Z","title":"Mambaocc: Visual state space model for bev-based occupancy prediction with local adaptive reordering,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:41.238293Z"},"links":{"cited_paper":"/paper/2408.11464","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:243e64e64c301c7ea955149f6302a66d68e05f0f96e221c6afcf8fde4cffa0dd","observation_id":"5595c955-8295-4fd2-a29c-4f1b6ce04e07","resolution":{"observed_at":"2026-08-07T13:11:41.238293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12058","last_updated":"2023-11-18T15:28:09Z","snapshot_observed_at":"2026-07-06T16:50:10.189504Z","submitted_at":"2023-11-18T15:28:09Z","title":"FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugin","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12058","snapshot_observed_at":"2026-08-07T13:11:41.381188Z","title":"Flashocc: Fast and memory-efficient occupancy prediction via channel-to-height plugin,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:41.381188Z"},"links":{"cited_paper":"/paper/2311.12058","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:d73b1ad8cada8858ab507bd2a5ccdf856456970f2f7266319de4905001a8ec4a","observation_id":"bf7e8efc-aabd-48c3-be53-1eed70ec74b3","resolution":{"observed_at":"2026-08-07T13:11:41.381188Z","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":"2026-08-07T13:11:50.679227Z","title":"Cotr: Compact occupancy transformer for vision-based 3d occupancy prediction,","venue":null,"work_id":"918614bf-334e-4a0f-a65d-7abf7bf2ce74","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:41.508048Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:bb0d19e3f34a9454611acdb65a3a741e1cd8757b3997ed54fe71b3c92d33b431","observation_id":"d32af923-cd98-454e-9d67-a361f6b1254d","resolution":{"observed_at":"2026-08-07T13:11:50.762400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.12959","last_updated":"2025-04-18T15:58:20Z","snapshot_observed_at":"2026-08-07T16:01:26.914754Z","submitted_at":"2025-04-17T14:05:33Z","title":"Rethinking Temporal Fusion with a Unified Gradient Descent View for 3D Semantic Occupancy Prediction","version":2},"cited_work":{"arxiv_id":"2504.12959","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.12959","snapshot_observed_at":"2026-08-07T13:11:47.059270Z","title":"Rethinking Temporal Fusion with a Unified Gradient Descent View for 3D Semantic Occupancy Prediction","venue":"cs.CV","work_id":"eccbc547-e6f8-4b37-a0db-7eecf2efb739","year":2025},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:41.595989Z"},"links":{"cited_paper":"/paper/2504.12959","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:30d79fd5a678485ba7ae658659fd26f15605f1e40be2374ada6f23e0a075e590","observation_id":"6bb53eca-c7a1-4334-bad2-0b6c78868994","resolution":{"observed_at":"2026-08-07T13:11:47.133805Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.19749","last_updated":"2025-04-28T12:49:20Z","snapshot_observed_at":"2026-08-07T15:58:37.315014Z","submitted_at":"2025-04-28T12:49:20Z","title":"STCOcc: Sparse Spatial-Temporal Cascade Renovation for 3D Occupancy and Scene Flow Prediction","version":1},"cited_work":{"arxiv_id":"2504.19749","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.19749","snapshot_observed_at":"2026-08-07T13:11:46.872677Z","title":"STCOcc: Sparse Spatial-Temporal Cascade Renovation for 3D Occupancy and Scene Flow Prediction","venue":"cs.CV","work_id":"f474eb81-1e60-4b7d-b1c0-3c6d5e3ba009","year":2025},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:41.708670Z"},"links":{"cited_paper":"/paper/2504.19749","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:400e23d340673b90b3f2d4ad5aa714fa934db013eb59c46651105b7c4255d98d","observation_id":"711e19c7-9a4f-4990-bbb3-3487ad380752","resolution":{"observed_at":"2026-08-07T13:11:46.918335Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:50.527760Z","title":"Tri-perspective view for vision-based 3d semantic occupancy prediction,","venue":null,"work_id":"1e297ff1-2b05-423d-aa49-6468fe40a0c5","year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:41.865677Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:9e8e71a58c4bbe21b7910e1b3016511d38c9e992c4452317cbdec9c251ed0ca7","observation_id":"128deb67-1e5c-483c-b33b-6d82f5772dde","resolution":{"observed_at":"2026-08-07T13:11:50.587655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05976","last_updated":"2026-06-21T15:24:02Z","snapshot_observed_at":"2026-07-06T20:03:29.510169Z","submitted_at":"2024-12-08T15:49:35Z","title":"LightOcc: Lightweight Spatial Embedding for Efficient Vision-based 3D Occupancy Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05976","snapshot_observed_at":"2026-08-07T13:11:42.031285Z","title":"Lightweight spatial embedding for vision-based 3d occupancy prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.031285Z"},"links":{"cited_paper":"/paper/2412.05976","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:44b15ea0184287f01ab6074f2c07bd114e8d5c334b39b225609048de2742b8e3","observation_id":"bfdfcc99-418c-4f83-9eb5-d1cce5725f29","resolution":{"observed_at":"2026-08-07T13:11:42.031285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.11019","last_updated":"2025-03-01T18:48:48Z","snapshot_observed_at":"2026-08-04T13:07:33.383664Z","submitted_at":"2024-10-14T19:14:49Z","title":"ET-Former: Efficient Triplane Deformable Attention for 3D Semantic Scene Completion From Monocular Camera","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.11019","snapshot_observed_at":"2026-08-07T13:11:42.201312Z","title":"Et-former: Efficient triplane deformable attention for 3d semantic scene completion from monocular camera,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.201312Z"},"links":{"cited_paper":"/paper/2410.11019","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:571c7ea70f7e985db0be32ad221e87f8de9277e4279ad2dfdb9d26bfe03708f4","observation_id":"538085b9-b515-4912-85d4-2324f9c8d61e","resolution":{"observed_at":"2026-08-07T13:11:42.201312Z","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":"2026-08-07T13:11:50.367117Z","title":"Gaussianformer: Scene as gaussians for vision-based 3d semantic occupancy prediction,","venue":null,"work_id":"ef0c3f02-a55e-4ee4-b048-92678467db78","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.313799Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:4ddd1a1a0551b40b4447be20c78105f122e37f1d48e58116c50c938936117140","observation_id":"1a3d3885-8ed6-4e98-8462-2885b757fe35","resolution":{"observed_at":"2026-08-07T13:11:50.440272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13193","last_updated":"2025-03-24T12:45:56Z","snapshot_observed_at":"2026-07-06T20:08:48.064792Z","submitted_at":"2024-12-17T18:59:46Z","title":"GaussTR: Foundation Model-Aligned Gaussian Transformer for Self-Supervised 3D Spatial Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13193","snapshot_observed_at":"2026-08-07T13:11:42.471135Z","title":"Gausstr: Foundation model-aligned gaussian transformer for self-supervised 3d spatial understanding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.471135Z"},"links":{"cited_paper":"/paper/2412.13193","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:933d17a2a52881bb17c529f9744182bffcfbfd3cff4bf5fe605267063bd93723","observation_id":"c0d3d367-a5f4-4af9-b659-1a023e986f07","resolution":{"observed_at":"2026-08-07T13:11:42.471135Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04384","last_updated":"2024-12-06T15:43:40Z","snapshot_observed_at":"2026-07-06T20:02:21.509050Z","submitted_at":"2024-12-05T17:59:58Z","title":"GaussianFormer-2: Probabilistic Gaussian Superposition for Efficient 3D Occupancy Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04384","snapshot_observed_at":"2026-08-07T13:11:42.588256Z","title":"Probabilistic gaussian superposition for efficient 3d occupancy prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.588256Z"},"links":{"cited_paper":"/paper/2412.04384","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:bfe0e9a71ad48dd470ac6ecc80f2e7e57c966c11e5ebb038c07de4ba6cbbf4ee","observation_id":"aac0a6e5-27bc-42cd-b517-239317a8aadb","resolution":{"observed_at":"2026-08-07T13:11:42.588256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09350","last_updated":"2024-10-31T01:39:52Z","snapshot_observed_at":"2026-07-06T19:15:21.535851Z","submitted_at":"2024-09-14T07:44:22Z","title":"OPUS: Occupancy Prediction Using a Sparse Set","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.09350","snapshot_observed_at":"2026-08-07T13:11:42.740268Z","title":"Opus: occupancy prediction using a sparse set,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.740268Z"},"links":{"cited_paper":"/paper/2409.09350","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:325d6bcf9a4d540063f6b85fe7bb21221758913ddfb88b9b1c82d868450a6d84","observation_id":"20366191-543c-46e4-9b89-da95e76da1d2","resolution":{"observed_at":"2026-08-07T13:11:42.740268Z","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":"2026-08-07T13:11:50.141290Z","title":"Fully sparse 3d occupancy prediction,","venue":null,"work_id":"6ab3078e-aa1f-4e82-abde-c7956578b106","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.882800Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:14b384483df139ed5d2f3bfaca521a7d31910049a746cc84a16f5d660a0d48a3","observation_id":"bb6e1018-c94c-4685-8f1b-741bba448bcd","resolution":{"observed_at":"2026-08-07T13:11:50.254583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:49.968118Z","title":"Sparseocc: Rethinking sparse latent representation for vision-based semantic occupancy prediction,","venue":null,"work_id":"860a3186-adbf-49ce-8630-aefd7610db40","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:42.992620Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:926f178844e83413400915c7ef99388f0c8da2dc23cad435a8b7c19f69bd9afc","observation_id":"8979f0db-01ba-4ebb-a16f-8e4023392d89","resolution":{"observed_at":"2026-08-07T13:11:50.038282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.15185","last_updated":"2025-03-19T13:14:57Z","snapshot_observed_at":"2026-08-07T16:52:07.855811Z","submitted_at":"2025-03-19T13:14:57Z","title":"3D Occupancy Prediction with Low-Resolution Queries via Prototype-aware View Transformation","version":1},"cited_work":{"arxiv_id":"2503.15185","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.15185","snapshot_observed_at":"2026-08-07T13:11:46.501747Z","title":"3D Occupancy Prediction with Low-Resolution Queries via Prototype-aware View Transformation","venue":"cs.CV","work_id":"9461208a-a54a-4a97-9757-01958c356351","year":2025},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.133524Z"},"links":{"cited_paper":"/paper/2503.15185","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:6a5b8363a158a1b59184cc94a5dda19992e2a4087fa4d306fba6845727719f01","observation_id":"cc12812f-f27d-4d29-a6b1-98768a4a9b1e","resolution":{"observed_at":"2026-08-07T13:11:46.597300Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:49.835996Z","title":"Long-tailed recognition via weight balancing,","venue":null,"work_id":"7c513b74-ff73-4d3b-98ac-3e6eb3effd64","year":2022},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.332389Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:3740572b87b4fe7f56d848348b2a439254f1583fcaf3cde71cabd3fa8e65ec31","observation_id":"6c0260c6-aee4-438a-8d02-950a24c2194f","resolution":{"observed_at":"2026-08-07T13:11:49.890151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:49.661246Z","title":"The devil is in classification: A simple framework for long-tail instance segmentation,","venue":null,"work_id":"96e4fb53-9c6d-4e0b-b5d1-43c93d954752","year":2020},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.456067Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:20d25e2b26e98d3bb0a7ddb9c7968bf36102153fe5228317da3f41513f0e8682","observation_id":"cd073f3b-8513-4deb-a6bc-3ec904893e81","resolution":{"observed_at":"2026-08-07T13:11:49.730296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.09217","last_updated":"2020-02-19T15:51:25Z","snapshot_observed_at":"2026-08-06T17:14:21.920122Z","submitted_at":"2019-10-21T09:03:19Z","title":"Decoupling Representation and Classifier for Long-Tailed Recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.09217","snapshot_observed_at":"2026-08-07T13:11:43.531974Z","title":"Decoupling representation and classifier for long-tailed recognition,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.531974Z"},"links":{"cited_paper":"/paper/1910.09217","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:550db36e7307a8b321e6274a20d57d4c7a71434a36c24cb5d10f5f34b1f80012","observation_id":"ff4e3154-6147-452e-828f-956cdffff196","resolution":{"observed_at":"2026-08-07T13:11:43.531974Z","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":"2026-08-07T13:11:43.638404Z","title":"Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.638404Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:35d24aeb28dbeffdfd19a73023dbbe36208ab596a15f748cf0ec55bb58271a5a","observation_id":"d4249312-1821-4247-8318-7263a2186c91","resolution":{"observed_at":"2026-08-07T13:11:43.638404Z","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":"2026-08-07T13:11:43.742322Z","title":"Occupancy networks: Learning 3d reconstruction in function space,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.742322Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:71ccc0904199e6c7824f59a7322a146a4307b5d911ff3224faa057571c275a66","observation_id":"7221a046-2d1f-42e0-b51e-c4b2b405745a","resolution":{"observed_at":"2026-08-07T13:11:43.742322Z","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":"2026-08-07T13:11:49.468426Z","title":"Convolutional occupancy networks,","venue":null,"work_id":"de874ecd-1a55-4a51-b68f-3b50eec668db","year":2020},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.847116Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:516c73a3587c76f651f68ca2db6a23ffab2b56857062d33f0ca6bcf90890d8bf","observation_id":"dda3d7e8-ae89-4bfb-a5b7-074cd5f40eeb","resolution":{"observed_at":"2026-08-07T13:11:49.528814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:49.274063Z","title":"Semantic scene completion from a single depth image,","venue":null,"work_id":"fae490e8-b895-4e54-b75f-488427b4b33a","year":2017},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:43.942255Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:bcedaf2edff0c934f5c14b30969f87200505f939f0cf0dbfef73ecd797229997","observation_id":"2ed46270-9eb5-47d9-8efd-0dba91a94dbe","resolution":{"observed_at":"2026-08-07T13:11:49.359320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:44.031674Z","title":"Rgbd based dimensional decomposition residual network for 3d semantic scene completion,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.031674Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:a2d7796d4220c922791c87c09cf57a215be810abd516bde191073253de42bc0f","observation_id":"4ff370a8-eb0c-416b-aef0-8aa0d5df97bc","resolution":{"observed_at":"2026-08-07T13:11:44.031674Z","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":"2026-08-07T13:11:49.114467Z","title":"Cascaded context pyramid for full-resolution 3d semantic scene completion,","venue":null,"work_id":"e450cb32-1f58-4871-bea9-f0cb11706c6b","year":2019},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.139588Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:86acb3215d7512702b9af7461c99f9c909bdacfe84cbeb0ae2720ac2b5bd6ea0","observation_id":"f58931d8-55c5-48ad-9fb3-0ca299cfd2ea","resolution":{"observed_at":"2026-08-07T13:11:49.167501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.05361","last_updated":"2018-06-14T04:42:05Z","snapshot_observed_at":"2026-08-03T18:17:07.831762Z","submitted_at":"2018-06-14T04:42:05Z","title":"View-volume Network for Semantic Scene Completion from a Single Depth Image","version":1},"cited_work":{"arxiv_id":"1806.05361","doi":null,"metadata_source":"pith","pith_arxiv_id":"1806.05361","snapshot_observed_at":"2026-08-07T13:11:46.305265Z","title":"View-volume Network for Semantic Scene Completion from a Single Depth Image","venue":"cs.CV","work_id":"920d3811-4cf9-4760-a476-47443b0916f6","year":2018},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.232494Z"},"links":{"cited_paper":"/paper/1806.05361","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:faa2c8fe18bdb78e893ecf1eead6cdff76d5145c847d615fb934a5b1ca882682","observation_id":"20713034-1fcb-4a66-9c53-db4cdb0ca9bf","resolution":{"observed_at":"2026-08-07T13:11:46.365226Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:44.296858Z","title":"Anisotropic convolutional networks for 3d semantic scene completion,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.296858Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:65dee243d89bcfc5c56c062e08a17de6e8fb7f8b2841426fe821a6f54d302f95","observation_id":"2b7ffb93-d0c1-470f-b457-a678c6303ec1","resolution":{"observed_at":"2026-08-07T13:11:44.296858Z","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":"2026-08-07T13:11:48.956708Z","title":"See and think: Disentangling semantic scene completion,","venue":null,"work_id":"0bd663a3-644e-4afc-9519-aa9daf4632ea","year":2018},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.438242Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:dea0bf888e6c7d7b7ee06a12309578a83be6fbbc2c31bcdf5d083a6ba95b7805","observation_id":"d2ddca64-5891-4868-9989-25f1e0e0b8de","resolution":{"observed_at":"2026-08-07T13:11:49.024825Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:44.520674Z","title":"Monoscene: Monocular 3d semantic scene completion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.520674Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:9168c6be3eeb46cd9d03c6914ca7c25d8ea01466ee8e29724288c14a06c1b267","observation_id":"a9e0a018-9e3c-41c8-aa14-0644a4689792","resolution":{"observed_at":"2026-08-07T13:11:44.520674Z","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":"2026-08-07T13:11:44.625958Z","title":"V oxformer: Sparse voxel transformer for camera-based 3d semantic scene completion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.625958Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:bce713f5962eda79eb836932f48d2c3eae406b44a7fdd6b4e8e2233c93cff63e","observation_id":"92247f66-8736-42c6-832f-8b778c5156d9","resolution":{"observed_at":"2026-08-07T13:11:44.625958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13540","last_updated":"2023-02-27T06:35:03Z","snapshot_observed_at":"2026-08-04T09:40:33.174673Z","submitted_at":"2023-02-27T06:35:03Z","title":"OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13540","snapshot_observed_at":"2026-08-07T13:11:44.748461Z","title":"Occdepth: A depth-aware method for 3d semantic scene completion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.748461Z"},"links":{"cited_paper":"/paper/2302.13540","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:9d2ac28a7fbd13e7cc849bc6e65d023de2e6ac15e1fe400e7c633e4935d83728","observation_id":"3d8d1c4c-46bc-4e6c-8ef6-f1e141df383c","resolution":{"observed_at":"2026-08-07T13:11:44.748461Z","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":"2026-08-07T13:11:48.790352Z","title":"Ndc-scene: Boost monocular 3d semantic scene completion in normalized device coordinates space,","venue":null,"work_id":"3f095bce-8a26-4c54-8f15-a9c6ef9e7bdc","year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.837295Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:d759eb05d42e7fb4b77f94c722dd4f6255a5777fcefd398cfc946b523ce91d9f","observation_id":"1bbd591c-cb50-420c-bb1c-633e3c64b86c","resolution":{"observed_at":"2026-08-07T13:11:48.837236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:44.892643Z","title":"Scene as occupancy,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.892643Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:de0d2a8bd2a29cfee05420d8e8ad7ae1f6f4ce598f9222562926d023a854797b","observation_id":"fbc727c5-bceb-4c5e-99b0-505c4b5f4dfb","resolution":{"observed_at":"2026-08-07T13:11:44.892643Z","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":"2026-08-07T13:11:48.564367Z","title":"Rethinking classifier re-training in long-tailed recognition: Label over-smooth can balance,","venue":null,"work_id":"d4828abf-a489-4515-8451-0cd5bcda23a2","year":null},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:44.979866Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:71f67802044a2e23a1460a7a5cc673db6703a2ac97e909edae6c9c8ab2606545","observation_id":"9e5af5db-4700-4d4a-946c-acf9d6dfc5ce","resolution":{"observed_at":"2026-08-07T13:11:48.673546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:48.360950Z","title":"Not all voxels are equal: Hardness- aware semantic scene completion with self-distillation,","venue":null,"work_id":"d112674d-b2b3-4f2c-aa43-c6e8c6a942f1","year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.048985Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:10130507ff252e00149e7693de28f8b35df9c4a9075a08031925df6705ee25a0","observation_id":"5c09ab91-0e0f-47bc-9488-8a2de905fc23","resolution":{"observed_at":"2026-08-07T13:11:48.432495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:45.178841Z","title":"Symphonize 3d semantic scene completion with contextual instance queries,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.178841Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:88a09ffcf12fd831032869b8ee405043a3fc99de7967f1d32c580eaa397bc360","observation_id":"53a7b028-2e5a-4caa-873c-877838f43d58","resolution":{"observed_at":"2026-08-07T13:11:45.178841Z","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":"2026-08-07T13:11:45.275126Z","title":"Lmscnet: Lightweight multiscale 3d semantic completion,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.275126Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:7d9da4129859324b82b581f790d022f07852752576b3cb0a9b88e0745244d0f6","observation_id":"f1a1b084-9815-4f96-805e-03e8173e0090","resolution":{"observed_at":"2026-08-07T13:11:45.275126Z","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":"2026-08-07T13:11:45.355300Z","title":"Sparse single sweep lidar point cloud segmentation via learning contextual shape priors from scene completion,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.355300Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:5fe6b55e00f88b2d20a83f8d24c46a34a8fbcfeebb6e369de9f3fe6ed0345f24","observation_id":"ba40f080-5896-4224-91a7-bcecd3e6a027","resolution":{"observed_at":"2026-08-07T13:11:45.355300Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.17270","last_updated":"2022-07-13T06:57:28Z","snapshot_observed_at":"2026-07-06T12:55:23.720351Z","submitted_at":"2022-03-31T17:59:01Z","title":"BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.17270","snapshot_observed_at":"2026-08-07T13:11:45.426681Z","title":"Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.426681Z"},"links":{"cited_paper":"/paper/2203.17270","citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:a5f33b57700564081557f3d25b9f72fcfedb4acc7e4a64a79ccbf38f17bc80dc","observation_id":"c4908c9d-5c01-49b5-9620-2d62f93274a1","resolution":{"observed_at":"2026-08-07T13:11:45.426681Z","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":"2026-08-07T13:11:48.116378Z","title":"Fb-bev: Bev representation from forward-backward view transformations,","venue":null,"work_id":"064eec0f-6081-4efa-b57b-77fce0d4005e","year":2023},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.493457Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:a8e61fd1a825d15508e34b1c6381fc835802480d0463306e55adcbdd46663cc1","observation_id":"036f6ba3-c31c-4bc1-bf36-374477eb4ec3","resolution":{"observed_at":"2026-08-07T13:11:48.183987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:45.531294Z","title":"Panoocc: Unified occupancy representation for camera-based 3d panoptic segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.531294Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:f8a5769c1c2b7620985b4bb53cd511729321baa6863c62c1a06ec935549961c8","observation_id":"49509b24-01c0-4a3d-b623-fdf68d3d7fd6","resolution":{"observed_at":"2026-08-07T13:11:45.531294Z","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":"2026-08-07T13:11:47.943346Z","title":"Protoocc: Accurate, efficient 3d occupancy prediction using dual branch encoder-prototype query decoder,","venue":null,"work_id":"d98b9a99-f8a6-493b-a9e0-59d4a0a7b887","year":2025},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.596783Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:0e75c86a0beb4d29aa5f719af9221302d3edb660fced375f4e6cdefcfed9e46b","observation_id":"598ac190-026b-4534-b752-ccb1804b7e5b","resolution":{"observed_at":"2026-08-07T13:11:47.994823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:45.675204Z","title":"Rangenet++: Fast and accurate lidar semantic segmentation,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.675204Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:f31d2b3e749e85819457bf65986f955ef0e549669f75f1a8db2e8740c28769fa","observation_id":"c746dc84-b13e-4e03-939d-c5c6c1415035","resolution":{"observed_at":"2026-08-07T13:11:45.675204Z","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":"2026-08-07T13:11:45.761634Z","title":"Polarnet: An improved grid representation for online lidar point clouds semantic segmentation,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.761634Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:56c12790b6fc5f5391f759905455547c997bf49f7a815b465bff50430261910d","observation_id":"f072d85d-8ba1-4eff-a74b-27856aa76cef","resolution":{"observed_at":"2026-08-07T13:11:45.761634Z","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":"2026-08-07T13:11:47.711831Z","title":"Salsanext: Fast, uncertainty-aware semantic segmentation of lidar point clouds,","venue":null,"work_id":"4fe1b381-dcfb-45ef-997e-742cb4e91d8d","year":2020},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.862298Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:2f40c61e3f90e5ae6d389c27baf3f1f8afd7c84d4119022a6a3e1b82921fd77c","observation_id":"0ab92a4d-e105-4d3b-9834-48c12ca87a33","resolution":{"observed_at":"2026-08-07T13:11:47.764779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:11:45.926386Z","title":"Cylindrical and asymmetrical 3d convolution networks for lidar segmentation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:45.926386Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:a40c36f718a1c5b15f8f032065f06436b1b3628f05405692ee2ea02d169800c7","observation_id":"5eb84f1a-a189-4c43-b190-9c1d4209367f","resolution":{"observed_at":"2026-08-07T13:11:45.926386Z","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":"2026-08-07T13:11:47.495594Z","title":"Rpvnet: A deep and efficient range-point- voxel fusion network for lidar point cloud segmentation,","venue":null,"work_id":"d7418399-ee56-4d9f-8244-a07f867e094b","year":2021},"citing_paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T13:11:46.033877Z"},"links":{"citing_paper":"/paper/2505.22461"},"observation_digest":"sha256:6613d438461bcd51b468968cde5d132c3ace0960bb91be6d046172777716e743","observation_id":"69afb9f8-806a-4c3c-9d53-d4f40ca771eb","resolution":{"observed_at":"2026-08-07T13:11:47.588244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.22461","last_updated":"2025-05-29T14:45:58Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T13:04:22.417271Z","submitted_at":"2025-05-28T15:16:15Z","title":"SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":5,"verified_fuzzy":22},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:2505.22461."}