{"as_of":"2026-08-09T16:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:87315eec83a13fc595a72ef683b234d37f04f831351be6d9f70a32a0635a0cc5","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:13:48.094190Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-08T07:14:45.121873Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":"2409.11356","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-07-08T07:14:45.121873Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356","venue":"cs.CV","work_id":"4b9a6117-4228-4ea0-8029-b662e10c2b1d","year":2024},"citing_paper":{"arxiv_id":"2412.12870","last_updated":"2026-04-04T22:46:07Z","snapshot_observed_at":"2026-08-04T04:34:45.260774Z","submitted_at":"2024-12-17T12:51:24Z","title":"Physically Interpretable World Models via Weakly Supervised Representation Learning","version":6},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-23T07:00:46.917344Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2412.12870"},"observation_digest":"sha256:57586dbe71e5d0cf010f7f71092d33bf531e97ea60873328ad3b005341fd4bde","observation_id":"deef4573-90b9-4c29-8729-68891a94863f","resolution":{"observed_at":"2026-05-23T07:02:41.432688Z","resolver_source":"arxiv_id","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":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-08-07T13:13:48.094190Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.22421","last_updated":"2025-05-29T12:41:53Z","snapshot_observed_at":"2026-08-09T00:50:02.229626Z","submitted_at":"2025-05-28T14:46:51Z","title":"GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-07T13:13:48.094190Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2505.22421"},"observation_digest":"sha256:593972cd58453bc98e847db9727286ec8b3c8dfac3197c1f15de2ad28dbc4840","observation_id":"b4366469-57ce-43cd-ab3c-ccbc6dff6753","resolution":{"observed_at":"2026-08-07T13:13:48.094190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-08-07T04:19:24.771073Z","title":"Renderworld: World model with self-supervised 3d label","venue":null,"work_id":null,"year":2024},"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":38,"source":"pdf_text","source_observed_at":"2026-08-07T04:19:24.771073Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2506.10977"},"observation_digest":"sha256:b990d1e459fafed9740a54a734846d8dffe31e1cb796ed7895827ab59c724e97","observation_id":"c5bb20dd-ea73-41fa-96fc-47fab51b52bb","resolution":{"observed_at":"2026-08-07T04:19:24.771073Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-08-07T00:41:32.077815Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13260","last_updated":"2025-06-16T09:01:09Z","snapshot_observed_at":"2026-08-09T10:44:12.559105Z","submitted_at":"2025-06-16T09:01:09Z","title":"COME: Adding Scene-Centric Forecasting Control to Occupancy World Model","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T00:41:32.077815Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2506.13260"},"observation_digest":"sha256:9df4ae123226e89cd95e83c18a208af05eb72066c8ed4580301ee94dd37b6901","observation_id":"35dce14c-04aa-4d4e-affd-231a24ef1861","resolution":{"observed_at":"2026-08-07T00:41:32.077815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-08-06T00:56:01.784657Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.04153","last_updated":"2025-08-06T07:28:25Z","snapshot_observed_at":"2026-08-07T15:10:08.429378Z","submitted_at":"2025-08-06T07:28:25Z","title":"ICM-Fusion: In-Context Meta-Optimized LoRA Fusion for Multi-Task Adaptation","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-06T00:56:01.784657Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2508.04153"},"observation_digest":"sha256:df3785dd9fdd9101f9dd5fe884399565f72bcf39d28df2ab32243903725954af","observation_id":"9a21fd56-40f5-4bdb-a8b9-00f5774e2009","resolution":{"observed_at":"2026-08-06T00:56:01.784657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-08-04T20:52:06.391983Z","title":"Renderworld: World model with self-supervised 3d label,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.08302","last_updated":"2025-09-10T05:45:49Z","snapshot_observed_at":"2026-08-07T03:24:45.987181Z","submitted_at":"2025-09-10T05:45:49Z","title":"Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-04T20:52:06.391983Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2509.08302"},"observation_digest":"sha256:8f301de88e41b6f4a7e93c6ec5afb6eefb73172864ad010ef629db657018dd70","observation_id":"a473cd25-a1ab-4d80-8798-767ed4d65a06","resolution":{"observed_at":"2026-08-04T20:52:06.391983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-08-04T20:49:00.193227Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.08388","last_updated":"2025-09-10T08:29:22Z","snapshot_observed_at":"2026-08-09T06:41:30.097348Z","submitted_at":"2025-09-10T08:29:22Z","title":"Semantic Causality-Aware Vision-Based 3D Occupancy Prediction","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-04T20:49:00.193227Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2509.08388"},"observation_digest":"sha256:ac4176f25047229333886c8e248bedc4356ab1dcb04c8e39ba23e69d14b80239","observation_id":"5ea04341-28ea-447d-b6c1-799087b87a69","resolution":{"observed_at":"2026-08-04T20:49:00.193227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":"2409.11356","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-07-08T07:14:45.121873Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356","venue":"cs.CV","work_id":"4b9a6117-4228-4ea0-8029-b662e10c2b1d","year":2024},"citing_paper":{"arxiv_id":"2511.22039","last_updated":"2026-04-14T12:13:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-27T02:48:45Z","title":"SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-17T05:26:34.859975Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2511.22039"},"observation_digest":"sha256:7557cf620da819062eae8e914042b75277b35163e4ee8b451aa5d3f26998d59c","observation_id":"b4471553-f03a-42ac-bdeb-e1219375c530","resolution":{"observed_at":"2026-05-17T05:29:05.016706Z","resolver_source":"arxiv_id","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":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":"2409.11356","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-07-08T07:14:45.121873Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356","venue":"cs.CV","work_id":"4b9a6117-4228-4ea0-8029-b662e10c2b1d","year":2024},"citing_paper":{"arxiv_id":"2606.04945","last_updated":"2026-06-08T08:41:05Z","snapshot_observed_at":"2026-08-02T15:48:27.544154Z","submitted_at":"2026-06-03T14:34:35Z","title":"STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models","version":2},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-06-28T07:14:26.441339Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2606.04945"},"observation_digest":"sha256:188a2d99544a046b1835f69c7649f63d86893e210eea34240dc4e04ea7d1d601","observation_id":"33520028-dd4c-4edc-ae7b-cb487020c75f","resolution":{"observed_at":"2026-07-02T07:06:43.728747Z","resolver_source":"arxiv_id","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":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":"2409.11356","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-07-08T07:14:45.121873Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356","venue":"cs.CV","work_id":"4b9a6117-4228-4ea0-8029-b662e10c2b1d","year":2024},"citing_paper":{"arxiv_id":"2606.27644","last_updated":"2026-06-26T01:43:37Z","snapshot_observed_at":"2026-08-02T14:55:50.321435Z","submitted_at":"2026-06-26T01:43:37Z","title":"CascadeOcc: Rethinking 3D Occupancy World Models with Cascaded VQ Representations","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-29T00:31:18.101634Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2606.27644"},"observation_digest":"sha256:876f5d3b282a6cb242a9bdb9a0e511ae9d4a13f938a0e1e6e6789a4b649df797","observation_id":"ae5552a0-c658-4d9e-af06-bc995033fdfe","resolution":{"observed_at":"2026-07-01T19:06:03.494454Z","resolver_source":"arxiv_id","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":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label","version":2},"cited_work":{"arxiv_id":"2409.11356","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.11356","snapshot_observed_at":"2026-07-08T07:14:45.121873Z","title":"Renderworld: World model with self-supervised 3d label.arXiv preprint arXiv:2409.11356","venue":"cs.CV","work_id":"4b9a6117-4228-4ea0-8029-b662e10c2b1d","year":2024},"citing_paper":{"arxiv_id":"2607.06401","last_updated":"2026-07-07T15:31:32Z","snapshot_observed_at":"2026-08-03T02:43:03.919769Z","submitted_at":"2026-07-07T15:31:32Z","title":"A Definition and Roadmap for World Models","version":1},"reference_index":201,"source":"arxiv_source","source_observed_at":"2026-07-08T07:10:33.826140Z"},"links":{"cited_paper":"/paper/2409.11356","citing_paper":"/paper/2607.06401"},"observation_digest":"sha256:c34eaa3335182bfd359546c6883c462fb84420bd43ddb526cb5cc413073ae174","observation_id":"64bd40ed-2d6a-4b72-bb44-96bce2f3d763","resolution":{"observed_at":"2026-07-08T07:14:45.124291Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.11356/citation-record","integrity":"/paper/2409.11356/integrity","json":"/paper/2409.11356/citation-record.json","paper":"/paper/2409.11356"},"outbound":[],"paper":{"arxiv_id":"2409.11356","last_updated":"2025-02-13T05:20:48Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T19:16:51.512681Z","submitted_at":"2024-09-17T17:00:52Z","title":"RenderWorld: World Model with Self-Supervised 3D Label"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2409.11356."}