{"as_of":"2026-08-11T12:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ad80c8ac00acc8f2830680753c8150c0d7d4dfe022e21c4b5735587250f3a966","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":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":15,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T17:20:07.259534Z","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":"2026-07-10T13:47:05.812667Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-08-10T17:20:07.259534Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12387","last_updated":"2025-01-21T18:59:23Z","snapshot_observed_at":"2026-08-10T17:10:19.492897Z","submitted_at":"2025-01-21T18:59:23Z","title":"Continuous 3D Perception Model with Persistent State","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T17:20:07.259534Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2501.12387"},"observation_digest":"sha256:16a2c4804b0d2cff03e5420926ebc3a9d4957a267e0ae90c8e8f674e7f2c9b05","observation_id":"e7a4c153-a992-4c5d-a000-4be09934141e","resolution":{"observed_at":"2026-08-10T17:20:07.259534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2504.07940","last_updated":"2026-04-23T02:00:55Z","snapshot_observed_at":"2026-07-30T04:57:12.317374Z","submitted_at":"2025-04-10T17:51:38Z","title":"Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-22T19:54:28.310854Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2504.07940"},"observation_digest":"sha256:70af8b76a80ed7f12d7abf40d1b6dcbf4e86e954362ecdcf925abd5f57dc8d36","observation_id":"2722be67-35bc-4efb-bb44-a029060e0e73","resolution":{"observed_at":"2026-05-22T19:55:05.046931Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2505.23747","last_updated":"2026-05-19T02:23:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-29T17:59:04Z","title":"Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-16T08:34:36.824053Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2505.23747"},"observation_digest":"sha256:d7c29834105476ab6a7c27efd33a06600320cc3450cece37e41b6171acf85d38","observation_id":"14c45576-ad59-4028-9493-c01e46a67481","resolution":{"observed_at":"2026-05-16T08:34:36.887261Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2505.23747","last_updated":"2026-05-19T02:23:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-29T17:59:04Z","title":"Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-22T00:59:13.826054Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2505.23747"},"observation_digest":"sha256:bc956c827ca2c8d318c51c847688253bb8b70708e2c545b029737138509bca14","observation_id":"075cd30b-da11-488e-adc4-07f2b80770a7","resolution":{"observed_at":"2026-05-22T01:00:51.337552Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-08-07T04:42:15.857646Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos.arXiv preprint arXiv:2412.04463, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09997","last_updated":"2025-06-11T17:59:58Z","snapshot_observed_at":"2026-08-07T04:33:15.759296Z","submitted_at":"2025-06-11T17:59:58Z","title":"DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T04:42:15.857646Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2506.09997"},"observation_digest":"sha256:a36a4408718fa35a9ec0f2353073d2a35d4290db3b5e42d2332be709ceee8376","observation_id":"8cfd81b2-af94-47ef-b3cc-1fafb5ec44a2","resolution":{"observed_at":"2026-08-07T04:42:15.857646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2507.02546","last_updated":"2025-07-03T11:40:01Z","snapshot_observed_at":"2026-07-06T21:51:38.554688Z","submitted_at":"2025-07-03T11:40:01Z","title":"MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-14T21:19:44.144633Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2507.02546"},"observation_digest":"sha256:a937998949c84db04f877f86545cea8cac540437d1f0914f603f5fff4ff7cb29","observation_id":"cf9cf5b2-ca4d-4cd9-ba6b-a15cdb08248e","resolution":{"observed_at":"2026-05-14T21:19:44.200428Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-08-06T13:02:29.290397Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21045","last_updated":"2025-08-03T14:18:19Z","snapshot_observed_at":"2026-08-10T06:49:30.997453Z","submitted_at":"2025-07-28T17:59:02Z","title":"Reconstructing 4D Spatial Intelligence: A Survey","version":2},"reference_index":169,"source":"pdf_text","source_observed_at":"2026-08-06T13:02:29.290397Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2507.21045"},"observation_digest":"sha256:1b7e24fdad1a9fe62bb2ab08c12c13ca85b3cb7444b9363dea6d09672182efc3","observation_id":"ee0ab505-117d-4f3f-b412-020d997975fd","resolution":{"observed_at":"2026-08-06T13:02:29.290397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-08-04T09:49:44.719772Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.13310","last_updated":"2026-07-21T19:26:24Z","snapshot_observed_at":"2026-08-09T04:59:17.288715Z","submitted_at":"2025-10-15T08:58:05Z","title":"InstantSfM: Towards GPU-Native SfM for the Deep Learning Era","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T09:49:44.719772Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2510.13310"},"observation_digest":"sha256:3bda726c1592c30c050d0fc1845cedee75fc916552538aba3ebf59d610a273c2","observation_id":"62d15d25-556c-46c1-bd26-2ed733f0da6b","resolution":{"observed_at":"2026-08-04T09:49:44.719772Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2512.15840","last_updated":"2026-05-08T06:37:02Z","snapshot_observed_at":"2026-08-11T06:04:17.319434Z","submitted_at":"2025-12-17T18:35:54Z","title":"Large Video Planner Enables Generalizable Robot Control","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-16T21:26:32.048309Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2512.15840"},"observation_digest":"sha256:8326ed375d57a7ec8f7d04d5d17115f4189d2cbfb8c3544724de7242eeea7bb3","observation_id":"b7a6c0fe-07b2-4668-a8bd-3ab9a1dd28f7","resolution":{"observed_at":"2026-05-16T21:28:33.877549Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2605.15185","last_updated":"2026-05-14T17:59:04Z","snapshot_observed_at":"2026-08-03T12:57:56.209990Z","submitted_at":"2026-05-14T17:59:04Z","title":"Quantitative Video World Model Evaluation for Geometric-Consistency","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-15T03:11:03.060052Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2605.15185"},"observation_digest":"sha256:40984937a4cc8ae8048e1e0173b4c0f789120f584b2b5b6e8b42bd77153554a1","observation_id":"92f69588-31c3-43e1-8b7d-7643a6d24169","resolution":{"observed_at":"2026-05-15T03:14:53.088956Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2606.29976","last_updated":"2026-06-29T08:50:27Z","snapshot_observed_at":"2026-08-01T23:15:46.644664Z","submitted_at":"2026-06-29T08:50:27Z","title":"Learning Efficient 4D Gaussian Representations from Monocular Videos with Flow Splatting","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-30T06:58:21.697133Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2606.29976"},"observation_digest":"sha256:b8725f7edb90aecef2c29e7ec0c8c8e62c881cd5c785a4dc4c5da31d0d5b5e26","observation_id":"bf613588-743a-4a57-b64a-b83b4b3fa693","resolution":{"observed_at":"2026-06-30T07:04:21.706986Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":"2412.04463","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-10T13:47:05.812667Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":"cs.CV","work_id":"6321850e-1f8c-42a0-8a91-d1f2a2e04034","year":2024},"citing_paper":{"arxiv_id":"2607.08016","last_updated":"2026-07-15T01:05:32Z","snapshot_observed_at":"2026-08-10T18:19:52.551946Z","submitted_at":"2026-07-09T00:44:43Z","title":"LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-10T13:41:50.229019Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2607.08016"},"observation_digest":"sha256:b6d19ce93cad021c8e24a5140493e59e94bdb0e560e7d2751146e717a9594018","observation_id":"8488f84c-da5d-485e-ae7e-fba8f09e4e16","resolution":{"observed_at":"2026-07-10T13:47:05.813940Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-08-02T08:02:12.124903Z","title":"Megasam: Accurate, fast, and robust structure and motion from casual dynamic videos.arXiv preprint arXiv:2412.04463, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.08016","last_updated":"2026-07-15T01:05:32Z","snapshot_observed_at":"2026-08-10T18:19:52.551946Z","submitted_at":"2026-07-09T00:44:43Z","title":"LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T08:02:12.124903Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2607.08016"},"observation_digest":"sha256:d415c3b05f954dce135799406733788bc0495656b5d478a29fde441656896860","observation_id":"2699f28b-91c7-4f1c-bd9b-8ec716fad5a2","resolution":{"observed_at":"2026-08-02T08:02:12.124903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-07-31T13:17:58.446114Z","title":"MegaSaM: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24495","last_updated":"2026-07-27T14:31:55Z","snapshot_observed_at":"2026-08-09T16:34:09.054226Z","submitted_at":"2026-07-27T14:31:55Z","title":"NSL-SLAM: High-Fidelity Neural Structured-Light Depth for Practical SLAM and Reconstruction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-31T13:17:58.446114Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2607.24495"},"observation_digest":"sha256:4942516a125feb035db1b23425c5ba415d810800db00bd5227da460cb9579a1c","observation_id":"a2079b88-4b28-4d8e-bea1-a733b09b2c2c","resolution":{"observed_at":"2026-07-31T13:17:58.446114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04463","snapshot_observed_at":"2026-08-07T00:14:03.547097Z","title":"MegaSaM: Accurate, fast, and robust structure and motion from casual dynamic videos","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02713","last_updated":"2026-08-03T17:59:58Z","snapshot_observed_at":"2026-08-07T23:09:56.055766Z","submitted_at":"2026-08-03T17:59:58Z","title":"Quo Vadis, World Modeling?","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:03.547097Z"},"links":{"cited_paper":"/paper/2412.04463","citing_paper":"/paper/2608.02713"},"observation_digest":"sha256:7dac29e9176d4dd456963ccd854feffd058cd0ccaade73ecd5bdb327ac9e6527","observation_id":"92908842-d826-41de-bd15-bf46b2f7bddc","resolution":{"observed_at":"2026-08-07T00:14:03.547097Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.04463/citation-record","integrity":"/paper/2412.04463/integrity","json":"/paper/2412.04463/citation-record.json","paper":"/paper/2412.04463"},"outbound":[],"paper":{"arxiv_id":"2412.04463","last_updated":"2024-12-06T19:15:46Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-03T14:50:26.372066Z","submitted_at":"2024-12-05T18:59:42Z","title":"MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videos"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2412.04463."}