{"as_of":"2026-08-21T09:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a393aea5612a4578bb33018a0df7c44e0d0a41d9867b6a1168ec6f21013951a","coverage":[{"denominator":108,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T04:40:18.891082Z","state":"measured"},{"denominator":108,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":108,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T19:17:33.322574Z","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":"2026-05-19T20:32:45.746136Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-08-09T11:42:03.486136Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02590","last_updated":"2025-05-12T01:53:46Z","snapshot_observed_at":"2026-08-19T17:33:59.393986Z","submitted_at":"2025-02-04T18:59:55Z","title":"Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-09T11:42:03.486136Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2502.02590"},"observation_digest":"sha256:c97e7546957a872b1e047bef7dafa7557fe78de152aa8eccf910597a2c41c1d6","observation_id":"a80ed881-9186-4349-b6e0-e1305a167952","resolution":{"observed_at":"2026-08-09T11:42:03.486136Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-08-07T10:17:57.528352Z","title":"Partgen: Part-level 3d generation and reconstruction with multi-view diffusion models.arXiv preprint arXiv:2412.18608, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05573","last_updated":"2025-06-05T20:30:28Z","snapshot_observed_at":"2026-08-16T16:58:09.756289Z","submitted_at":"2025-06-05T20:30:28Z","title":"PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformers","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T10:17:57.528352Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2506.05573"},"observation_digest":"sha256:2e6f27bb794ea673224664bbde25065147c1233ccb1738d3d0bd8028df1bacf1","observation_id":"f95e8570-ff01-45b2-87bb-547729ba5ff7","resolution":{"observed_at":"2026-08-07T10:17:57.528352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-08-07T04:40:13.424655Z","title":"Partgen: Part-level 3d generation and reconstruction with multi-view diffusion models.arXiv preprint arXiv:2412.18608, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09980","last_updated":"2025-06-11T17:55:03Z","snapshot_observed_at":"2026-08-15T17:26:55.813715Z","submitted_at":"2025-06-11T17:55:03Z","title":"Efficient Part-level 3D Object Generation via Dual Volume Packing","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:40:13.424655Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2506.09980"},"observation_digest":"sha256:ee712035b1b0dbf5dc485f6832f2067faf7e2f856876af62a5ff1580b94901f5","observation_id":"c03851f5-fb5e-4e9c-b0f9-c109e03d3728","resolution":{"observed_at":"2026-08-07T04:40:13.424655Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-08-15T19:17:33.322574Z","title":"InACM SIGGRAPH 2011 papers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.17074","last_updated":"2025-06-20T15:25:20Z","snapshot_observed_at":"2026-08-18T12:02:22.835857Z","submitted_at":"2025-06-20T15:25:20Z","title":"Assembler: Scalable 3D Part Assembly via Anchor Point Diffusion","version":1},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-15T19:17:33.322574Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2506.17074"},"observation_digest":"sha256:b26b6eca2fc52804fc31838b79e7dbeed8a125b12509bef95c4596015cb377d7","observation_id":"06f3c474-40ad-43cf-be1a-9ef94ab43b7f","resolution":{"observed_at":"2026-08-15T19:17:33.322574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-08-06T19:44:19.968190Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04765","last_updated":"2025-07-07T08:43:46Z","snapshot_observed_at":"2026-08-16T23:44:48.848582Z","submitted_at":"2025-07-07T08:43:46Z","title":"GraphBrep: Learning B-Rep in Graph Structure for Efficient CAD Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:44:19.968190Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2507.04765"},"observation_digest":"sha256:6d2637e817d7aa219ef6565f7c9d1de001e2e5262b3c8defc38ba9a2e6124262","observation_id":"2ac6704a-0954-45e6-81d7-1949912fe120","resolution":{"observed_at":"2026-08-06T19:44:19.968190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":"2412.18608","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"d4e5d3c5-f06a-4d60-8dbf-da4fd6c3ee57","year":2024},"citing_paper":{"arxiv_id":"2605.16990","last_updated":"2026-05-16T13:21:22Z","snapshot_observed_at":"2026-08-15T01:46:55.665442Z","submitted_at":"2026-05-16T13:21:22Z","title":"DreamEdit3D: Personalization of Multi-View Diffusion Models for 3D Editing","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-19T20:27:54.127523Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2605.16990"},"observation_digest":"sha256:3d8c01c052d8c7de483d888cebddc5def913a10e24ef0ab0885301e43e54f0a7","observation_id":"8e2563a5-4fba-4d65-8c35-5a42575864c6","resolution":{"observed_at":"2026-05-19T20:32:45.747409Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-08-15T15:08:55.103003Z","title":"arXiv preprint arXiv:2412.18608 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.01825","last_updated":"2026-08-03T07:32:10Z","snapshot_observed_at":"2026-08-20T01:15:26.680255Z","submitted_at":"2026-08-03T07:32:10Z","title":"PartMat: Material-Aware 3D Part Decomposition with a Single Global Latent","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-15T15:08:55.103003Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2608.01825"},"observation_digest":"sha256:8922d3d6b1d2baef47a59a200bec3be366c131fe6e307e6510fda616542c7ed4","observation_id":"a2e694ef-f12f-4712-82b9-2f86d63b82e9","resolution":{"observed_at":"2026-08-15T15:08:55.103003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18608","snapshot_observed_at":"2026-08-12T00:33:58.485633Z","title":"PartGen: Part-level 3D generation and reconstruction with multi-view diffusion models.arXiv preprint arXiv:2412.18608, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.08053","last_updated":"2026-08-08T10:39:09Z","snapshot_observed_at":"2026-08-16T01:37:15.617871Z","submitted_at":"2026-08-08T10:39:09Z","title":"PhysX-CoT: Structured Physical Reasoning from a Single Image to Simulation-Ready 3D Assets","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T00:33:58.485633Z"},"links":{"cited_paper":"/paper/2412.18608","citing_paper":"/paper/2608.08053"},"observation_digest":"sha256:b66559eead045854d394926840b22cde2bc5a73200601718a5aa9abac8533e9c","observation_id":"58eb3d9b-306f-4888-9e15-e12b136d54f7","resolution":{"observed_at":"2026-08-12T00:33:58.485633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.18608/citation-record","integrity":"/paper/2412.18608/integrity","json":"/paper/2412.18608/citation-record.json","paper":"/paper/2412.18608"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T04:40:17.497448Z","title":"SPAGHETTI: editing implicit shapes through part aware generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.497448Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:44a75af0ad0cbd434676b8fdca474d56d352dba79e0a5a2b7f412379c65c5d62","observation_id":"39b3668f-7376-4f32-9678-1209b218ed65","resolution":{"observed_at":"2026-08-11T04:40:17.497448Z","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":"2026-08-11T04:40:17.501495Z","title":"Henriques, Andrea Vedaldi, and Andrew Zisserman","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.501495Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:397411c11e127c88f6267b5c110351d1198d7b8b26faa686e7e7cc037bd689b3","observation_id":"a730b09f-986f-4ba2-92cf-7251da660e0d","resolution":{"observed_at":"2026-08-11T04:40:17.501495Z","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":"2026-08-11T04:40:17.534752Z","title":"Henriques, Andrew Zisserman, and Andrea Vedaldi","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.534752Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ce1f135b6d333cd4663f2db63cba5f065868860bbfa5562daed5469505f0d572","observation_id":"77a9cb06-e9d0-4825-b723-9c99f6819c98","resolution":{"observed_at":"2026-08-11T04:40:17.534752Z","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":"2026-08-11T04:40:17.554203Z","title":"Neural part priors: Learning to optimize part-based object completion in rgb- d scans","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.554203Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:663cc7d384ab7da302c2a11c20760d3afcba45dfc2eb3503c3f1482986dd34a7","observation_id":"d2b9ff9d-1b6d-483b-9e92-d282c3035d17","resolution":{"observed_at":"2026-08-11T04:40:17.554203Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.19760","last_updated":"2024-04-30T17:59:51Z","snapshot_observed_at":"2026-08-16T13:56:30.805264Z","submitted_at":"2024-04-30T17:59:51Z","title":"Lightplane: Highly-Scalable Components for Neural 3D Fields","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.19760","snapshot_observed_at":"2026-08-11T04:40:17.563552Z","title":"Lightplane: Highly-scalable components for neu- ral 3d fields","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.563552Z"},"links":{"cited_paper":"/paper/2404.19760","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:7cae90d6d06b8570dcca03938b37911a0c140ac1312c1bbf9a441fb16e4e9ed2","observation_id":"3dc55305-2088-46e3-bcc3-29f23cfc5cd7","resolution":{"observed_at":"2026-08-11T04:40:17.563552Z","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":"2026-08-11T04:40:17.568492Z","title":"Chan, Koki Nagano, Matthew A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.568492Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:7bbd54f137c3736e0509d556b9b57f9b1684ebfa8248f37e98720953ab26b5d2","observation_id":"2b10c677-1cce-4550-9e03-5d56c5028c5b","resolution":{"observed_at":"2026-08-11T04:40:17.568492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.12409","last_updated":"2024-03-19T03:39:43Z","snapshot_observed_at":"2026-08-16T14:08:32.827923Z","submitted_at":"2024-03-19T03:39:43Z","title":"ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion Guidance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.12409","snapshot_observed_at":"2026-08-11T04:40:17.572907Z","title":"Comboverse: Compositional 3d assets creation using spatially-aware diffusion guidance","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.572907Z"},"links":{"cited_paper":"/paper/2403.12409","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:706cee5290913ea44921b1edc6008cee09cdd98919e6af57f6262086d3ad7007","observation_id":"8a7f253c-c1d2-4916-9509-71b65df09fb8","resolution":{"observed_at":"2026-08-11T04:40:17.572907Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16585","last_updated":"2024-04-02T05:10:02Z","snapshot_observed_at":"2026-08-19T22:18:38.052508Z","submitted_at":"2023-09-28T16:44:31Z","title":"Text-to-3D using Gaussian Splatting","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16585","snapshot_observed_at":"2026-08-11T04:40:17.580013Z","title":"Text-to-3D using Gaussian splatting","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.580013Z"},"links":{"cited_paper":"/paper/2309.16585","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:07e3543d56587e5da1edeffc22199285bfb10b2d09afa9494db4fc11cea8013d","observation_id":"7af3ca76-2acc-4caf-89e2-1a3f2062fa04","resolution":{"observed_at":"2026-08-11T04:40:17.580013Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.06738","last_updated":"2024-03-11T14:03:36Z","snapshot_observed_at":"2026-08-16T17:17:18.224007Z","submitted_at":"2024-03-11T14:03:36Z","title":"V3D: Video Diffusion Models are Effective 3D Generators","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.06738","snapshot_observed_at":"2026-08-11T04:40:17.604749Z","title":"V3D: Video diffusion models are effective 3D generators","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.604749Z"},"links":{"cited_paper":"/paper/2403.06738","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:fa6cb9bf71b0d23d2d382a06832846640b8f76caceb27850770addc821cd0352","observation_id":"d02a54c9-978f-446a-ad98-082951345489","resolution":{"observed_at":"2026-08-11T04:40:17.604749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15886","last_updated":"2025-02-16T03:41:41Z","snapshot_observed_at":"2026-08-16T13:32:23.242134Z","submitted_at":"2024-07-21T11:58:53Z","title":"CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15886","snapshot_observed_at":"2026-08-11T04:40:17.617175Z","title":"Catvton: Concatenation is all you need for virtual try-on with diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.617175Z"},"links":{"cited_paper":"/paper/2407.15886","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b5e97c660add325cc5baa091c7f21c57cc757b67177d7f020b7817b42d7b8b87","observation_id":"d8b94eca-9671-4a26-8399-5a63cc1b6eda","resolution":{"observed_at":"2026-08-11T04:40:17.617175Z","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":"2026-08-11T04:40:17.624518Z","title":"Set-the-scene: Global-local training for generating controllable nerf scenes","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.624518Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:6c9e60d688210c7e154335beb493623d0c3e85b562064ac5ec9e7cb750be2e84","observation_id":"8a146389-ee90-4be0-aa9d-30a501ca68fe","resolution":{"observed_at":"2026-08-11T04:40:17.624518Z","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":"2026-08-11T04:40:17.654864Z","title":"CSM text-to-3D cube 2.0, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.654864Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:e5a81e539880cd511a7e5e67ac77262b80c7ff7e6e52776ecdcbf9502b961a20","observation_id":"f7feb5a7-9a15-4789-a55b-5fee2d687147","resolution":{"observed_at":"2026-08-11T04:40:17.654864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.15807","last_updated":"2023-09-27T17:30:19Z","snapshot_observed_at":"2026-08-16T14:57:07.361681Z","submitted_at":"2023-09-27T17:30:19Z","title":"Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.15807","snapshot_observed_at":"2026-08-11T04:40:17.669136Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.669136Z"},"links":{"cited_paper":"/paper/2309.15807","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b90c7e6b60708d1364bd027912aabc7cc70def8ae9823374ff55e08df0d6092b","observation_id":"2c2289b7-e1fd-4e72-a0d0-89f9768a437c","resolution":{"observed_at":"2026-08-11T04:40:17.669136Z","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":"2026-08-11T04:40:17.694646Z","title":"Rodin text-to-3D gen-1 (0525) v0.5, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.694646Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ebb22466224a6966c765b55cd030bc6e3dfbe7fc18739892fc69396156cf32de","observation_id":"453a1f2b-568c-45df-bad7-bc635cc0aea9","resolution":{"observed_at":"2026-08-11T04:40:17.694646Z","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":"2026-08-11T04:40:17.727781Z","title":"Google scanned objects: A high-quality dataset of 3d scanned household items","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.727781Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ac696f077ae1ee46c042f0a33ea5f87c5c6c51ea93093ff525497f3babdf6bf1","observation_id":"7f47b12f-3e4b-4740-b98d-0aba0ff1ef8f","resolution":{"observed_at":"2026-08-11T04:40:17.727781Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-11T04:40:17.736804Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.736804Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:8100aa8d74f3313a093c2045517591fe35e3381cae313769f90345927f2597ba","observation_id":"8fcb49fc-06c0-4eba-9d2e-c51f4880aae4","resolution":{"observed_at":"2026-08-11T04:40:17.736804Z","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":"2026-08-11T04:40:17.742442Z","title":"Efros, and Aleksander Holynski","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.742442Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:1b9a8099035747030c899ff895f96c5fe74fd9ef1c97fba521ebcc49385b3480","observation_id":"3bd03185-f799-4a55-8148-747609e296d0","resolution":{"observed_at":"2026-08-11T04:40:17.742442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.10314","last_updated":"2024-05-16T17:59:05Z","snapshot_observed_at":"2026-08-15T07:34:03.035482Z","submitted_at":"2024-05-16T17:59:05Z","title":"CAT3D: Create Anything in 3D with Multi-View Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.10314","snapshot_observed_at":"2026-08-11T04:40:17.764769Z","title":"Barron, and Ben Poole","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.764769Z"},"links":{"cited_paper":"/paper/2405.10314","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:36ca4b877830915e62336f8ca2c85125321ac6b49b731766c8670058ac7026fe","observation_id":"52f0c828-d438-42a0-ad90-9c60a3c80b60","resolution":{"observed_at":"2026-08-11T04:40:17.764769Z","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":"2026-08-11T04:40:17.783921Z","title":"Freeman, and Thomas Funkhouser","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.783921Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:05a245a085902cfe13febd9476d0fd9580c1422973e01e6f692359c258a77486","observation_id":"a22be49b-3b32-4030-998b-ab5627f5d09d","resolution":{"observed_at":"2026-08-11T04:40:17.783921Z","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":"2026-08-11T04:40:17.798711Z","title":"Funkhouser","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.798711Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:6f7c521719e6b0aba2a13bae29badaee070de783ea72970e389c1caff58af3be","observation_id":"aafb97fa-21b4-4e0f-8051-1946184083ad","resolution":{"observed_at":"2026-08-11T04:40:17.798711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05371","last_updated":"2023-03-27T18:04:20Z","snapshot_observed_at":"2026-08-18T12:01:25.394018Z","submitted_at":"2023-03-09T16:18:14Z","title":"3DGen: Triplane Latent Diffusion for Textured Mesh Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05371","snapshot_observed_at":"2026-08-11T04:40:17.813806Z","title":"3DGen: Triplane latent diffusion for textured mesh generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.813806Z"},"links":{"cited_paper":"/paper/2303.05371","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:1b4f3aac6afe3c9dd6d3d73320a8dd75adab4ae51bcc52ca001424f0955f155a","observation_id":"43950879-7922-497e-8320-4de3c6a81060","resolution":{"observed_at":"2026-08-11T04:40:17.813806Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.00890","last_updated":"2025-06-02T03:28:40Z","snapshot_observed_at":"2026-08-16T13:13:38.928420Z","submitted_at":"2024-10-01T17:29:43Z","title":"Flex3D: Feed-Forward 3D Generation with Flexible Reconstruction Model and Input View Curation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.00890","snapshot_observed_at":"2026-08-11T04:40:17.833820Z","title":"Flex3d: Feed-forward 3d genera- tion with flexible reconstruction model and input view cu- ration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.833820Z"},"links":{"cited_paper":"/paper/2410.00890","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ba550a69869a86ab668274989ad744d4a5a9ec666ed8f09c6982f667eff3cfb5","observation_id":"35fc59b8-3796-4ea0-8b23-c61676c906b9","resolution":{"observed_at":"2026-08-11T04:40:17.833820Z","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":"2026-08-11T04:40:17.842228Z","title":"Vfusion3d: Learning scalable 3d generative models from video diffu- sion models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.842228Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:bdd282abf0714e70b633001daa15c19ad49b7230144fc0a51dfe848597de2119","observation_id":"f253b6fa-5522-49ea-b813-92bef8097817","resolution":{"observed_at":"2026-08-11T04:40:17.842228Z","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":"2026-08-11T04:40:17.855665Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.855665Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:fd7ddc5bf77d11f7898554adc172ea1d49e4e67f94807929e2030cc23e09c402","observation_id":"a75b8dcc-5de2-403f-afd4-1483c5557e02","resolution":{"observed_at":"2026-08-11T04:40:17.855665Z","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":"2026-08-11T04:40:17.891176Z","title":"ViewDiff: 3D-consistent image generation with text-to-image models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.891176Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:971625bebc7a5b0c30ba73ad048b1797e4570b6267938371d197f9288088246d","observation_id":"99f1f123-8780-474d-a905-29cffc6674fc","resolution":{"observed_at":"2026-08-11T04:40:17.891176Z","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":"2026-08-11T04:40:17.908311Z","title":"LRM: Large reconstruction model for single im- age to 3D","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.908311Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:94e78ba4d3da63406b27fc60bab3458517f81ddf7bce621433e368edf74244a8","observation_id":"c19dc871-8324-4a64-85aa-9fb4c2d4cdd8","resolution":{"observed_at":"2026-08-11T04:40:17.908311Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.12422","last_updated":"2024-05-06T14:23:25Z","snapshot_observed_at":"2026-08-20T19:40:18.680066Z","submitted_at":"2023-06-21T17:59:45Z","title":"DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.12422","snapshot_observed_at":"2026-08-11T04:40:17.918577Z","title":"Dreamtime: An im- proved optimization strategy for text-to-3D content cre- ation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.918577Z"},"links":{"cited_paper":"/paper/2306.12422","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:f5f10df7f7b2f06776983b0be6fb27b3d6cd245fce0aee9d92607a02d7910368","observation_id":"849ead89-7ac8-43d7-8a75-86725b2b18c8","resolution":{"observed_at":"2026-08-11T04:40:17.918577Z","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":"2026-08-11T04:40:17.924261Z","title":"Neu- ral template: Topology-aware reconstruction and disentan- gled generation of 3d meshes","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.924261Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:721c8a8e8d6e754e45ba86d7621802f85c3fae0149d1b2224953dd0b22688496","observation_id":"b347403f-862c-4fff-b7ff-283356989140","resolution":{"observed_at":"2026-08-11T04:40:17.924261Z","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":"2026-08-11T04:40:17.936155Z","title":"H ´enaff, Matthew M","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.936155Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:76c2aa6596b0012d8736c1f95e1f779d6a2d0564401db4d492ce3863bbe41867","observation_id":"19951bb9-1a5e-41b9-bfd2-9a4c18e3d8a7","resolution":{"observed_at":"2026-08-11T04:40:17.936155Z","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":"2026-08-11T04:40:17.942434Z","title":"CodeNeRF: Disen- tangled neural radiance fields for object categories","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.942434Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:f2f2489547b17d4a34c5a0a32c6eee8b54e9a3ec57c1cfc6a75251f7df64f171","observation_id":"f96cf934-1768-4743-b770-fc4bd07664be","resolution":{"observed_at":"2026-08-11T04:40:17.942434Z","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":"2026-08-11T04:40:17.950779Z","title":"Shap-E: Generating condi- tional 3D implicit functions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.950779Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ff70d2c7bf8721441c95d95d92df9c9d6fcb45e75d193a378455d66d45d79cdc","observation_id":"a899d67a-1e44-4ba4-9f3b-6a8bfee52599","resolution":{"observed_at":"2026-08-11T04:40:17.950779Z","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":"2026-08-11T04:40:17.955695Z","title":"3D Gaussian Splatting for real-time radiance field rendering","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.955695Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:31306ffbebe818f07d42d8b344235e630dda88576fe9b2c86fa85bf4d42117eb","observation_id":"2bef1bbc-97bd-4b11-84f1-dcbb72fb0021","resolution":{"observed_at":"2026-08-11T04:40:17.955695Z","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":"2026-08-11T04:40:17.961404Z","title":"LERF: language embed- ded radiance fields","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.961404Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ae5f99e197ceeac1886af415a4ac0b72e1e630ba7f484b8019fa6f92a25256fa","observation_id":"9281bdc5-a419-461c-a042-2416991dda02","resolution":{"observed_at":"2026-08-11T04:40:17.961404Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.09419","last_updated":"2024-01-17T18:57:53Z","snapshot_observed_at":"2026-08-16T14:26:42.016906Z","submitted_at":"2024-01-17T18:57:53Z","title":"GARField: Group Anything with Radiance Fields","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.09419","snapshot_observed_at":"2026-08-11T04:40:17.967278Z","title":"Garfield: Group anything with radiance fields","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.967278Z"},"links":{"cited_paper":"/paper/2401.09419","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:9cd59969f43f43b72a57c32483936c0406d8dbd18720bd18bbc85e35d5f2a61a","observation_id":"63ce452d-2552-48c2-9fc2-9f8a922af7f0","resolution":{"observed_at":"2026-08-11T04:40:17.967278Z","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":"2026-08-11T04:40:17.973028Z","title":"Berg, Wan-Yen Lo, Piotr Doll´ar, and Ross Girshick","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.973028Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:bdd30f8dad0301ec7ff937ae64f8bee782c80dcc1fe686431bb95df304e43375","observation_id":"a0d27f2d-ac46-4dd3-9f1b-4d4315508410","resolution":{"observed_at":"2026-08-11T04:40:17.973028Z","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":"2026-08-11T04:40:17.981710Z","title":"Decomposing NeRF for editing via feature field dis- tillation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.981710Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:d0f53a434aae39f37fb0333bc6cd3418b652d8619bf1381ac4a7430346e3dc0f","observation_id":"2bed9c2e-8cc7-4e85-bfc5-6e29a32f89e0","resolution":{"observed_at":"2026-08-11T04:40:17.981710Z","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":"2026-08-11T04:40:17.985728Z","title":"SALAD: part-level latent diffusion for 3D shape generation and manipulation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:17.985728Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:3b76d6bd044d11f9595b4c2d2f1eb661b6565563c428d386653c4aafa62cbe54","observation_id":"a7adab7e-8a72-422b-b42d-1199fe4fc17f","resolution":{"observed_at":"2026-08-11T04:40:17.985728Z","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":"2026-08-11T04:40:18.002648Z","title":"Larlus, G","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.002648Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:14766313454fe03b47c98268af7ab2ce3f9116a26ca39872ba697e6ad33968c8","observation_id":"0e773a76-4bce-47c7-93f3-4f665318ede8","resolution":{"observed_at":"2026-08-11T04:40:18.002648Z","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":"2026-08-11T04:40:18.016720Z","title":"Instant3D: Fast text-to-3D with sparse-view generation and large reconstruction model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.016720Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:0c2936498d1c31ed9e86d61773d29e97e3600a194056a3f7d11fa2d0bae4060e","observation_id":"87ff3b98-eb92-4243-8068-10b684ef4bc2","resolution":{"observed_at":"2026-08-11T04:40:18.016720Z","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":"2026-08-11T04:40:18.044764Z","title":"Focaldreamer: Text-driven 3d editing via focal-fusion assembly, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.044764Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:a4f0d096ed29d3d140b1774fcefa7257d806f3dad37af75d4c27d53e8da96c27","observation_id":"86cf66d0-e6b9-4406-a69b-2c731fe9e8f0","resolution":{"observed_at":"2026-08-11T04:40:18.044764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.10440","last_updated":"2023-03-25T17:32:25Z","snapshot_observed_at":"2026-08-20T19:38:17.943289Z","submitted_at":"2022-11-18T18:59:59Z","title":"Magic3D: High-Resolution Text-to-3D Content Creation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.10440","snapshot_observed_at":"2026-08-11T04:40:18.074739Z","title":"Magic3D: High-resolution text-to-3D content creation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.074739Z"},"links":{"cited_paper":"/paper/2211.10440","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:7915d8f78de0a585503ca7db2650b0fea784b548aa2c06489990b4a7d1db2453","observation_id":"508daef8-224d-43a1-9092-1fbeeef1dfc8","resolution":{"observed_at":"2026-08-11T04:40:18.074739Z","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":"2026-08-11T04:40:22.031593Z","title":"Guibas, and Paul Guerrero","venue":null,"work_id":"a88b18d2-5f22-4e0e-b748-8a9590c2b97c","year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.079176Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:e87587c861dad79c427a70849a75b04a48e8a6292e6ec993ba09d4428a2920d1","observation_id":"1837465b-03bc-4fcb-8314-cf52638ddc4a","resolution":{"observed_at":"2026-08-11T04:40:22.037712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:22.008383Z","title":"Common diffusion noise schedules and sample steps are flawed","venue":null,"work_id":"cbdea1c4-879a-4d3e-93de-43d19cca7562","year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.091738Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:a36077cd264e817d2d090b0d1f40b63faf6dc49b1b06ff4871adb5bfd168187d","observation_id":"1ee8b24f-4c89-4016-b55a-2cd2e0b655d8","resolution":{"observed_at":"2026-08-11T04:40:22.014985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16888","last_updated":"2024-05-27T07:10:21Z","snapshot_observed_at":"2026-08-16T13:49:10.958739Z","submitted_at":"2024-05-27T07:10:21Z","title":"Part123: Part-aware 3D Reconstruction from a Single-view Image","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16888","snapshot_observed_at":"2026-08-11T04:40:18.119704Z","title":"Part123: Part-aware 3d reconstruction from a single-view image","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.119704Z"},"links":{"cited_paper":"/paper/2405.16888","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:0514dc932f1090839d15f21b6a777743a4356f276a3b0c71ef1be514ec643243","observation_id":"b67f44ce-1423-4526-a5e2-515217632328","resolution":{"observed_at":"2026-08-11T04:40:18.119704Z","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":"2026-08-11T04:40:21.988623Z","title":"One-2-3-45: Any single image to 3D mesh in 45 seconds without per- shape optimization","venue":null,"work_id":"5b6fe0d5-d714-438e-b475-02e8cb89f135","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.132460Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:e54d4b906167d9a870e0e293529c45d5d53191b46400927aee3a993216c3b301","observation_id":"e2af10c6-92d6-4bf7-8849-568192bbf1d3","resolution":{"observed_at":"2026-08-11T04:40:21.998428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.954967Z","title":"PartSLIP: low-shot part segmentation for 3D point clouds via pretrained image- language models","venue":null,"work_id":"42d832a3-cbc9-4666-bb3f-79af08da58c3","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.155714Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:87002899272e5479acfcca468fb7fdd2f9e0ccc0e5a057bec44444eeec63a5dc","observation_id":"6c1eaa66-a6cf-46aa-b3b6-1a350f008498","resolution":{"observed_at":"2026-08-11T04:40:21.969243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.883005Z","title":"Zero-1-to-3: Zero-shot one image to 3D object","venue":null,"work_id":"e7637401-5c69-43ab-8d16-1f9a52a92723","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.184938Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:400f135baebeaa35674f2c91bebde97e7d8d88e92c671a2494a2e25b8b6f6fa9","observation_id":"04395efd-675e-4fea-8c06-6a15ddb49f2b","resolution":{"observed_at":"2026-08-11T04:40:21.914751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.851830Z","title":"Composable part-based manip- ulation","venue":null,"work_id":"227b0161-1a6d-4ac8-9a11-e287f271ac75","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.204891Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:064da644633a54a8109e5411306424bc9563b1e63620a463986b018ef926dce2","observation_id":"e233ca0c-b887-4fda-b2e8-34df4647095b","resolution":{"observed_at":"2026-08-11T04:40:21.857705Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.03453","last_updated":"2024-04-15T10:28:44Z","snapshot_observed_at":"2026-08-12T22:52:54.817720Z","submitted_at":"2023-09-07T02:28:04Z","title":"SyncDreamer: Generating Multiview-consistent Images from a Single-view Image","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.03453","snapshot_observed_at":"2026-08-11T04:40:18.219365Z","title":"SyncDreamer: Generating multiview-consistent images from a single-view image","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.219365Z"},"links":{"cited_paper":"/paper/2309.03453","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:f644f988bdede8cda4f45e8209427546f569e87699acf828a13f84c35ca1d275","observation_id":"1128b3ce-cea5-4ff4-aaac-08509ba0941e","resolution":{"observed_at":"2026-08-11T04:40:18.219365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.15008","last_updated":"2023-11-08T16:50:08Z","snapshot_observed_at":"2026-08-20T15:07:45.973811Z","submitted_at":"2023-10-23T15:02:23Z","title":"Wonder3D: Single Image to 3D using Cross-Domain Diffusion","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.15008","snapshot_observed_at":"2026-08-11T04:40:18.251545Z","title":"Wonder3D: Single image to 3D using cross-domain diffu- sion","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.251545Z"},"links":{"cited_paper":"/paper/2310.15008","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:a3164136d1557c1d9608fccde6014a026f5bb219603ed385a837cb5bc47da585","observation_id":"54437b8a-5da9-45b0-a9a9-9b9ec3d218ab","resolution":{"observed_at":"2026-08-11T04:40:18.251545Z","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":"2026-08-11T04:40:21.795013Z","title":"Genie text-to-3D v1.0, 2024","venue":null,"work_id":"78002490-051e-4a8d-9e02-c2036bd19e48","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.274162Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:c8618ff08f9174c09391b1d01d697a3305c62d13142999182717c3bb2705e13b","observation_id":"4b71cc6d-475c-4080-b52d-0e2004a2c928","resolution":{"observed_at":"2026-08-11T04:40:21.805020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.07279","last_updated":"2023-06-16T03:58:15Z","snapshot_observed_at":"2026-08-16T15:24:31.128386Z","submitted_at":"2023-06-12T17:59:03Z","title":"Scalable 3D Captioning with Pretrained Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.07279","snapshot_observed_at":"2026-08-11T04:40:18.305626Z","title":"Scalable 3d captioning with pretrained models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.305626Z"},"links":{"cited_paper":"/paper/2306.07279","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:f3fe46930d18cf4e55ac03d1b0bdf939aad55e83a8e884058019961d5476d874","observation_id":"50b47aac-066c-494b-82f4-166fd0873a0b","resolution":{"observed_at":"2026-08-11T04:40:18.305626Z","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":"2026-08-11T04:40:21.714753Z","title":"Grounding language with visual affordances over unstruc- tured data","venue":null,"work_id":"f420f0c2-32c2-442e-b4fe-4f5a2940985c","year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.334750Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:1426e147fb2334036a1b1a9a0f0014b4b35a7448865fba9df1102ba78cb0263a","observation_id":"e0c08b00-eff4-46f1-8f61-3883be900a22","resolution":{"observed_at":"2026-08-11T04:40:21.744754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.656140Z","title":"RealFusion: 360 reconstruction of any object from a single image","venue":null,"work_id":"d292020f-83d3-4cd4-b946-ff22e8da95a7","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.339463Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:bb5c982a52eaf4ffba305e3227938566c345a1fa4e0145a97c2a688895990196","observation_id":"2a558b9c-0436-4cd9-872c-5fc510d7ffc2","resolution":{"observed_at":"2026-08-11T04:40:21.670840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.637241Z","title":"PC2: Projection-conditioned point cloud diffusion for single-image 3d reconstruction","venue":null,"work_id":"3669971a-6b14-40fb-85d7-62c0604eecef","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.342988Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:24897c6f19be67f6c9d1ce700a272a971417bb9f86e6cbd93cb5120370487576","observation_id":"30e0d6cf-10e5-48de-9381-b2ca988ee3a0","resolution":{"observed_at":"2026-08-11T04:40:21.644131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.609709Z","title":"IM-3D: Iterative multiview diffusion and re- construction for high-quality 3D generation","venue":null,"work_id":"b16e8ddf-8097-4c7c-8a3f-6af829a4185f","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.352152Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:5eef1d28708766399519c5c5bf1f979578fbef7d534f304959818675302ccc23","observation_id":"1e1e5e61-2aba-4aac-b76c-a57987ecd818","resolution":{"observed_at":"2026-08-11T04:40:21.616466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.588232Z","title":"Mescheder, M","venue":null,"work_id":"afec06cf-2451-4c22-ba1d-130769c1bb83","year":2019},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.368258Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:f54972228b2a5644e8f7b1bbba07ddac7dcb62a6cb351029b423067ac5a3686d","observation_id":"baf49aee-7c62-49ef-9b06-030184626ea0","resolution":{"observed_at":"2026-08-11T04:40:21.594949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.568743Z","title":"Meshy text-to-3D v3.0, 2024","venue":null,"work_id":"2201770d-88aa-4263-8387-74dc5e79c3b0","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.372314Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ca6a6d0ce78e392d66ca246268f5141949cf50d31eeecd3d13342bc134ce1acc","observation_id":"c0e4ab3f-80d7-4d1a-9286-1def566768a0","resolution":{"observed_at":"2026-08-11T04:40:21.572519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.552682Z","title":"Srinivasan, Matthew Tancik, Jonathan T","venue":null,"work_id":"ea9b98b8-ac3f-4af2-b227-cda5f850b8ad","year":2020},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.384449Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:fbbee7abd4e508cf90709acecf4fddd89cade7c0ffe7ba5cd71510dd30c59328","observation_id":"07aec54d-948d-495b-ae56-1dc1bf2e37c6","resolution":{"observed_at":"2026-08-11T04:40:21.557786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.535894Z","title":"Differentiable blocks world: Qualitative 3d decomposition by rendering primitives","venue":null,"work_id":"fe72d342-5a61-420a-bfd7-c0652f77a77d","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.424093Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:af18c8cac8b4d8535e2f41348fd329f6c83600a28039aaff83b32804371ea63c","observation_id":"8b491238-a600-497a-a447-e5ef3168b2d7","resolution":{"observed_at":"2026-08-11T04:40:21.541917Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.511721Z","title":"Diff- Facto: controllable part-based 3D point cloud generation with cross diffusion","venue":null,"work_id":"2372cc10-7200-46ce-aeb5-9c90a3a8172d","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.433702Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:68aa6074953fe6103a845f87382aeba7c4063c1c2903bdd5a9b3fc70a88539aa","observation_id":"91e07644-d184-41ce-8bdc-15789a8d1da2","resolution":{"observed_at":"2026-08-11T04:40:21.519215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.08751","last_updated":"2022-12-16T23:22:59Z","snapshot_observed_at":"2026-08-17T05:04:12.370590Z","submitted_at":"2022-12-16T23:22:59Z","title":"Point-E: A System for Generating 3D Point Clouds from Complex Prompts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.08751","snapshot_observed_at":"2026-08-11T04:40:18.441309Z","title":"Point-E: A system for gener- ating 3D point clouds from complex prompts","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.441309Z"},"links":{"cited_paper":"/paper/2212.08751","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:67cd3c72a1b2f4799914ba36612c07dc2e408e7ea7fc6b3cdf3a9d2c67ad3291","observation_id":"5c2f4013-7066-4f6e-bac1-9bd323f1adf4","resolution":{"observed_at":"2026-08-11T04:40:18.441309Z","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":"2026-08-11T04:40:21.464136Z","title":"Aria digital twin: A new benchmark dataset for egocentric 3d machine percep- tion, 2023","venue":null,"work_id":"6804608b-f582-4a8b-af53-ed201b66a990","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.448943Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b38705edb1f8af749ac1c20b0200c7b2e0a328733ee1a9e182910dea8524e2e3","observation_id":"836e0091-907a-475d-91b1-999a9d9a28e3","resolution":{"observed_at":"2026-08-11T04:40:21.477132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.12218","last_updated":"2023-03-23T00:29:24Z","snapshot_observed_at":"2026-08-16T15:46:24.357441Z","submitted_at":"2023-03-21T22:37:16Z","title":"Compositional 3D Scene Generation using Locally Conditioned Diffusion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.12218","snapshot_observed_at":"2026-08-11T04:40:18.467199Z","title":"Compositional 3d scene generation using locally conditioned diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.467199Z"},"links":{"cited_paper":"/paper/2303.12218","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b00ec9edb692f31c371d25bb872e2599bfefa2404003db4b5aa9354a77942999","observation_id":"7bc9fe53-d22b-433f-9571-d90c8c7742e2","resolution":{"observed_at":"2026-08-11T04:40:18.467199Z","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":"2026-08-11T04:40:21.394335Z","title":"Barron, and Ben Milden- hall","venue":null,"work_id":"9328502a-bb10-44c7-af04-8a15f7a28244","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.487531Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:5229e7ab5b6cf604e43c375f627411da1fc32db8396346e20a68e35182b41db4","observation_id":"94114291-57b2-48f4-b93a-ecba0c83f4cd","resolution":{"observed_at":"2026-08-11T04:40:21.447230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.17843","last_updated":"2023-07-23T21:27:30Z","snapshot_observed_at":"2026-08-20T12:03:29.864144Z","submitted_at":"2023-06-30T17:59:08Z","title":"Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.17843","snapshot_observed_at":"2026-08-11T04:40:18.493548Z","title":"Magic123: One image to high-quality 3D object generation using both 2D and 3D diffusion priors","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.493548Z"},"links":{"cited_paper":"/paper/2306.17843","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:2d4ba1a863b9d84b7f02c1647a86b5ff0a4732a6e9f7b359b2567956640f7c87","observation_id":"32db37c4-bb67-4391-b35d-de77a06a8d24","resolution":{"observed_at":"2026-08-11T04:40:18.493548Z","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":"2026-08-11T04:40:21.343345Z","title":"LangSplat: 3D language Gaussian splat- ting","venue":null,"work_id":"cd2613dc-43b9-42d6-9a16-edfe526be635","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.499735Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:58f5d4116c87de1754478b86b93a469796218550b5de8115829412f2c12d34fd","observation_id":"2d979aed-ade9-44f2-9dbf-f415f042e2ae","resolution":{"observed_at":"2026-08-11T04:40:21.351286Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.16918","last_updated":"2023-12-24T16:36:09Z","snapshot_observed_at":"2026-08-16T14:39:35.058205Z","submitted_at":"2023-11-28T16:22:33Z","title":"RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3D","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.16918","snapshot_observed_at":"2026-08-11T04:40:18.524754Z","title":"Richdreamer: A gen- eralizable normal-depth diffusion model for detail richness in text-to-3D","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.524754Z"},"links":{"cited_paper":"/paper/2311.16918","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:fb2589d26e46a37f7a77227e79702981e484bbfede22b4011fbdb341ad1eae7a","observation_id":"68990c3e-e84b-4479-b80a-5aa798bcf09f","resolution":{"observed_at":"2026-08-11T04:40:18.524754Z","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":"2026-08-11T04:40:21.318222Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"d52b5022-e52d-49d1-a72a-70892c02d343","year":2021},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.534450Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:8e34ab57f009bb42d834b850e3655a55aee462bd467c5e606e97bdb104561f6b","observation_id":"2fe2f05a-875d-4031-b17e-8ae6a33cd3ad","resolution":{"observed_at":"2026-08-11T04:40:21.328211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00714","last_updated":"2024-10-28T16:37:57Z","snapshot_observed_at":"2026-07-06T18:55:41.459417Z","submitted_at":"2024-08-01T17:00:08Z","title":"SAM 2: Segment Anything in Images and Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00714","snapshot_observed_at":"2026-08-11T04:40:18.538971Z","title":"SAM 2: Segment anything in images and videos","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.538971Z"},"links":{"cited_paper":"/paper/2408.00714","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:da56a3001bbc8dc3a91a2a954e09145d4c6da8b61120cc9fe3ae05c13b9e7d4e","observation_id":"06c4f53a-276b-475d-9cb4-a3f7c4fe04ef","resolution":{"observed_at":"2026-08-11T04:40:18.538971Z","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":"2026-08-11T04:40:21.256561Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"ae93e656-459d-4430-a9a3-80c1951b49ad","year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.553292Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b0777bf2a3bf4ed6ac105777ce8c2f354f4e89396574fb0e4302e8337ca2305f","observation_id":"a0525b2b-7f03-438e-b816-8a69a299f4a0","resolution":{"observed_at":"2026-08-11T04:40:21.277387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.00512","last_updated":"2022-06-07T09:17:35Z","snapshot_observed_at":"2026-08-12T01:14:44.484432Z","submitted_at":"2022-02-01T16:07:25Z","title":"Progressive Distillation for Fast Sampling of Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.00512","snapshot_observed_at":"2026-08-11T04:40:18.562237Z","title":"Progressive distillation for fast sampling of diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.562237Z"},"links":{"cited_paper":"/paper/2202.00512","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:c945ef999b0962bc54877639c0209ba99ed32036c82ab332aeaef9419c97c3c5","observation_id":"451cb5bb-a370-4dc2-bc68-4b0e24d0f8ce","resolution":{"observed_at":"2026-08-11T04:40:18.562237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.15110","last_updated":"2023-10-23T17:18:59Z","snapshot_observed_at":"2026-08-15T06:11:26.743203Z","submitted_at":"2023-10-23T17:18:59Z","title":"Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.15110","snapshot_observed_at":"2026-08-11T04:40:18.567551Z","title":"Zero123++: a single image to consistent multi- view diffusion base model.arXiv.cs, abs/2310.15110, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.567551Z"},"links":{"cited_paper":"/paper/2310.15110","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:fa8d60850aa9fe61462aa2f9283ef11cf242935085347182b77c4d0649b54a2b","observation_id":"97d633a2-4773-4e8f-96a5-27752a04c9b1","resolution":{"observed_at":"2026-08-11T04:40:18.567551Z","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":"2026-08-11T04:40:21.226378Z","title":"MVDream: Multi-view diffusion for 3D generation","venue":null,"work_id":"0d36a6a0-b4a5-4f21-8b1d-3e15ed00b54f","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.573942Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:d6e0409ef178076d299d6dacf9d179b1e29e0651dea7d7d39a423579c7f81a5f","observation_id":"365f1e44-c897-4aa8-b6ee-7d1fc55c1602","resolution":{"observed_at":"2026-08-11T04:40:21.231641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.176068Z","title":"What does clip know about a red circle? vi- sual prompt engineering for vlms","venue":null,"work_id":"deb4e116-8bf1-45c6-b85e-848ca9bcf1b0","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.578580Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:6ba252ddb03ab7c6f4282560c78b0a6777de6acb5f4b4eb52a46829da833415c","observation_id":"b9adbda3-1eb6-4ba4-a687-2754edb14a6e","resolution":{"observed_at":"2026-08-11T04:40:21.182820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.145365Z","title":"Meta 3D Asset Gen: Text-to-mesh gener- ation with high-quality geometry, texture, and PBR mate- rials","venue":null,"work_id":"da3f5c57-6ad1-4e8f-867e-79101ec4f83f","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.588224Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:96605bebba911c41d99415b94856ebacbe5ae74c9c304a92a78a7b54150a1406","observation_id":"9950f9f5-6b87-43ea-b6cd-134bee1cdae4","resolution":{"observed_at":"2026-08-11T04:40:21.158379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.118858Z","title":"Denois- ing diffusion implicit models","venue":null,"work_id":"bf2798cf-7840-4ac5-9e43-574e8fd2e0a0","year":2021},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.598616Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:dd1c3cb79cd355ca848b4e09f7c0f8ca89dcc060e854942c6af1a735f0f203fa","observation_id":"3509dd89-1209-4b47-86f3-2eb4536a34a3","resolution":{"observed_at":"2026-08-11T04:40:21.131660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.16818","last_updated":"2023-10-26T06:54:22Z","snapshot_observed_at":"2026-08-18T06:53:22.500649Z","submitted_at":"2023-10-25T17:50:10Z","title":"DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.16818","snapshot_observed_at":"2026-08-11T04:40:18.606497Z","title":"DreamCraft3D: Hier- archical 3D generation with bootstrapped diffusion prior","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.606497Z"},"links":{"cited_paper":"/paper/2310.16818","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b5a2f4142f0d24f300f71b526985bae81923dddb17c3142a11ad46687e2308e7","observation_id":"42269a71-59f6-4fb2-822d-c8355217b37d","resolution":{"observed_at":"2026-08-11T04:40:18.606497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16653","last_updated":"2024-03-29T08:39:23Z","snapshot_observed_at":"2026-07-06T16:25:05.493379Z","submitted_at":"2023-09-28T17:55:05Z","title":"DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16653","snapshot_observed_at":"2026-08-11T04:40:18.617885Z","title":"DreamGaussian: Generative gaussian splat- ting for efficient 3D content creation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.617885Z"},"links":{"cited_paper":"/paper/2309.16653","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b904f4169f5e24a7054322f05d21104fe951a37cdf997cf00a43338954e0370e","observation_id":"5f298d07-9ba0-4a22-ba78-93a73708b488","resolution":{"observed_at":"2026-08-11T04:40:18.617885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.14184","last_updated":"2023-04-03T07:18:27Z","snapshot_observed_at":"2026-08-19T02:01:49.254315Z","submitted_at":"2023-03-24T17:54:22Z","title":"Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.14184","snapshot_observed_at":"2026-08-11T04:40:18.626072Z","title":"Make-It-3D: High- fidelity 3d creation from A single image with diffusion prior","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.626072Z"},"links":{"cited_paper":"/paper/2303.14184","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:0e277a65ea9f15ce3f88c8ac0436832ea4fb0929bf8f851731ee09133a2ebe72","observation_id":"79f546b9-7933-447c-b97f-3381e231e60f","resolution":{"observed_at":"2026-08-11T04:40:18.626072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.12712","last_updated":"2024-04-30T04:11:58Z","snapshot_observed_at":"2026-08-17T11:37:16.366931Z","submitted_at":"2024-02-20T04:25:57Z","title":"MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.12712","snapshot_observed_at":"2026-08-11T04:40:18.639408Z","title":"MVDiffusion++: A dense high-resolution multi-view diffusion model for single or sparse-view 3d object reconstruction","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.639408Z"},"links":{"cited_paper":"/paper/2402.12712","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:1f13b60b2b024f8a50dfb1da66cdb01cf0bf38c159d85b266441a7872ced882c","observation_id":"0cd31803-ab96-47c3-a649-55c7af65fb57","resolution":{"observed_at":"2026-08-11T04:40:18.639408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.09554","last_updated":"2023-03-21T16:09:25Z","snapshot_observed_at":"2026-08-16T15:47:36.787471Z","submitted_at":"2023-03-16T17:59:22Z","title":"PartNeRF: Generating Part-Aware Editable 3D Shapes without 3D Supervision","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.09554","snapshot_observed_at":"2026-08-11T04:40:18.645209Z","title":"Emiris, Yannis Avrithis, and Leonidas J","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.645209Z"},"links":{"cited_paper":"/paper/2303.09554","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:601b9adeaa6b5c0c1f71f6f9f469361e3166a6b9ab6b7bb29a599492c491b793","observation_id":"b5258491-6946-4f4a-ae76-b3dca14207b1","resolution":{"observed_at":"2026-08-11T04:40:18.645209Z","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":"2026-08-11T04:40:21.084763Z","title":"Tripo3D text-to-3D, 2024","venue":null,"work_id":"dbff2c44-aae6-432b-b719-e14b376daeb5","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.651914Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:fb36bda7b56785ba2ac7dc7a82abc83d375266174bac91a7e0c8f4bf1f4a6839","observation_id":"57247d26-2b01-4e58-89bb-759f28351577","resolution":{"observed_at":"2026-08-11T04:40:21.097366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.035564Z","title":"Neural Feature Fusion Fields: 3D distillation of self-supervised 2D image representation","venue":null,"work_id":"25f577a7-568a-40a1-bea3-72bf6b01a271","year":2022},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.662081Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:ac94ef07b4b8774c1044d89554f13dcf56b15329a0206f3bea3e02df7c315b7a","observation_id":"2efae9c9-a1f9-4b11-a5b1-0d7cff2f447c","resolution":{"observed_at":"2026-08-11T04:40:21.052693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:21.020444Z","title":"Yeh, and Greg Shakhnarovich","venue":null,"work_id":"fc6020ad-e687-493a-8799-94781d83a47a","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.669730Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:bdfc4009a75d6a82d6989c56cc474d9efc4db68dc2af020341f58846f3443338","observation_id":"af02f86e-bdf1-4613-86d6-eb6413db6024","resolution":{"observed_at":"2026-08-11T04:40:21.025418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:20.983672Z","title":"ImageDream: Image-prompt multi-view diffusion for 3D generation","venue":null,"work_id":"0a0b4a07-4fe4-499a-9099-32c76cd549d5","year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.674639Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:10d247786864e22910619be442cffc32d07e4b245e842ac618f9c0596f80700e","observation_id":"5a2220a0-6796-4318-8393-61638f4978f1","resolution":{"observed_at":"2026-08-11T04:40:21.005355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16213","last_updated":"2023-11-22T07:34:38Z","snapshot_observed_at":"2026-08-18T13:58:32.234911Z","submitted_at":"2023-05-25T16:19:18Z","title":"ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.16213","snapshot_observed_at":"2026-08-11T04:40:18.678994Z","title":"ProlificDreamer: High- fidelity and diverse text-to-3D generation with variational score distillation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.678994Z"},"links":{"cited_paper":"/paper/2305.16213","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:0ebc23af48b63744b70f9278664f3cb2bb06a6a01ac743d4ed681bd572d41e78","observation_id":"1ffe7dd3-163c-4454-9578-6c735486891a","resolution":{"observed_at":"2026-08-11T04:40:18.678994Z","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":"2026-08-11T04:40:20.894738Z","title":"Novel view synthesis with diffusion models","venue":null,"work_id":"53df400f-8010-4b7d-be6b-4c02dc5ff6ec","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.684239Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:82a0df9a1f58e8305ffe63c386a2904f3b7c2b0e4762ee79032562f79ebd2d39","observation_id":"570be2f4-0bb9-4eae-adfe-2cfe80bf6b73","resolution":{"observed_at":"2026-08-11T04:40:20.933170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-11T04:40:20.866498Z","title":"Omniobject3d: Large- vocabulary 3d object dataset for realistic perception, re- construction and generation","venue":null,"work_id":"496b138a-d6d6-4690-8099-7aa358d8095b","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.693766Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:95e85e00afd855284c2eb2a8c3103a178eb404687c44410088c58e30d492fd4a","observation_id":"4b44ec0b-b799-4b77-8adf-14d81dd74897","resolution":{"observed_at":"2026-08-11T04:40:20.871911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07191","last_updated":"2024-04-14T16:54:24Z","snapshot_observed_at":"2026-08-13T18:57:44.379289Z","submitted_at":"2024-04-10T17:48:37Z","title":"InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07191","snapshot_observed_at":"2026-08-11T04:40:18.711760Z","title":"InstantMesh: efficient 3D mesh generation from a single image with sparse-view large reconstruction models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.711760Z"},"links":{"cited_paper":"/paper/2404.07191","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:31fe2863c8fb57d0237ae20b6fb28d7936b380fcaa205b222337676ced318004","observation_id":"1d59640c-1f57-4a67-809f-6a6a0ce8700f","resolution":{"observed_at":"2026-08-11T04:40:18.711760Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.14621","last_updated":"2024-03-21T17:59:34Z","snapshot_observed_at":"2026-08-20T17:33:33.568286Z","submitted_at":"2024-03-21T17:59:34Z","title":"GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.14621","snapshot_observed_at":"2026-08-11T04:40:18.731464Z","title":"GRM: Large gaussian reconstruction model for effi- cient 3D reconstruction and generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.731464Z"},"links":{"cited_paper":"/paper/2403.14621","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b858f723ab3359a435d9e20eb97245d7f8b27c35d92516556d6148a3d9f7b8e7","observation_id":"5bdf8527-e61f-4c93-b4ff-1c1e30759db9","resolution":{"observed_at":"2026-08-11T04:40:18.731464Z","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":"2026-08-11T04:40:20.846055Z","title":"DMV3D: Denoising multi- view diffusion using 3D large reconstruction model","venue":null,"work_id":"4cfdb3da-819b-462b-a4f5-893ef9f3d71d","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.744033Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:0571c0e9961398b2f4406f8f9608dc25b8b456cecd615d050af372a780c1dfe1","observation_id":"247dfc54-a133-48a1-bf7b-9ef5a0cce9a1","resolution":{"observed_at":"2026-08-11T04:40:20.852798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10343","last_updated":"2023-10-16T12:29:29Z","snapshot_observed_at":"2026-08-20T21:12:57.441609Z","submitted_at":"2023-10-16T12:29:29Z","title":"ConsistNet: Enforcing 3D Consistency for Multi-view Images Diffusion","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10343","snapshot_observed_at":"2026-08-11T04:40:18.762533Z","title":"ConsistNet: Enforcing 3D consistency for multi- view images diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.762533Z"},"links":{"cited_paper":"/paper/2310.10343","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:2b65bbc24dd33eade30d7b87dafc4e7d77eed531246889ddc6a94ea5bed91905","observation_id":"cdd0b05d-f5f6-4bcd-bfa7-201d47a010ef","resolution":{"observed_at":"2026-08-11T04:40:18.762533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03611","last_updated":"2024-03-26T10:13:11Z","snapshot_observed_at":"2026-08-16T14:37:05.974514Z","submitted_at":"2023-12-06T16:55:53Z","title":"DreamComposer: Controllable 3D Object Generation via Multi-View Conditions","version":2},"cited_work":{"arxiv_id":"2312.03611","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.03611","snapshot_observed_at":"2026-08-11T04:40:19.537951Z","title":"DreamComposer: Controllable 3D Object Generation via Multi-View Conditions","venue":"cs.CV","work_id":"d324432a-d935-425a-b9bb-5c47c7f8ba9d","year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.767406Z"},"links":{"cited_paper":"/paper/2312.03611","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:a1f98dd272024f537ff36e2f73f572f6985604d3a4cb984d5b3d52266a60bd7a","observation_id":"a43ed362-c665-4353-a4dc-fb84a10b94fc","resolution":{"observed_at":"2026-08-11T04:40:19.551579Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.09222","last_updated":"2024-04-24T10:34:45Z","snapshot_observed_at":"2026-08-16T14:34:39.455666Z","submitted_at":"2023-12-14T18:52:52Z","title":"Mosaic-SDF for 3D Generative Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.09222","snapshot_observed_at":"2026-08-11T04:40:18.775721Z","title":"Mosaic-SDF for 3D generative models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.775721Z"},"links":{"cited_paper":"/paper/2312.09222","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:41b39df27fba69545e27726f225bb851508b337afcd55a6f615254b206ad53b4","observation_id":"042cec4e-64c5-499b-9a47-f64772fe03bc","resolution":{"observed_at":"2026-08-11T04:40:18.775721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.06721","last_updated":"2023-08-13T08:34:51Z","snapshot_observed_at":"2026-07-06T16:05:39.158819Z","submitted_at":"2023-08-13T08:34:51Z","title":"IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.06721","snapshot_observed_at":"2026-08-11T04:40:18.825278Z","title":"Ip- adapter: Text compatible image prompt adapter for text-to- image diffusion models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.825278Z"},"links":{"cited_paper":"/paper/2308.06721","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:fa40b2d7d43c188bd9e7bb89e1f5be457b988b57ae95359d5543d62abf49fcca","observation_id":"60d4b361-2760-42a6-81cf-65ad7e197b80","resolution":{"observed_at":"2026-08-11T04:40:18.825278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08529","last_updated":"2024-05-13T14:12:23Z","snapshot_observed_at":"2026-08-20T05:50:12.697859Z","submitted_at":"2023-10-12T17:22:24Z","title":"GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08529","snapshot_observed_at":"2026-08-11T04:40:18.833497Z","title":"GaussianDreamer: Fast generation from text to 3D gaussian splatting with point cloud priors","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.833497Z"},"links":{"cited_paper":"/paper/2310.08529","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:02f65bbf3f9ea9aa721ec37472374cddce20f3404bfbf7e61ea7e3bffaf60bbf","observation_id":"84daaf1d-267a-4901-bb16-f402e4edfa27","resolution":{"observed_at":"2026-08-11T04:40:18.833497Z","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":"2026-08-11T04:40:20.799852Z","title":"Omniseg3d: Omniversal 3d segmentation via hierarchical contrastive learning","venue":null,"work_id":"86d084f9-77ca-4a47-a093-93ef2ea961bd","year":2024},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.853278Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:b578cf53d6cf4cd33ca33d853e183615f7dbb29fb424652319b9991c31b7b34a","observation_id":"da15cc71-9a13-4662-ac9e-c184965de041","resolution":{"observed_at":"2026-08-11T04:40:20.807269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06744","last_updated":"2024-07-12T01:55:26Z","snapshot_observed_at":"2026-08-16T14:53:23.763554Z","submitted_at":"2023-10-10T16:14:20Z","title":"HiFi-123: Towards High-fidelity One Image to 3D Content Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06744","snapshot_observed_at":"2026-08-11T04:40:18.884747Z","title":"HiFi-123: Towards high-fidelity one image to 3D content generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.884747Z"},"links":{"cited_paper":"/paper/2310.06744","citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:f989894945d8525e6ad0615b2d6ca96eebbf52f25f7ced11fcb7cce3ed393fae","observation_id":"e37024eb-62bd-477d-9381-e1493932fb5d","resolution":{"observed_at":"2026-08-11T04:40:18.884747Z","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":"2026-08-11T04:40:20.757715Z","title":"Generative 3d part assembly via dynamic graph learning","venue":null,"work_id":"bc9c4425-b550-41cf-85c4-336dd4eebbfe","year":null},"citing_paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models","version":2},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-11T04:40:18.891082Z"},"links":{"citing_paper":"/paper/2412.18608"},"observation_digest":"sha256:e33c7d2e7abe1635cd63f9891babc9b1d0bce369c0b963b7a95e9162eadeda93","observation_id":"233fc078-9d28-4579-9b4b-1a13ecc25013","resolution":{"observed_at":"2026-08-11T04:40:20.786276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.18608","last_updated":"2024-12-29T16:01:58Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T02:05:41.349627Z","submitted_at":"2024-12-24T18:59:43Z","title":"PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Models"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":65,"verified_exact":1,"verified_fuzzy":34},"total_outbound_references":108},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 100 of 108 outbound references and 8 inbound Pith citation observations for arXiv:2412.18608."}