{"as_of":"2026-08-13T18:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4a9fe5f723001d7fd70eca74ca16bd04957e0e17712c6c8aa1ea26a3a0f2497d","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:47:52.576639Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2411.12290/citation-record","integrity":"/paper/2411.12290/integrity","json":"/paper/2411.12290/citation-record.json","paper":"/paper/2411.12290"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:47:52.363927Z","title":"Blended diffusion for text-driven editing of natural images","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.363927Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:1802abd2411b1db4f74d0e469d23ce103b6f7df86524d5694a017933a826f4ec","observation_id":"4fcaabb2-b13d-4bed-8fea-0880adafbf52","resolution":{"observed_at":"2026-08-12T17:47:52.363927Z","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":"2026-08-12T17:47:52.369395Z","title":"Se- mantickitti: A dataset for semantic scene understanding of lidar sequences","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.369395Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:665686177185914d2aa724b0e95af0d3f5a75ffe8da612e88bb26c267052c4be","observation_id":"6588dd23-3615-47e8-829b-e6b17ba2e9c4","resolution":{"observed_at":"2026-08-12T17:47:52.369395Z","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":"2026-08-12T17:47:52.374845Z","title":"The lov´asz-softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.374845Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:1f2ec538a6d1a33d375ed0a293b401d183cdcfe98173d4f6d1476ea8234b65f3","observation_id":"af8def67-9370-4774-a634-fcfcc8a009d7","resolution":{"observed_at":"2026-08-12T17:47:52.374845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.01401","last_updated":"2021-01-14T05:36:59Z","snapshot_observed_at":"2026-08-13T06:40:48.610500Z","submitted_at":"2018-01-04T15:25:26Z","title":"Demystifying MMD GANs","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.01401","snapshot_observed_at":"2026-08-12T17:47:52.381246Z","title":"Demystifying mmd gans","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.381246Z"},"links":{"cited_paper":"/paper/1801.01401","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:45961a6d2a564e501a8ed6a96d5e41ce8932210e81bec654c2fafa62ffaea843","observation_id":"22198e29-6980-431c-9524-2ee3bf26ef2d","resolution":{"observed_at":"2026-08-12T17:47:52.381246Z","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":"2026-08-12T17:47:52.386425Z","title":"Efficient geometry-aware 3d generative adversarial networks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.386425Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:bf13a0ff2fb755c75f5e5ee471e0f21d8aec9d3f3c691319a61a8e17ef2cff23","observation_id":"fc7b943e-30cd-45f5-8b54-a0b2c738f821","resolution":{"observed_at":"2026-08-12T17:47:52.386425Z","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":"2026-08-12T17:47:53.182534Z","title":"3d-r2n2: A unified approach for single and multi-view 3d object reconstruction","venue":null,"work_id":"9e051ed7-2619-4103-9e99-b00ccf0cad05","year":2016},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.391543Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:4566989bc5ff9dd157ec89542d169f66549c23373edc9ddf4cba99ce99965ee1","observation_id":"07dd1b5a-9876-496b-9c78-cdc0764f0690","resolution":{"observed_at":"2026-08-12T17:47:53.187979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.14819","last_updated":"2024-08-27T07:01:56Z","snapshot_observed_at":"2026-08-12T22:56:52.071384Z","submitted_at":"2024-08-27T07:01:56Z","title":"Build-A-Scene: Interactive 3D Layout Control for Diffusion-Based Image Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.14819","snapshot_observed_at":"2026-08-12T17:47:52.396667Z","title":"Build-a-scene: Interactive 3d layout control for diffusion-based image gen- eration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.396667Z"},"links":{"cited_paper":"/paper/2408.14819","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:6e0e2f881f580d160a947fdff4a9fe340d3c3df51135d86451cfcce9a528442e","observation_id":"0a39b6bd-0fe0-484e-8019-4ce662ec0816","resolution":{"observed_at":"2026-08-12T17:47:52.396667Z","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":"2026-08-12T17:47:52.402002Z","title":"Make-a-scene: Scene- based text-to-image generation with human priors","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.402002Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:d290d932cb883975ae74a8dbe0d06fb4be1b29d41cd3a05d1ec3617d1b112f64","observation_id":"ccd366f0-fb14-4e2b-91d7-60ea1fefdfa6","resolution":{"observed_at":"2026-08-12T17:47:52.402002Z","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":"2026-08-12T17:47:52.407589Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilib- rium","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.407589Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:0c2fd84c8a3d0079bffeca5e5829841cdf96ba2d62b81712473743e519c6e964","observation_id":"935702eb-70f6-4d83-ace9-c82062429f61","resolution":{"observed_at":"2026-08-12T17:47:52.407589Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.12598","last_updated":"2022-07-26T01:42:07Z","snapshot_observed_at":"2026-08-12T19:28:23.372660Z","submitted_at":"2022-07-26T01:42:07Z","title":"Classifier-Free Diffusion Guidance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.12598","snapshot_observed_at":"2026-08-12T17:47:52.412415Z","title":"Classifier-free diffusion guidance","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.412415Z"},"links":{"cited_paper":"/paper/2207.12598","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:99643bd46bdf1ee7d34de90cb29c9761eefe5b872b92d46feb97d433737954b5","observation_id":"787e9498-ece4-449b-b357-255220986724","resolution":{"observed_at":"2026-08-12T17:47:52.412415Z","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":"2026-08-12T17:47:53.142492Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":"68072077-e02b-4bb4-9d3b-4389dfd64d66","year":2020},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.417611Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:53c3b4b3fe5b0477171d9ae75973e3e7dce904f6bfd810f3cc0e3b9d051a456d","observation_id":"67b2dcdb-01f7-44d9-8ae9-c2c982ec9421","resolution":{"observed_at":"2026-08-12T17:47:53.147827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T17:47:53.124643Z","title":"Sym- phonize 3d semantic scene completion with contextual in- stance queries","venue":null,"work_id":"038b6624-adfe-4b1b-869d-1095a5f0073d","year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.422571Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:5cb529333330af6dfbc0dfdc0816701aa9a94ac2246e9756e078a342f48d5f56","observation_id":"a0786638-9290-43fa-91d5-d6d00fc44e00","resolution":{"observed_at":"2026-08-12T17:47:53.130642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T17:47:53.106917Z","title":"Diffindscene: Diffusion-based high-quality 3d indoor scene generation","venue":null,"work_id":"84c171f8-2e71-4cc5-9953-a792f3672528","year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.427159Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:3684ba078ebf7ef4e4d08d8b387f36c2fc03fa5002eb08657c67f41b88dd49df","observation_id":"3adb8731-4725-4963-b19d-03d4fd05c82e","resolution":{"observed_at":"2026-08-12T17:47:53.112511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T17:47:53.090470Z","title":"Holodiffusion: Training a 3d diffusion model using 2d images","venue":null,"work_id":"1427b5f9-5074-4ee4-a70e-e6f949962b5a","year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.432059Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:0b444cd94572c9544255eff25fe0d92238ebaba8eb8288aad1d1e3085e32fac6","observation_id":"722903cd-9d91-4f74-a8bb-cfe301306d64","resolution":{"observed_at":"2026-08-12T17:47:53.095642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.00527","last_updated":"2023-01-02T05:00:11Z","snapshot_observed_at":"2026-08-13T13:10:59.354615Z","submitted_at":"2023-01-02T05:00:11Z","title":"Diffusion Probabilistic Models for Scene-Scale 3D Categorical Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00527","snapshot_observed_at":"2026-08-12T17:47:52.437006Z","title":"Dif- fusion probabilistic models for scene-scale 3d categorical data","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.437006Z"},"links":{"cited_paper":"/paper/2301.00527","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:95240416fa69c976061f91fa7b064c7e8aa5a4630daeb44ce5274aec80aca0a1","observation_id":"b4c7d624-df16-4782-957d-ec27e617f18c","resolution":{"observed_at":"2026-08-12T17:47:52.437006Z","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":"2026-08-12T17:47:53.072586Z","title":"Semcity: Semantic scene genera- tion with triplane diffusion","venue":null,"work_id":"e1816beb-d6eb-4d0a-bb24-25f1624432a3","year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.442229Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:e58c8c4d91568e2e5a6677c7cb28d8cd545cde437fcd3038bbce82cf2ddd8291","observation_id":"51c37aa4-35a0-4664-8d97-843d8e83c8cc","resolution":{"observed_at":"2026-08-12T17:47:53.078136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:47:52.446912Z","title":"Diffusion- sdf: Text-to-shape via voxelized diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.446912Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:225b739b33de00a09f14ec92c59a5cb0f8c2c8bb30bf54a1f8673db864871f67","observation_id":"89426067-785b-435a-aaba-701686e676a5","resolution":{"observed_at":"2026-08-12T17:47:52.446912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04717","last_updated":"2024-02-07T10:09:00Z","snapshot_observed_at":"2026-08-13T04:24:26.174172Z","submitted_at":"2024-02-07T10:09:00Z","title":"InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04717","snapshot_observed_at":"2026-08-12T17:47:52.451685Z","title":"Instructscene: Instruction- driven 3d indoor scene synthesis with semantic graph prior","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.451685Z"},"links":{"cited_paper":"/paper/2402.04717","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:82fc94bb0547e9f10f43db02d1a76054a6d195d762aa33838dcdb08b1405e6a7","observation_id":"7786630f-afec-4d4f-92f9-ae531dea3c18","resolution":{"observed_at":"2026-08-12T17:47:52.451685Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12085","last_updated":"2024-07-18T16:04:19Z","snapshot_observed_at":"2026-08-13T05:22:02.342831Z","submitted_at":"2023-11-20T11:24:21Z","title":"Pyramid Diffusion for Fine 3D Large Scene Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12085","snapshot_observed_at":"2026-08-12T17:47:52.457007Z","title":"Pyramid diffusion for fine 3d large scene generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.457007Z"},"links":{"cited_paper":"/paper/2311.12085","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:9cec08ed4d72c414a605af8f4ef96858eb8a551337fa12d508bd18a7f30401e2","observation_id":"beaa02d4-5e21-400c-bd9f-0aed45dc8058","resolution":{"observed_at":"2026-08-12T17:47:52.457007Z","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":"2026-08-12T17:47:53.045537Z","title":"Repaint: Inpainting using denoising diffusion probabilistic models","venue":null,"work_id":"01beaeeb-e70c-45a4-97a9-294c7064814a","year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.462351Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:83d6873327dc5dba0367db4dff76431fa166f7f381a0a80af199fa93a5a101b8","observation_id":"8e040e4a-b4e5-4cfd-a7dc-deab0299548a","resolution":{"observed_at":"2026-08-12T17:47:53.050843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:47:52.467025Z","title":"Text2mesh: Text-driven neural stylization for meshes","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.467025Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:2ad4355088acdf3b84ff3620c5dbc30d78dcf663b6ce0c700e90fd08b5cba5d7","observation_id":"adb842ae-b9cf-422e-b8ef-fdf5a9ec7034","resolution":{"observed_at":"2026-08-12T17:47:52.467025Z","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":"2026-08-12T17:47:53.018020Z","title":"Autosdf: Shape priors for 3d comple- tion, reconstruction and generation","venue":null,"work_id":"7dcae7a0-1ad4-49af-9ce1-fab741f6f93a","year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.471689Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:e00829fd6f69ab02c27d63037e28bca0c13281dcf9254403a513189b8f6fb03e","observation_id":"91f11197-336e-4d63-80e4-902adae589c1","resolution":{"observed_at":"2026-08-12T17:47:53.023243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T17:47:52.999767Z","title":"Difffacto: Controllable part-based 3d point cloud generation with cross diffusion","venue":null,"work_id":"a8e9a766-b566-48ee-b250-3b7dec11f6d4","year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.477343Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:5f353e7674a968cc0659c350f55d61627425cec692769e764bddf0c9be8ff414","observation_id":"3a079e31-c417-49d7-a69f-b895be53a851","resolution":{"observed_at":"2026-08-12T17:47:53.005597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.10741","last_updated":"2022-03-08T18:18:49Z","snapshot_observed_at":"2026-08-07T12:21:17.790675Z","submitted_at":"2021-12-20T18:42:55Z","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.10741","snapshot_observed_at":"2026-08-12T17:47:52.482108Z","title":"Glide: Towards photorealistic image generation and editing with text-guided diffusion models.arXiv preprint arXiv:2112.10741, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.482108Z"},"links":{"cited_paper":"/paper/2112.10741","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:8f1128f2bc86605c2ee57365385b7f99396f060c4c627e8c2804e0b7f69e7f32","observation_id":"d31c1198-34bd-4794-a69f-56618de38695","resolution":{"observed_at":"2026-08-12T17:47:52.482108Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.06125","last_updated":"2022-04-13T01:10:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-13T01:10:33Z","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.06125","snapshot_observed_at":"2026-08-12T17:47:52.486947Z","title":"Hierarchical text-conditional image gener- 9 ation with clip latents","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.486947Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:e397b8a50b173b00751f5c195c39f244ed915d41d40d8e5be4197fdb21621376","observation_id":"394701a6-e51b-43a5-99e4-bfcdb60821fe","resolution":{"observed_at":"2026-08-12T17:47:52.486947Z","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":"2026-08-12T17:47:52.982990Z","title":"Xcube: Large-scale 3d generative modeling using sparse voxel hierarchies","venue":null,"work_id":"ffca6e7f-1eaf-40e8-9f28-7c3afe12eab9","year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.491753Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:e1106d0cc6900998bd5ec95073a15b48c10d5fce28c68a7dce7de796eb98590b","observation_id":"8d593bbc-65b3-46ae-9950-1ee2faa429ba","resolution":{"observed_at":"2026-08-12T17:47:52.988423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T17:47:52.965573Z","title":"Lmscnet: Lightweight multiscale 3d semantic completion","venue":null,"work_id":"858c6788-455a-44bc-98a8-96c94950fcb8","year":2020},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.496717Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:83b8b5ffa2dd03d5658982d3f97cbd3bdb828705945afe982d96bbeb1656343d","observation_id":"b7d01440-a9ec-45d2-97b1-5926de7370b4","resolution":{"observed_at":"2026-08-12T17:47:52.971302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:47:52.501892Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.501892Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:3b9c84dadf3c68b00541df97db46f87382b562177bbe0a40152660abc87b6b42","observation_id":"3a57a0c4-b058-420b-bfbc-14486d725902","resolution":{"observed_at":"2026-08-12T17:47:52.501892Z","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":"2026-08-12T17:47:52.506662Z","title":"Palette: Image-to-image diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.506662Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:36f242f6e857e0949b9e444f952397853a32d3ca1cc1a0a857c8e429b064f193","observation_id":"27a86f5c-7a76-48f3-9940-e1f2e4bb9ab8","resolution":{"observed_at":"2026-08-12T17:47:52.506662Z","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":"2026-08-12T17:47:52.511392Z","title":"Improved techniques for training gans","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.511392Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:8ecf9f9209642ad55e3f444726157a54b9be85f87a23feb36bf4e60c8e75231e","observation_id":"7e9491cb-4bf3-496e-aa23-d48e11e14803","resolution":{"observed_at":"2026-08-12T17:47:52.511392Z","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":"2026-08-12T17:47:52.516074Z","title":"3d neural field generation using triplane diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.516074Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:d0155d48e2c76f038a7c52e703705ebe93becec6537110a2f639c81577a2bea2","observation_id":"39a3f738-2191-4b8b-aac2-60dd7b0d4706","resolution":{"observed_at":"2026-08-12T17:47:52.516074Z","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":"2026-08-12T17:47:52.903066Z","title":"Diffuscene: Denoising diffu- sion models for generative indoor scene synthesis","venue":null,"work_id":"a36201fc-7756-424c-b545-79e96d7d33c3","year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.521007Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:d69dd1464acbb6cb4338ca728f0be9c6929d8fbd5aff49d35122eeeb5f52e9d7","observation_id":"ffa47de5-5980-4f00-9c17-bf8c84f0c45b","resolution":{"observed_at":"2026-08-12T17:47:52.908501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T17:47:52.886034Z","title":"Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving","venue":null,"work_id":"87a15eea-705d-4988-909f-56edc5f0ce9e","year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.525944Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:e9b8ca5ac81627fed00c4731d6d1015794ec74c9a9787ea95e17fb2de460f005","observation_id":"fbb3fd3f-0db8-4cb1-8cc3-8a1f1af14fa5","resolution":{"observed_at":"2026-08-12T17:47:52.891471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:47:52.530997Z","title":"Lion: Latent point dif- fusion models for 3d shape generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.530997Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:b40458bfdce959e2f5eb1ad87ae17c9fd1fb8cd02037889d21af17c59f2e9368","observation_id":"d633b044-15d3-4ded-b2a7-0aa5626647e1","resolution":{"observed_at":"2026-08-12T17:47:52.530997Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.20337","last_updated":"2024-05-30T17:59:42Z","snapshot_observed_at":"2026-08-12T23:53:52.505475Z","submitted_at":"2024-05-30T17:59:42Z","title":"OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.20337","snapshot_observed_at":"2026-08-12T17:47:52.536021Z","title":"Occsora: 4d occupancy generation models as world simulators for au- tonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.536021Z"},"links":{"cited_paper":"/paper/2405.20337","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:24e7ef455837d8d3eded9658fe148bad97e7d432916825ed2cb4d2adfd37160b","observation_id":"2f75f627-97a7-4d74-83d8-4628609fbbfd","resolution":{"observed_at":"2026-08-12T17:47:52.536021Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.12952","last_updated":"2022-05-25T17:58:26Z","snapshot_observed_at":"2026-08-13T15:36:25.966998Z","submitted_at":"2022-05-25T17:58:26Z","title":"Pretraining is All You Need for Image-to-Image Translation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.12952","snapshot_observed_at":"2026-08-12T17:47:52.541663Z","title":"Pretraining is all you need for image-to-image translation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.541663Z"},"links":{"cited_paper":"/paper/2205.12952","citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:c114c11c43f11fd0f1db9b4359fedbbd34c32440d84aeb861918e1d4f3acc218","observation_id":"f9fd17e3-df1b-4a2b-bae8-3bbb9e5d2ba2","resolution":{"observed_at":"2026-08-12T17:47:52.541663Z","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":"2026-08-12T17:47:52.859545Z","title":"Motionsc: Data set and network for real- time semantic mapping in dynamic environments","venue":null,"work_id":"5b444904-8ebb-4d56-910f-004b33f40915","year":2022},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.546829Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:643d3c353a74d1a669a2270970fbbeafaf11372b58f5b42f9c8c806d81883264","observation_id":"681eecea-b28c-48a0-a70e-164bc7e05b92","resolution":{"observed_at":"2026-08-12T17:47:52.864755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-12T17:47:52.842213Z","title":"Scpnet: Se- mantic scene completion on point cloud","venue":null,"work_id":"a52f07ca-80fb-41af-b2a4-f034e6a2916a","year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.551870Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:c09aad903147de96a2b6591d15351c490be4f7a981ab9b3bd1eccd9318242c76","observation_id":"45a7488c-9668-483d-bda2-4b64479745f6","resolution":{"observed_at":"2026-08-12T17:47:52.847707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:47:52.557220Z","title":"Disn: Deep implicit surface network for high-quality single-view 3d reconstruction","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.557220Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:a9a916d04b07e88095f1a4bfc3355648eb46b9ee24dbc63d1596cbff8b7690eb","observation_id":"4cd2871b-bf6e-47d4-80c8-34d5c7e99d0f","resolution":{"observed_at":"2026-08-12T17:47:52.557220Z","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":"2026-08-12T17:47:52.813666Z","title":"Commonscenes: Generating commonsense 3d indoor scenes with scene graphs","venue":null,"work_id":"244bf308-b24f-4fb8-917c-0dccc0dd9509","year":2024},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.562307Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:bc87cb3c572483ee3f15d26c932d3af9afe6e6352fa97c7fd555bbb253c0ef84","observation_id":"741f0e2a-6c75-49fa-b0dd-96f8ff207ea0","resolution":{"observed_at":"2026-08-12T17:47:52.819145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:47:52.567244Z","title":"Adding conditional control to text-to-image diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.567244Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:dd32b9c2455321cb67fe4511942df761c3006a87c90c29e7217c106803b2efcb","observation_id":"e41161f8-60bd-494a-bb4c-dc1f7e1f636a","resolution":{"observed_at":"2026-08-12T17:47:52.567244Z","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":"2026-08-12T17:47:52.572072Z","title":"Layoutdiffusion: Controllable diffu- sion model for layout-to-image generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.572072Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:7a379e1c093fbbe246356ed5a47f5720351273b96a117a41b5051eba0be32355","observation_id":"d38b2c64-ea21-429e-b35c-205b3445e24f","resolution":{"observed_at":"2026-08-12T17:47:52.572072Z","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":"2026-08-12T17:47:52.774238Z","title":"3d shape generation and completion through point-voxel diffusion","venue":null,"work_id":"085643d3-864e-4521-b511-28e01f66fe0d","year":2021},"citing_paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T17:47:52.576639Z"},"links":{"citing_paper":"/paper/2411.12290"},"observation_digest":"sha256:231e1ba530decd98910426844616851c7c00a7be780e83311725e6594aaaed65","observation_id":"dd7f6e42-acd4-415c-a3fb-76a153ecddcf","resolution":{"observed_at":"2026-08-12T17:47:52.781357Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.12290","last_updated":"2024-11-19T07:19:05Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T17:46:06.239859Z","submitted_at":"2024-11-19T07:19:05Z","title":"SSEditor: Controllable Mask-to-Scene Generation with Diffusion Model"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":26,"verified_exact":0,"verified_fuzzy":17},"total_outbound_references":43},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2411.12290."}