{"as_of":"2026-08-10T23:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cd4cdaa4ec3460e70f2fb21e0a5b5c735883c8dc1c02597d43b1c73f34d068c5","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:48:13.518351Z","state":"measured"},{"denominator":42,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":42,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2507.04685/citation-record","integrity":"/paper/2507.04685/integrity","json":"/paper/2507.04685/citation-record.json","paper":"/paper/2507.04685"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:48:14.209047Z","title":"Synthetic data from diffusion models improves imagenet classification","venue":null,"work_id":"930ebde6-6539-4a48-8652-9122d1120dd8","year":2023},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:12.450218Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:3b7f3fb58e03967f78689632704bb6d24edb2312b3cad22902c346786f64195e","observation_id":"4e5faa5f-d112-431d-b06e-9f7769755f80","resolution":{"observed_at":"2026-08-06T19:48:14.212989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:14.197219Z","title":"Language models are few-shot learners","venue":null,"work_id":"a00eef3e-c21f-4603-8b4d-993238724f85","year":1901},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:12.559495Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:b617e830833e7ba7ecda2dd78b560398b9f6b68a09ebc0c6b15a27440ad81ef9","observation_id":"57405cff-cabe-49e2-bfb8-5c0bf2e13f62","resolution":{"observed_at":"2026-08-06T19:48:14.201122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:14.182986Z","title":"Decor- gan: 3d shape detailization by conditional refinement","venue":null,"work_id":"f60786d8-3a87-4083-a271-7e4865f7b31f","year":2021},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:12.680663Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:b56a5da7cee12ace602e2b87f89662b24d6a6cf4b0bca7f8f6c66cf218bbf662","observation_id":"2ebea41e-4b44-4e6d-9e50-d6af2bcd8031","resolution":{"observed_at":"2026-08-06T19:48:14.186880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:14.168368Z","title":"3d u-net: learn- ing dense volumetric segmentation from sparse annota- tion","venue":null,"work_id":"1e930463-c031-4f05-b204-5676928052df","year":2016},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:12.867028Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:d3a4c5168a2bff11347eff16fe1d786a0de7983dc3ce12e8cf71060e594e610c","observation_id":"c12ab319-c404-4128-b742-8f26e6d34f08","resolution":{"observed_at":"2026-08-06T19:48:14.173695Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:14.155954Z","title":"Collaborative tooth motion diffusion model in digital orthodontics","venue":null,"work_id":"7f7aaa14-ab38-4be8-b853-ceb054382049","year":2024},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:12.989218Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:dc4688310986a37d9a8942b4f79e43365baaa112e6b9a1b07e6a48b5273b7819","observation_id":"2c24d545-5dd1-400a-9077-220651c47e41","resolution":{"observed_at":"2026-08-06T19:48:14.159936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.00064","last_updated":"2018-03-30T21:56:38Z","snapshot_observed_at":"2026-08-09T12:13:33.243753Z","submitted_at":"2018-03-30T21:56:38Z","title":"Learning Beyond Human Expertise with Generative Models for Dental Restorations","version":1},"cited_work":{"arxiv_id":"1804.00064","doi":null,"metadata_source":"pith","pith_arxiv_id":"1804.00064","snapshot_observed_at":"2026-08-06T19:48:13.595119Z","title":"Learning Beyond Human Expertise with Generative Models for Dental Restorations","venue":"cs.CV","work_id":"2d47b49e-06ba-47ce-a6db-7ebe94b2025e","year":2018},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.195044Z"},"links":{"cited_paper":"/paper/1804.00064","citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:ff8e63bf45cceb8b67239a0f49b708f4feb297e0080025a4c6960c66acd6151a","observation_id":"ac88a527-432e-4f31-b314-7c3bfab46dda","resolution":{"observed_at":"2026-08-06T19:48:13.599178Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:14.029812Z","title":"Zero-shot text-guided object gen- eration with dream fields","venue":null,"work_id":"ba655fc3-2c66-4c77-a8de-aba678af6071","year":2022},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.340820Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:b090ef004eb5da4ea4e333110ab2794a3f2959aa3f6c1b084ca7a79698f052b3","observation_id":"8a0f46c5-54b4-49a9-b020-eeff8cf181a0","resolution":{"observed_at":"2026-08-06T19:48:14.034144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02303","last_updated":"2022-10-05T14:41:38Z","snapshot_observed_at":"2026-07-06T13:59:57.800591Z","submitted_at":"2022-10-05T14:41:38Z","title":"Imagen Video: High Definition Video Generation with Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.02303","snapshot_observed_at":"2026-08-06T19:48:13.344966Z","title":"Kingma Diederik, Poole Ben, Norouzi Mohammad, J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.344966Z"},"links":{"cited_paper":"/paper/2210.02303","citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:23a1f3ebf28040a0589108a01c34889ca18708cdaeafc9cdd2386202154dc7f0","observation_id":"55dd0a38-33de-4e1c-a3ff-c917c8ca1333","resolution":{"observed_at":"2026-08-06T19:48:13.344966Z","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":"2026-08-06T19:48:14.012107Z","title":"Dc- face: Synthetic face generation with dual condition diffusion model","venue":null,"work_id":"fce8cfc7-f4a9-42fb-bc99-655a1314e06b","year":null},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.349932Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:bb52d51de1feb06577bb8e17ded502a57c563f55c5e42f773b93e303c937571b","observation_id":"460db4d7-1f97-4d5d-9d5c-e1d1c0c357a8","resolution":{"observed_at":"2026-08-06T19:48:14.016943Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.997107Z","title":"Automatic tooth arrangement with joint features of point and mesh rep- resentations via diffusion probabilistic models","venue":null,"work_id":"65bc07e6-4244-45fd-9c23-5b7eb397f434","year":2024},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.354658Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:ec4e0008128b9e8167e1f93c42901b468fe6106113c2768c01a54c0349f0efa9","observation_id":"ef595527-75bb-4ac7-aba3-e399c6056828","resolution":{"observed_at":"2026-08-06T19:48:14.003482Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.981132Z","title":"Malocclusion treatment planning via pointnet based spatial transformation network","venue":null,"work_id":"284aa46a-9eb3-4472-836b-c6f5f195a363","year":2020},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.359980Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:fe53bc34c42cfc5891e118dc5898cb9151eef5cb0447a2161f0f492c2b06d4b6","observation_id":"076acf09-1fb1-408c-b10e-6e57c487125e","resolution":{"observed_at":"2026-08-06T19:48:13.985856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.964523Z","title":"Magic3d: High-resolution text-to-3d content creation","venue":null,"work_id":"ef5cc7b0-edc9-48b4-ac9d-7367da3639fa","year":2023},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.363784Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:740b5bfa50129b76ef6e9b4a71ffa6472a5727c7a4c739f2d98e073669c5ba2d","observation_id":"6414ba33-027b-4a0c-b60a-f31b56bcc8b8","resolution":{"observed_at":"2026-08-06T19:48:13.970143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.950438Z","title":"iorthopredictor: model- guided deep prediction of teeth alignment","venue":null,"work_id":"db89003f-bc17-4125-b38c-7bf6e6835489","year":2020},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.367843Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:cd242c338651d9b9f3bc5e7f9ab01e6f4a29cf0b4d18f61de306c3577f56f7cc","observation_id":"0f82837f-a8fd-4bc2-879e-134f71b0a2c3","resolution":{"observed_at":"2026-08-06T19:48:13.954586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.934607Z","title":"One-2-3-45: Any single image to 3d mesh in 45 seconds without per-shape optimiza- tion","venue":null,"work_id":"9b0866ea-8eee-454c-8b58-25e9bdb7ca39","year":2024},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.377574Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:8b1d46c537fe1193c5286bcc241bf833b15d2fd3ba1127d24bb9a40c2ee117b4","observation_id":"f8fca89d-b7c5-4239-af2e-515cf15d524b","resolution":{"observed_at":"2026-08-06T19:48:13.940165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.919836Z","title":"Meshdiffu- sion: Score-based generative 3d mesh modeling","venue":null,"work_id":"0823709b-8d95-45e6-ac59-77050a3c10fa","year":null},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.383219Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:750c6b38a708df020cbe59925a1ff6b435dc21919808ef29687afbd53d0c795a","observation_id":"a36415c8-0b08-4e94-9d48-654c10989435","resolution":{"observed_at":"2026-08-06T19:48:13.924980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.905165Z","title":"Point- voxel cnn for efficient 3d deep learning","venue":null,"work_id":"edb4f7d3-cb06-4a3e-8a95-34bfaaf612ba","year":2019},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.392090Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:9964df1fc23c1a835692791532debcfd2e5196dc7780162048061a4149b15a33","observation_id":"d2796b49-4a98-4180-a7f5-585ada29e0c5","resolution":{"observed_at":"2026-08-06T19:48:13.910018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.890563Z","title":"Wonder3d: Sin- gle image to 3d using cross-domain diffusion","venue":null,"work_id":"9f9680a7-926d-41a8-bba6-0e1da49e58d8","year":2024},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.396038Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:7e14be15f1c0312c85062e8ad4893d2077f66be7073656a1ce7441c9c3536b81","observation_id":"721971a5-cbd0-4e29-aa94-60165e6a7960","resolution":{"observed_at":"2026-08-06T19:48:13.895392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.877474Z","title":"Diffusion probabilistic models for 3d point cloud generation","venue":null,"work_id":"736a68be-64f7-4e00-8f92-83827b9180a1","year":null},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.400428Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:7d4668cdee4fc5d7898c6d57ae0ca641165419e879ddfe1e6bfb61e3765e4917","observation_id":"c2cdcdad-94ed-462d-9524-fb280cc1b800","resolution":{"observed_at":"2026-08-06T19:48:13.881379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.865651Z","title":"Dit-3d: Exploring plain diffusion transformers for 3d shape generation.NeurIPS, 36: 67960–67971, 2023","venue":null,"work_id":"67e1f9c0-8451-4430-9dec-a99c7dafc88b","year":2023},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.405707Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:afc6a430d88835ec718419bdc2ad8be94413867d623dc56b0bdc7be49051edb6","observation_id":"290f2aca-01e3-40a1-92da-aba268c74c0a","resolution":{"observed_at":"2026-08-06T19:48:13.869692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.853546Z","title":"Fast marching far- thest point sampling","venue":null,"work_id":"e215c38c-5999-4bc4-88c4-abdac089d850","year":2003},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.414575Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:7d798d4178afbf2d039e82b073ce769677f3e148b234691977ac094530d0d2d8","observation_id":"630142f0-c62a-46bb-a850-2e51a1cf3ec8","resolution":{"observed_at":"2026-08-06T19:48:13.857500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.841465Z","title":"Polygen: An autoregressive generative model of 3d meshes","venue":null,"work_id":"6a733840-a676-47f7-83d7-02e6ccb1e817","year":2020},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.418870Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:9940572c3195fb5933d73b3fcae9668ef0956bcdcda4a896931c004ed255d013","observation_id":"55f84710-ad21-4abd-9bf3-88c2ace00d59","resolution":{"observed_at":"2026-08-06T19:48:13.845703Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.422650Z","title":"Improved denoising diffusion probabilistic models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.422650Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:2850dc387bf22fe63bcd3e3b82d76578957cfa83e31320714d7fc6eb8514f652","observation_id":"67d886e2-7d92-4eaa-bf94-42ca7510e3f9","resolution":{"observed_at":"2026-08-06T19:48:13.422650Z","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":"2026-08-06T19:48:13.821871Z","title":"A time for change of tooth numbering systems","venue":null,"work_id":"2d6b50e8-92bb-4a53-9ccb-145a97e82bac","year":1993},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.426540Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:e6e0b34406cd41d0eefebe018c8082c6c75fdb070b118a0acfecdcd26676b8df","observation_id":"fb895c34-1aca-43b0-9bed-48471059c7fe","resolution":{"observed_at":"2026-08-06T19:48:13.825876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.809145Z","title":"Dreamfusion: Text-to-3d using 2d diffusion","venue":null,"work_id":"a0f5a8b0-8c2e-4672-a4d3-77806bd957e0","year":null},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.429746Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:ab88cf4d19f5c425fbb57657413e2a32d83d0f8392a75500272e7618239ab1a5","observation_id":"991764ad-c773-4a4e-a497-aba342e5f12b","resolution":{"observed_at":"2026-08-06T19:48:13.813396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.788707Z","title":"Dreambooth3d: Subject-driven text-to-3d generation","venue":null,"work_id":"a70b5ced-f83d-44e5-a666-ce7d66db83cc","year":2023},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.433661Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:808eb8be55e62c5227c8b79aa00176755a91ef5712cf318a3a2bc5edfeba2db5","observation_id":"b099f02c-49d8-496b-af9b-ccf95e7e39f1","resolution":{"observed_at":"2026-08-06T19:48:13.794118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.438693Z","title":"Palette: Image-to-image diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.438693Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:a99c8689613414e9cc42d9c95fbff5032826844f3e3db24e2b6893c166141ff5","observation_id":"9c1fdb78-ea7d-497f-b679-c4e7d96bad93","resolution":{"observed_at":"2026-08-06T19:48:13.438693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.14162","last_updated":"2025-02-23T10:44:08Z","snapshot_observed_at":"2026-07-06T14:35:45.516513Z","submitted_at":"2022-12-29T03:12:47Z","title":"OrthoGAN:High-Precision Image Generation for Teeth Orthodontic Visualization","version":2},"cited_work":{"arxiv_id":"2212.14162","doi":null,"metadata_source":"pith","pith_arxiv_id":"2212.14162","snapshot_observed_at":"2026-08-06T19:48:13.565301Z","title":"OrthoGAN:High-Precision Image Generation for Teeth Orthodontic Visualization","venue":"cs.CV","work_id":"97b11a70-fd27-4aa3-b268-578385bc73da","year":2022},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.449615Z"},"links":{"cited_paper":"/paper/2212.14162","citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:67b6810b66518f3451eb179145fb37b40b5576a86b601fc668146d04bf84e9cd","observation_id":"10a94bb0-2cd6-4a62-b93e-e273e631f75c","resolution":{"observed_at":"2026-08-06T19:48:13.570000Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.763596Z","title":"Ai models collapse when trained on recursively generated data","venue":null,"work_id":"094af84d-5845-46b3-bda0-1601de41b853","year":2024},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.454213Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:f0b6d3c9611ded4f2ec9f9fce6cb1357aebcbf2fb05ca8a913147f6a3b22ee7d","observation_id":"ecd34e4e-2c62-4573-a200-8a0f6e248f1c","resolution":{"observed_at":"2026-08-06T19:48:13.768114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.748747Z","title":"Meshgpt: Generating triangle meshes with decoder-only transformers","venue":null,"work_id":"04cdff2a-f59f-4d0c-a275-83c4ddaea143","year":2024},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.464098Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:7a04090d72c3e73103fd676639710c9c0d7534ac44eee192ef8ac082fbe0d565","observation_id":"6a0c4498-7889-47d3-a9fc-2792376d4b45","resolution":{"observed_at":"2026-08-06T19:48:13.753231Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.735931Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics","venue":null,"work_id":"f3c112be-d045-40c5-bac6-15170faafac3","year":2015},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.471261Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:b59909bfdb0b925a1e2aa328dd04ff8c85acebd75af5fb9f76ded531854995ee","observation_id":"7c1396a0-8035-47fa-983a-6bec6bacbece","resolution":{"observed_at":"2026-08-06T19:48:13.740947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.725037Z","title":"Score-based generative modeling through stochastic differential equa- tions","venue":null,"work_id":"263a305d-ba7b-4b8a-a028-6bed12786002","year":2021},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.474955Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:f2895fbc886503947b1e3556b573286a1970ecd29d4fff9511e4efc880ac05f9","observation_id":"abdfff99-a2b1-4e5d-997b-2ed739a0fef8","resolution":{"observed_at":"2026-08-06T19:48:13.728378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.713758Z","title":"Vari- ational autoencoders for deforming 3d mesh models","venue":null,"work_id":"4be64eaf-7f69-478d-bce9-3808d723193c","year":2018},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.478737Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:d4cf2cd0c674d8e9df0ab429c830e1422dc0151e4e74ade1cb896b095fff70bb","observation_id":"e0e98403-11d0-4a30-97a2-e3a6900550b9","resolution":{"observed_at":"2026-08-06T19:48:13.717548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.702916Z","title":"Lion: Latent point dif- fusion models for 3d shape generation","venue":null,"work_id":"f04380e5-b263-4469-b02a-e1b9bbf46f28","year":2022},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.482523Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:b0cc0ece549ec7d4543887b161f5d06988bbd00e5c3fb449513f1cab457604fc","observation_id":"b71555d7-11b4-425b-a081-16fbd63d4dfb","resolution":{"observed_at":"2026-08-06T19:48:13.706103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.691852Z","title":"Neural discrete representation learning","venue":null,"work_id":"fd93c07b-89df-462b-b123-4cfb98860143","year":2017},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.486042Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:931fa388362b455556f27145b93e03ccd9cad543a8fb2e1ce31500f4865ca9f6","observation_id":"ef89c2e0-8ae7-4c87-9ff2-9e6c1e303ede","resolution":{"observed_at":"2026-08-06T19:48:13.695625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.676520Z","title":"Tooth alignment network based on landmark constraints and hierarchical graph structure","venue":null,"work_id":"a482232c-a612-4530-97ee-d5c5b344bf53","year":2022},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.489414Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:e785f9b5bc88df74b2afa321307b951f4f0f8022118bb7fdf26085c73108de3c","observation_id":"54548164-f524-4e09-bb20-76113585c623","resolution":{"observed_at":"2026-08-06T19:48:13.680896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5281/zenodo.11392406","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"A 3d dental model dataset with pre/post- orthodontic treatment for automatic tooth alignment [data set]","venue":"Zenodo (CERN European Organization for Nuclear Research)","work_id":"ac09a0f2-89fd-4001-947f-6fe854554134","year":null},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.496012Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:d63231bb7ca843fcae263a8b215b92a396f7b70eadbbe6c903fc9bb06cfbafc2","observation_id":"7046bf1e-712f-4f3e-8260-2db7ea552e8b","resolution":{"observed_at":"2026-08-06T19:48:13.551081Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.663256Z","title":"Tanet: To- wards fully automatic tooth arrangement","venue":null,"work_id":"bddbadd0-bb54-413c-a2bd-82e8ef4dc10d","year":2020},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.501158Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:d38b2665b1cacb19ac400d7077c66acfcb81bb2a10ebb32f3802a437da06724c","observation_id":"7d5a11aa-32e4-4809-aecf-61e246c0635d","resolution":{"observed_at":"2026-08-06T19:48:13.667849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.649639Z","title":"Learning pro- gressive point embeddings for 3d point cloud generation","venue":null,"work_id":"ea148cef-c451-446b-ae2c-82dda29b83e2","year":2021},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.504656Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:ddf8a508c05c79250617099a323cb70fc964d35d78558a7ef25c6d48c02c9fea","observation_id":"e2ebd1f2-7257-4079-b62e-355aaefe4a27","resolution":{"observed_at":"2026-08-06T19:48:13.654306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.638704Z","title":"Pointflow: 3d point cloud generation with continuous normalizing flows","venue":null,"work_id":"a89c1718-a6d6-43e3-af48-7a38b4323013","year":2019},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.508111Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:ffffe33f41a17bb7e8b5f3fe6c4ca7d7114d90800babac507cc5061af29952b1","observation_id":"5cf5c383-6054-4b70-8e82-c5418752dd06","resolution":{"observed_at":"2026-08-06T19:48:13.642555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.628399Z","title":"3dstyle-diffusion: Pursuing fine-grained text-driven 3d stylization with 2d diffusion models","venue":null,"work_id":"d182b389-753c-42ec-9cb1-83e7744de211","year":2023},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.511234Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:46409deb4d13b7ef118ca53f6b4cef74c0889daa187512177641b5e22e305e4d","observation_id":"417b2379-c081-4813-9c87-c56b27d6016e","resolution":{"observed_at":"2026-08-06T19:48:13.631826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.617330Z","title":"3d shape genera- tion and completion through point-voxel diffusion","venue":null,"work_id":"18f807e5-e2a9-4e76-b967-123c98478bef","year":2021},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.514791Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:a95a5b0ad4512bea75d2e788a9b6f6dbd6dcdd728eabd9069afc9f3469e18a87","observation_id":"2b99d85c-d75f-4aec-ab17-a786c88a6fc4","resolution":{"observed_at":"2026-08-06T19:48:13.621045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T19:48:13.606187Z","title":"On the continuity of rotation representations in neural networks","venue":null,"work_id":"586519b8-f134-4cc2-adf8-cae6a9c1f1de","year":2019},"citing_paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T19:48:13.518351Z"},"links":{"citing_paper":"/paper/2507.04685"},"observation_digest":"sha256:df40aee1bf0044b6ad636a2e467754e941baf48c2db604d91d89780828aaa897","observation_id":"2069b29b-399d-4c1f-b8b8-936322414ea5","resolution":{"observed_at":"2026-08-06T19:48:13.609417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.04685","last_updated":"2025-07-07T06:08:10Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T19:39:58.730012Z","submitted_at":"2025-07-07T06:08:10Z","title":"TeethGenerator: A two-stage framework for paired pre- and post-orthodontic 3D dental data generation"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":3,"verified_fuzzy":36},"total_outbound_references":42},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.04685."}