{"as_of":"2026-08-08T23:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:acc51ce54d448d1162e9506a7ea4c0709625176e2c45196c7fb3e9e1e9bda811","coverage":[{"denominator":103,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T11:42:08.572680Z","state":"measured"},{"denominator":101,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":101,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-13T20:49:57.757693Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-13T20:53:15.947771Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"cited_work":{"arxiv_id":"2509.02466","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.02466","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tera: Rethinking text-guided realistic 3d avatar generation","venue":null,"work_id":"fa0011b3-d437-4ce5-94a7-4d21fa050733","year":2025},"citing_paper":{"arxiv_id":"2604.02883","last_updated":"2026-04-03T08:46:54Z","snapshot_observed_at":"2026-07-06T22:52:10.923214Z","submitted_at":"2026-04-03T08:46:54Z","title":"Information-Regularized Constrained Inversion for Stable Avatar Editing from Sparse Supervision","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-05-13T20:49:57.757693Z"},"links":{"cited_paper":"/paper/2509.02466","citing_paper":"/paper/2604.02883"},"observation_digest":"sha256:58711b52ea040b5469fe9c7d03262bb263b8473210c2d618b12000704dda39a4","observation_id":"8ad5f169-dfb9-4ef3-908f-825f09837855","resolution":{"observed_at":"2026-05-13T20:53:15.949215Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2509.02466/citation-record","integrity":"/paper/2509.02466/integrity","json":"/paper/2509.02466/citation-record.json","paper":"/paper/2509.02466"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-05T11:42:08.286765Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.286765Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:538df89a537e70ebc95f8dea81b5f51c618bb3708579d3088b706218ca732f3e","observation_id":"86806d03-3573-4f00-8530-9888a53d0d7a","resolution":{"observed_at":"2026-08-05T11:42:08.286765Z","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":"2026-08-05T11:42:08.290231Z","title":"Learning representations and generative models for 3d point clouds","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.290231Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:28a79000ed0880285cfdcee9d3dc0fc582128b50d966f7222cb5aff7457bcac6","observation_id":"539b319c-3d0e-42a8-95df-b653defa4c1f","resolution":{"observed_at":"2026-08-05T11:42:08.290231Z","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":"2026-08-05T11:42:08.294672Z","title":"The digital emily project: Achieving a photorealistic digital actor","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.294672Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:0516b5531f21a320b59769c0892a316eef6d1605b1f2af7eae25ce81abc50270","observation_id":"5f6d57c2-41c4-44e8-86bb-7d58e09bb9e7","resolution":{"observed_at":"2026-08-05T11:42:08.294672Z","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":"2026-08-05T11:42:08.297914Z","title":"imghum: Implicit generative models of 3d human shape and articulated pose","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.297914Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:3daaf99e241fd42caac8429686545aa4fb050e843ea7c247476331d57820696f","observation_id":"4815bc61-a50d-49cf-8657-d6866837eb08","resolution":{"observed_at":"2026-08-05T11:42:08.297914Z","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":"2026-08-05T11:42:08.300846Z","title":"Panohead: Geometry-aware 3d full- head synthesis in 360deg","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.300846Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:f66c94714109f4c285479da7e9f3e8cb692712b5ff0aac85482886a3fdcba4bd","observation_id":"ef7256fc-ddc0-42ce-9d9d-9eec766cd750","resolution":{"observed_at":"2026-08-05T11:42:08.300846Z","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":"2026-08-05T11:42:08.303754Z","title":"Controlled diffusion models for optimal dividend pay-out","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.303754Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:83c6b7b61ff4c7213d59094b81fea1ab93139d9e150f2f30712d7080627738c0","observation_id":"12dbba38-a665-4143-8db9-a4664bdf7dd4","resolution":{"observed_at":"2026-08-05T11:42:08.303754Z","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":"2026-08-05T11:42:08.306599Z","title":"Blended latent diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.306599Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:9721e1073051c17bc63cf1df8d1a0ea3e733f06296c40bf95e62e6a81d65a787","observation_id":"30f855c6-e483-4a8e-9bc4-310b17f4193b","resolution":{"observed_at":"2026-08-05T11:42:08.306599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-08-05T11:42:08.309552Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.309552Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:4732370d50cb20db7c148dcf70e91d13ef7c5ba3ff7c1b0c2f54f7d495e38ded","observation_id":"071050ac-12a3-430c-beaa-1ccbad16002c","resolution":{"observed_at":"2026-08-05T11:42:08.309552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.01324","last_updated":"2023-03-14T00:22:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-11-02T17:43:04Z","title":"eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.01324","snapshot_observed_at":"2026-08-05T11:42:08.312655Z","title":"ediffi: Text-to-image diffusion models with an ensemble of expert denoisers.arXiv preprint arXiv:2211.01324, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.312655Z"},"links":{"cited_paper":"/paper/2211.01324","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:33233a59931f2fecf1cf1748380f2eb3625b6338cfe68d4bcc4a02aade26a4e8","observation_id":"09184a01-47fa-4191-a0b0-786f9e66bac6","resolution":{"observed_at":"2026-08-05T11:42:08.312655Z","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":"2026-08-05T11:42:08.315693Z","title":"Universal guidance for diffusion models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.315693Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:88fa5714cf9b95f41d3379e04769513e98ce1f15e97ee8881d6f381a685d0bf5","observation_id":"962815e8-c69a-4c3c-859e-39d30f9fabf5","resolution":{"observed_at":"2026-08-05T11:42:08.315693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.15127","last_updated":"2023-11-25T22:28:38Z","snapshot_observed_at":"2026-08-07T21:47:08.589400Z","submitted_at":"2023-11-25T22:28:38Z","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.15127","snapshot_observed_at":"2026-08-05T11:42:08.318616Z","title":"Stable video diffusion: Scaling latent video diffusion models to large datasets","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.318616Z"},"links":{"cited_paper":"/paper/2311.15127","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:1bc80ddd1c963ec6a73022f2710ae7e518859a4a9de4d66d8628db86fbd150c8","observation_id":"aea14582-ab38-41b4-9fbb-a31e4b72c615","resolution":{"observed_at":"2026-08-05T11:42:08.318616Z","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":"2026-08-05T11:42:08.321538Z","title":"Dreamavatar: Text-and-shape guided 3d hu- man avatar generation via diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.321538Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:2274d6f7687fc66a7f886d6289fc3510f070f96f3fbd879fec66b4c9c9f8055a","observation_id":"2feef37f-c414-4e2d-ae56-54c22876600f","resolution":{"observed_at":"2026-08-05T11:42:08.321538Z","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":"2026-08-05T11:42:08.324258Z","title":"Efficient geometry-aware 3d generative adversarial networks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.324258Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:e69f42ade8ebd59545b687c09f6f809f5af7c3d3bf243ee2e2abdbd28ff7bd60","observation_id":"20282b80-a1da-42cd-b0f5-1187bd52decf","resolution":{"observed_at":"2026-08-05T11:42:08.324258Z","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":"2026-08-05T11:42:08.327223Z","title":"Text2shape: Generating shapes from natural language by learning joint embeddings","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.327223Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:6c907dcde1e978f371223207cf4a3e6ae59839a51880d1c5695a950cbde68b9e","observation_id":"2f6a2186-2f4f-42ae-a5f9-4652d7e09104","resolution":{"observed_at":"2026-08-05T11:42:08.327223Z","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":"2026-08-05T11:42:08.330235Z","title":"Fan- tasia3d: Disentangling geometry and appearance for high- quality text-to-3d content creation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.330235Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:22814ed232971a8d1472320cca44ad71840cd4263c9e861b30fe29ba0f0ebced","observation_id":"450b1e3d-82b1-4b94-8475-3dfe298fd790","resolution":{"observed_at":"2026-08-05T11:42:08.330235Z","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":"2026-08-05T11:42:08.332816Z","title":"Text-to-3d using gaussian splatting","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.332816Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:7474ae1963525709f4734186e7f769feef495aa5dc2b0d5736e0f57c864aac99","observation_id":"27bfc8e1-d236-4819-a1d8-bcd1b2a23b55","resolution":{"observed_at":"2026-08-05T11:42:08.332816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.10384","last_updated":"2019-03-25T15:03:35Z","snapshot_observed_at":"2026-08-03T01:52:30.564299Z","submitted_at":"2019-03-25T15:03:35Z","title":"MeshGAN: Non-linear 3D Morphable Models of Faces","version":1},"cited_work":{"arxiv_id":"1903.10384","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.10384","snapshot_observed_at":"2026-08-05T11:42:08.738714Z","title":"MeshGAN: Non-linear 3D Morphable Models of Faces","venue":"cs.CV","work_id":"d68e22c9-8753-458c-9d6a-bd9e2c754936","year":2019},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.335658Z"},"links":{"cited_paper":"/paper/1903.10384","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:73a2bfb719e1161f80faf7b49c7f98790c25b248603aefa360aeff95090220f7","observation_id":"1014096f-9092-43db-aad0-bfbdec1de2c3","resolution":{"observed_at":"2026-08-05T11:42:08.741969Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.339158Z","title":"Progressive3d: Progres- sively local editing for text-to-3d content creation with com- plex semantic prompts","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.339158Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:76faf44185d8fe8458f41304c8d5c81beb2d1dc9662ab8648bfafea06a4aa87c","observation_id":"30ed2a6c-3b0b-4d85-a409-89ac380d21c5","resolution":{"observed_at":"2026-08-05T11:42:08.339158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10802","last_updated":"2024-10-14T17:58:07Z","snapshot_observed_at":"2026-07-06T19:33:16.949210Z","submitted_at":"2024-10-14T17:58:07Z","title":"Boosting Camera Motion Control for Video Diffusion Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10802","snapshot_observed_at":"2026-08-05T11:42:08.342317Z","title":"Boosting camera mo- tion control for video diffusion transformers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.342317Z"},"links":{"cited_paper":"/paper/2410.10802","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:358495fa92a45461701ceacc74b748a04881182e3b76fdc055736a77b88f0462","observation_id":"8ec23a3e-6463-4286-8c4e-65f8b3a372ae","resolution":{"observed_at":"2026-08-05T11:42:08.342317Z","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":"2026-08-05T11:42:08.346254Z","title":"The light stages and their applications to pho- toreal digital actors","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.346254Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:5d723ee8d36f9f6da3d48526dde7007675436da012efff504e77c2e7630015aa","observation_id":"9af0e109-29b6-4d4c-befd-4dc453ed7e70","resolution":{"observed_at":"2026-08-05T11:42:08.346254Z","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":"2026-08-05T11:42:08.350248Z","title":"Textdeformer: Geometry manipu- lation using text guidance","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.350248Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:dfefef3cdbc0ba624520c697476618cbaa4a5410e1dffa9c81b6461616dcf311","observation_id":"d1a0363e-3b8f-4028-92e2-0817854e3b0e","resolution":{"observed_at":"2026-08-05T11:42:08.350248Z","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":"2026-08-05T11:42:08.353502Z","title":"Visual fact checker: En- abling high-fidelity detailed caption generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.353502Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:07dc6fd6dc53e3aaedb33d8df70291fa7db34025fb9d6e402fbf8c6784af5d25","observation_id":"ad454c46-8c8e-432f-bca3-67fcc39557bb","resolution":{"observed_at":"2026-08-05T11:42:08.353502Z","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":"2026-08-05T11:42:08.356602Z","title":"Densepose: Dense human pose estimation in the wild","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.356602Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:5ab8ab5bb5608828bfe970de607e02f4254df9ed1a82c1c12d6cb09aa754149d","observation_id":"086d3e1c-b8f0-4f56-be4e-3b8d173d2485","resolution":{"observed_at":"2026-08-05T11:42:08.356602Z","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":"2026-08-05T11:42:08.359603Z","title":"The re- lightables: V olumetric performance capture of humans with realistic relighting","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.359603Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:e5b03be2124d12ca9f0c7caa270a2517bd0ca058361733ecd89530fe758c264d","observation_id":"6651db06-b5d5-44df-bec6-fe794b8c5cb8","resolution":{"observed_at":"2026-08-05T11:42:08.359603Z","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":"2026-08-05T11:42:08.363026Z","title":"I2v-adapter: A general image-to-video adapter for diffusion models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.363026Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:6ad31b4c3fdf67d63bed0467c55d6567168d50bbe0e560cb48d58df4d951cfe1","observation_id":"8f1cdadf-e731-4cec-909f-94266dfe56e7","resolution":{"observed_at":"2026-08-05T11:42:08.363026Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02101","last_updated":"2025-03-13T18:35:06Z","snapshot_observed_at":"2026-07-06T17:54:39.685251Z","submitted_at":"2024-04-02T16:52:41Z","title":"CameraCtrl: Enabling Camera Control for Text-to-Video Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02101","snapshot_observed_at":"2026-08-05T11:42:08.365905Z","title":"Cameractrl: Enabling camera control for text-to-video generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.365905Z"},"links":{"cited_paper":"/paper/2404.02101","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:d87d63ab1588fb00ea42d1e97b5568b877560af3197cab8146ec62f80b36d2c2","observation_id":"c545b13c-4789-44ef-a579-2659cb38acfa","resolution":{"observed_at":"2026-08-05T11:42:08.365905Z","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":"2026-08-05T11:42:08.368947Z","title":"Head360: Learning a parametric 3d full-head for free-view synthesis in 360◦","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.368947Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:4cf7f7a3e86379cc62dc57af81b0e06b1f20db204570e3393e7c3faba66ced0f","observation_id":"5b540359-578a-4e21-b051-4f96dd671b43","resolution":{"observed_at":"2026-08-05T11:42:08.368947Z","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":"2026-08-05T11:42:08.371764Z","title":"Clipscore: A reference-free evaluation met- ric for image captioning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.371764Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:fdcf996b44e2a745157cd640013e0e53ac3c050feabfcdde8ebb6f5d82c13e94","observation_id":"86c2441d-aec8-4441-9f0c-b3ebe08dca34","resolution":{"observed_at":"2026-08-05T11:42:08.371764Z","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":"2026-08-05T11:42:08.374597Z","title":"Classifier-free diffusion guidance","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.374597Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:1bfe36af9c1bb0c1a8b852af51856cfe48c8409095926f1a2e2a59c1be508917","observation_id":"94c1ea96-e2af-4fc8-a81b-f6156892f395","resolution":{"observed_at":"2026-08-05T11:42:08.374597Z","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":"2026-08-05T11:42:08.377656Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.377656Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:19bbe7beec44f98035d867db824ff0bcc48f4ed1b206eaeffb4127fafb4bfdba","observation_id":"54a607c5-97a2-4f9a-b2d8-725cdc26bb63","resolution":{"observed_at":"2026-08-05T11:42:08.377656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.04888","last_updated":"2022-10-10T17:59:31Z","snapshot_observed_at":"2026-07-31T08:36:15.719965Z","submitted_at":"2022-10-10T17:59:31Z","title":"EVA3D: Compositional 3D Human Generation from 2D Image Collections","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.04888","snapshot_observed_at":"2026-08-05T11:42:08.380437Z","title":"Eva3d: Compositional 3d human generation from 2d image collections","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.380437Z"},"links":{"cited_paper":"/paper/2210.04888","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:97a983d5aed5a8d2efbce4fa635933fd76af3698d723a8957e682f2b46d31dab","observation_id":"bb983268-a102-4f15-82a1-6a141c80ac12","resolution":{"observed_at":"2026-08-05T11:42:08.380437Z","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":"2026-08-05T11:42:09.316466Z","title":"Avatarclip: Zero-shot text- driven generation and animation of 3d avatars","venue":null,"work_id":"9082170b-7304-421c-9928-0a4f03312c20","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.383812Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:b87aaaf43788398c2aaa8b547f24a8babe3e95262cc445ccac6c87ecfaa0ef4f","observation_id":"04d2c82c-48a8-4721-bedb-bd60d2bbe01d","resolution":{"observed_at":"2026-08-05T11:42:09.319329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10126","last_updated":"2025-02-25T00:32:29Z","snapshot_observed_at":"2026-08-07T18:45:05.745904Z","submitted_at":"2024-06-14T15:33:00Z","title":"Training-free Camera Control for Video Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10126","snapshot_observed_at":"2026-08-05T11:42:08.386994Z","title":"Training-free camera control for video generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.386994Z"},"links":{"cited_paper":"/paper/2406.10126","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:3c1fc0d51f7a7d468d2cc09cb0eb4d56e92aade18b2876dc3bc5432b08d44779","observation_id":"abc4e1e5-f6bb-40b1-a651-f3f69c18802a","resolution":{"observed_at":"2026-08-05T11:42:08.386994Z","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":"2026-08-05T11:42:09.307442Z","title":"Structldm: Struc- tured latent diffusion for 3d human generation","venue":null,"work_id":"1a4bb86c-4fa8-4d50-89be-a344db25b3c7","year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.389645Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:847e707187af812dc76673eb3e10c4fa414936fb5623245d3944145376fd1926","observation_id":"a3fb492f-6051-495c-8dec-15ecae16f10a","resolution":{"observed_at":"2026-08-05T11:42:09.310529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.291028Z","title":"Humannorm: Learning normal diffusion model for high-quality and realistic 3d hu- man generation","venue":null,"work_id":"157737d7-5711-4a46-858d-c27648e12bf2","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.392856Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:30545d4b5652c64f4a0617b04a800dc01ca70b3d7e7221367995679257fb21a7","observation_id":"a29c0153-0cd4-48ba-b8f0-225ca67550dc","resolution":{"observed_at":"2026-08-05T11:42:09.297614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.271525Z","title":"Dreamwaltz: Make a scene with complex 3d animatable avatars.Advances in Neural Information Processing Systems , 36:4566–4584,","venue":null,"work_id":"d6063c09-f61d-474a-a3c3-e3fcb9bbcf49","year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.395350Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:3b5854482783927809f87194730bd6bee481e9d68965152370aaded54b94b345","observation_id":"15b38dda-e81d-4540-82d9-8551f1eba3ad","resolution":{"observed_at":"2026-08-05T11:42:09.279403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.261258Z","title":"Zero-shot text-guided object genera- tion with dream fields","venue":null,"work_id":"b1591da1-9ce3-4ec5-8240-fad48f9d6c17","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.398410Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:dc176ba77080483adb07ec64f7e48f3cfb13e93f854c6ca94ef743f4bc479212","observation_id":"194296c9-ff1e-48b7-a26c-18401ab2723c","resolution":{"observed_at":"2026-08-05T11:42:09.264233Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.252254Z","title":"Avatar- craft: Transforming text into neural human avatars with pa- rameterized shape and pose control","venue":null,"work_id":"52cae3fa-aa18-4f26-b938-f4fdb58f0f55","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.401050Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:06596af125ee4e38b3a8333d1cd5142ca96a0edebea0a27d0e8c8ef6846c65b3","observation_id":"d9fbaf67-1dc6-4f90-b121-f7b34ab285e0","resolution":{"observed_at":"2026-08-05T11:42:09.255296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.242744Z","title":"Flovd: Optical flow meets video diffusion model for enhanced camera-controlled video synthesis","venue":null,"work_id":"ec5fa82d-1c6b-4739-aac3-ef8f0519719c","year":2040},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.403641Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:9927ffb8608a1138a87441a73db199e7f15e7f4838b064f03d7dedb1aa5688ea","observation_id":"bba0194f-131e-4aff-9d04-f00614b2ee0c","resolution":{"observed_at":"2026-08-05T11:42:09.246045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.233484Z","title":"3d gaussian splatting for real-time radiance field rendering","venue":null,"work_id":"277fd401-d61d-4207-9265-40d358fef604","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.406392Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:0f4092bff329c2ce34fa68935549aea66e9c2293e2f852580352d924c2d4051b","observation_id":"11b072d9-203c-479c-97a5-9b207b8667cd","resolution":{"observed_at":"2026-08-05T11:42:09.236528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.223992Z","title":"Gghead: Fast and generalizable 3d gaussian heads","venue":null,"work_id":"873c520d-167c-4e79-8400-166e98eef98b","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.409220Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:49d6b3beacd11e96044372fe8270da8713d52ae14365b45bb8e5f7ff672fc124","observation_id":"b60b62cd-5937-4c46-9399-5e4f34e35b31","resolution":{"observed_at":"2026-08-05T11:42:09.226937Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.215003Z","title":"Dreamhuman: Animatable 3d avatars from text","venue":null,"work_id":"3f15eb2f-8d45-4cf0-9edb-979fc93e97ff","year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.411842Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:1dc6cb3f2b99a3458f2f3e45f2c5c81e62dc6eff9fecfde171a67ce2f0567c0c","observation_id":"76e23b93-632e-4361-9f10-c79cfcf182b3","resolution":{"observed_at":"2026-08-05T11:42:09.217962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.205710Z","title":"Ln3diff: Scalable latent neural fields diffusion for speedy 3d generation","venue":null,"work_id":"85350f46-63fb-4463-aa59-20eab6955747","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.414638Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:bc178c50449d92b85f7229bf1419f4536d8407b191de3a9d48888d3572a49d4b","observation_id":"d57b6790-bbe7-4dd0-a535-0ff7279ca8cf","resolution":{"observed_at":"2026-08-05T11:42:09.209020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.196505Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation","venue":null,"work_id":"8e8685e0-6c1f-4df6-b3ba-1850976d4737","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.417586Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:ebd6f30bf16c579208613722e8aeeeda8fa256f097367fbc927d3c2621e68e80","observation_id":"b0f25018-63af-4b4d-9253-e266f524745f","resolution":{"observed_at":"2026-08-05T11:42:09.199645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.187546Z","title":"Tada! text to animatable digital avatars","venue":null,"work_id":"5c427073-4325-4d0c-815b-6aaee0a19baf","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.420301Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:83809e9b0824827e34b1912c44310909d96c74911389bfbaa892de2f8bf52311","observation_id":"321fb4be-0194-4671-82c2-b74bbc5cae78","resolution":{"observed_at":"2026-08-05T11:42:09.190579Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.422897Z","title":"Flow matching for generative mod- eling","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.422897Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:93f3235aaadd86482aa211d12a66673e8e87af92705a5ae7ae11034cb02cad28","observation_id":"d1469207-3342-4b12-88ac-ee8c1ef886a0","resolution":{"observed_at":"2026-08-05T11:42:08.422897Z","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":"2026-08-05T11:42:08.425875Z","title":"Humangaus- sian: Text-driven 3d human generation with gaussian splat- ting","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.425875Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:e14ec78f0a296c5b6d4fd3733cc6239888aabf7069395dbe535e09c2d2b3654f","observation_id":"da367ba9-990c-48d6-8262-b9034d85b257","resolution":{"observed_at":"2026-08-05T11:42:08.425875Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17177","last_updated":"2024-04-17T18:41:39Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-27T03:30:58Z","title":"Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17177","snapshot_observed_at":"2026-08-05T11:42:08.428741Z","title":"Sora: A review on background, technology, limitations, and opportunities of large vision models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.428741Z"},"links":{"cited_paper":"/paper/2402.17177","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:af5f227ff872ce0c457b21203918595fa71f027d2d32fc0535f7293ff82490ea","observation_id":"e31a1435-749d-43ca-ac9f-5a00632cc988","resolution":{"observed_at":"2026-08-05T11:42:08.428741Z","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":"2026-08-05T11:42:09.166091Z","title":"To- wards implicit text-guided 3d shape generation","venue":null,"work_id":"eb98f1da-a313-4e89-914e-15470ef873b5","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.431492Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:6aa6869c6311374400fa9f2c77f5f2a88e70829ea2fbfc0df188328c9bf47939","observation_id":"8368bdca-0f62-4605-88c5-33d70d7b8a32","resolution":{"observed_at":"2026-08-05T11:42:09.169097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.157158Z","title":null,"venue":null,"work_id":"e0430080-db84-4d01-bdfd-86e4cbdc9819","year":2015},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.434503Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:0dcac15c690808b1d7b7cac22afd783053e413d4e6646791d9c8eee2bb3a72a2","observation_id":"53e09c0f-7fee-4abe-9411-a900f3c6e928","resolution":{"observed_at":"2026-08-05T11:42:09.159906Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03048","last_updated":"2025-05-01T09:40:21Z","snapshot_observed_at":"2026-08-02T13:01:06.918463Z","submitted_at":"2024-01-05T19:55:15Z","title":"Latte: Latent Diffusion Transformer for Video Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03048","snapshot_observed_at":"2026-08-05T11:42:08.437291Z","title":"Latte: Latent diffusion transformer for video generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.437291Z"},"links":{"cited_paper":"/paper/2401.03048","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:a9a6e888f155b246e9e75b32322a2a5a31acdd1216fdd715ec3e891282855907","observation_id":"99720687-79e0-44f8-b744-40613d9a6f40","resolution":{"observed_at":"2026-08-05T11:42:08.437291Z","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":"2026-08-05T11:42:09.148233Z","title":"X-oscar: a progressive framework for high- quality text-guided 3d animatable avatar generation","venue":null,"work_id":"bf8b713e-b47f-495a-a28e-80d84ce6b1b2","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.440238Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:9e4afe552f7bac8da7a2562ec1a8d0ec23d3b69fe90514ab9255a70c630b9710","observation_id":"a316db78-d8ac-45fc-86f7-84bf3996a01f","resolution":{"observed_at":"2026-08-05T11:42:09.151195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.139183Z","title":"Latent-nerf for shape-guided generation of 3d shapes and textures","venue":null,"work_id":"e4c1601f-4f51-45f2-818c-f53042b3084c","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.443070Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:05049193c33d2bd745de38dd777f2c0dc204dec285433393a5f71dd2c69eead2","observation_id":"1aeb5298-ae86-4d61-b64f-be61859865b1","resolution":{"observed_at":"2026-08-05T11:42:09.142578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.130621Z","title":"Text2mesh: Text-driven neural stylization for meshes","venue":null,"work_id":"3b397660-160c-4c85-9031-cfb6473e8adf","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.445901Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:57706ec96b41763ee8faa9f639004354900094bf80dc75887a33714364dfa512","observation_id":"6075c592-71f0-42ab-b045-41429e4dc190","resolution":{"observed_at":"2026-08-05T11:42:09.133502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.448540Z","title":"Clip-mesh: Generating textured meshes from text using pretrained image-text models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.448540Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:bef1aa011483521210870e2dfae56b1cd33b54219eb47aa50c1716e4fe2e8abb","observation_id":"ad9b5afd-7835-47eb-a57f-24a2539c9100","resolution":{"observed_at":"2026-08-05T11:42:08.448540Z","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":"2026-08-05T11:42:09.116389Z","title":"Expressive body capture: 3d hands, face, and body from a single image","venue":null,"work_id":"a52c991e-0f21-4478-9508-f7adae9cd438","year":2019},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.451178Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:3a79fe865051c4b5b8370e3c38f7943d9044a2d34650c2b61caa0f1649e72a87","observation_id":"e53ff045-5533-44c4-a689-635ca90a2707","resolution":{"observed_at":"2026-08-05T11:42:09.119276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.108063Z","title":"Barron, and Ben Milden- hall","venue":null,"work_id":"49c9596d-a5fd-4127-ab7e-9ebddbcabf9e","year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.453995Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:3a3bac5de45d9dc5b8dddc08b324159fd6fe14670a29a0aecdc06477cc6762de","observation_id":"9779af50-3e44-4ca5-994a-57054299fce4","resolution":{"observed_at":"2026-08-05T11:42:09.110720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.099605Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"e0a980ed-5d91-4d5a-9a25-bc10128b578e","year":2021},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.456787Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:0a849fc51bfddc3db08ae89a577d2ab04e9be4d8d16400a2b0a57171414fefd5","observation_id":"637ad7ef-22b0-46c9-a232-98433ec1ba23","resolution":{"observed_at":"2026-08-05T11:42:09.102580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-05T11:42:08.459287Z","title":"Hierarchical text-conditional image gen- eration with clip latents","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.459287Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:52a74290a4ecedeacb21dc7562a7d11760168409997cfc1b47fdd984bfa4aeb4","observation_id":"70f9ebc8-20a6-4bd7-b207-8f4c70fcd034","resolution":{"observed_at":"2026-08-05T11:42:08.459287Z","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":"2026-08-05T11:42:09.090931Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"d1cd9dda-5c57-4578-b018-1ac943c4331b","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.462208Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:14f72953041a863bcdb5f687b9ae6578f2e3a5da69c3e589713f723b2bd1178c","observation_id":"cc33d7d6-cf72-4b6c-b692-debf30a853eb","resolution":{"observed_at":"2026-08-05T11:42:09.093755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.464903Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.464903Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:4620b9b98b5e265c3f56173348a2322ee7652d0a45d6577868295312d1631415","observation_id":"04e7051c-56a0-4b8e-8323-9eded4320ad2","resolution":{"observed_at":"2026-08-05T11:42:08.464903Z","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":"2026-08-05T11:42:09.076601Z","title":"High-resolution image syn- thesis with latent diffusion models","venue":null,"work_id":"2bb749a4-40f6-4b13-9fb7-f0216b1098b3","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.467520Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:db62a078f6c72a1d5b1d59f650d5d81f35d27b85993d5d619b28f7e17301fb65","observation_id":"98aefde9-00a3-4f28-9d14-ab8c479d0856","resolution":{"observed_at":"2026-08-05T11:42:09.079686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.470326Z","title":"Photorealistic text-to-image diffusion models with deep language understanding","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.470326Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:8ddcc0d15f7e15f174ef4ea11f571e3e42df45cb5f00e4a6bf286a87f5964478","observation_id":"f8a2dff3-b057-436a-be4a-7ed8adc76b86","resolution":{"observed_at":"2026-08-05T11:42:08.470326Z","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":"2026-08-05T11:42:09.061984Z","title":"Pifu: Pixel-aligned implicit function for high-resolution clothed human digitiza- tion","venue":null,"work_id":"01382295-7574-41ee-a317-45dee9c919ea","year":2019},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.473012Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:784f5e13a673fb6297b9326e3c5b843ad471d4f40c3be37d0d9a0d670c4920d7","observation_id":"b0a444dc-b860-4e9e-aa4d-1c6471586fa0","resolution":{"observed_at":"2026-08-05T11:42:09.065139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.053002Z","title":"3d point cloud generative adversarial network based on tree structured graph convolutions","venue":null,"work_id":"dfd819a5-8e0b-49a2-a214-8a0246e047e1","year":2019},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.475798Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:1663f30f29447feb9a799144d50318378a68a828837825f4b231a288eafec663","observation_id":"84e0d533-c5bb-49eb-9c2b-8be40aa557ec","resolution":{"observed_at":"2026-08-05T11:42:09.055923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.043901Z","title":"Dreamgaussian: Generative gaussian splatting for ef- ficient 3d content creation","venue":null,"work_id":"233b2d40-45c8-495f-b85d-96c3864f4c63","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.478520Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:422452600facd1af9f97c2fefeb3be1fc5d2e8b8952d27ca74c76794f75c25e8","observation_id":"a1c0ddf1-c5c9-41cb-97f1-44e84dc2cef6","resolution":{"observed_at":"2026-08-05T11:42:09.047010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.034899Z","title":"Shapescaffolder: Structure-aware 3d shape generation from text","venue":null,"work_id":"7499b6ce-ff4f-4a1e-bc76-f7cc6b26f635","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.481222Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:53ad794243b33fe6fad17f658c4b342eae1f56daf527e8cb4d73445221087a43","observation_id":"829c3730-7388-44a7-8f80-ad8a7e110f66","resolution":{"observed_at":"2026-08-05T11:42:09.038019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.02151","last_updated":"2024-03-04T16:00:56Z","snapshot_observed_at":"2026-07-06T17:39:16.540553Z","submitted_at":"2024-03-04T16:00:56Z","title":"TripoSR: Fast 3D Object Reconstruction from a Single Image","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.02151","snapshot_observed_at":"2026-08-05T11:42:08.484003Z","title":"Triposr: Fast 3d object reconstruction from a single image","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.484003Z"},"links":{"cited_paper":"/paper/2403.02151","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:7c1012a7d4a7c25c978deda5549f27570ab9f6d022975d6987eeb18a4eedaf86","observation_id":"68934472-68ea-40dd-90f4-232c7d09e6a4","resolution":{"observed_at":"2026-08-05T11:42:08.484003Z","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":"2026-08-05T11:42:09.025152Z","title":"Clip-nerf: Text-and-image driven manip- ulation of neural radiance fields","venue":null,"work_id":"97f10e23-046d-448c-87c4-c9e460c264b8","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.486889Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:7ec6b244a9b49f652a2d8c208b7992c6edd089398910fd49fe76b918ce3a14e2","observation_id":"5e968468-921d-4c02-82b0-590ee938e538","resolution":{"observed_at":"2026-08-05T11:42:09.028216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.489775Z","title":"Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.489775Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:07313a0df4cb25719e48f568845ecbfdaeafccc2970c87439cca2a9fb6cd556f","observation_id":"dc6c882a-d674-4305-995f-eedc0d8b3f57","resolution":{"observed_at":"2026-08-05T11:42:08.489775Z","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":"2026-08-05T11:42:09.010404Z","title":"Disentangled clothed avatar generation from text descriptions","venue":null,"work_id":"e4332e96-3cc3-409d-a0ff-42557dd8f45a","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.492460Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:f7e48198f6d43e29c001acab3598d1ba10f3d16c081771a5b2b3069638807a9c","observation_id":"82e8789c-489a-47df-b77e-0505cfa65b48","resolution":{"observed_at":"2026-08-05T11:42:09.013595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:09.001660Z","title":"Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion","venue":null,"work_id":"d58938a8-a880-49cd-9fe9-d73fc7114ab1","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.495110Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:c4966d51b79b478ffffd35b450f8a1a90295938fe5b149f9a8d2518d806c6427","observation_id":"6e33ecf5-b61c-46b9-9cac-8ea7e7bd55ee","resolution":{"observed_at":"2026-08-05T11:42:09.004667Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.992805Z","title":"Taps3d: Text-guided 3d textured shape generation from pseudo supervision","venue":null,"work_id":"2e7b738d-8e62-4095-ab12-3f685d0d28a9","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.497869Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:2f08ba7f0cfb3871e4e65c5b1a16c60e99259ceec3e42ff99ee9bc80589096de","observation_id":"cdb6c960-db90-499d-a7e9-2cbb42a22c88","resolution":{"observed_at":"2026-08-05T11:42:08.995984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.983961Z","title":"Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling","venue":null,"work_id":"3eb2f32c-b992-47f7-bbef-2cb4de0c5339","year":2016},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.500415Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:9611d08965047f2211a35a770fcea0479d791266898c06342557653ef8bf4b74","observation_id":"a63dd0d5-5c5d-4212-8c52-7f7e41621802","resolution":{"observed_at":"2026-08-05T11:42:08.986960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.975372Z","title":"Direct3d: Scal- able image-to-3d generation via 3d latent diffusion trans- former","venue":null,"work_id":"d4fd043d-a75a-4dbb-9c8c-3f82b5a44df2","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.503148Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:7265efcedb9a897f080aba51b0d97f9b27638d22ed5988fb9a814839f3b62202","observation_id":"98cc984f-460d-42c5-a0c4-505ef1d913cd","resolution":{"observed_at":"2026-08-05T11:42:08.978334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.966269Z","title":"Structured 3d latents for scalable and versatile 3d gen- eration","venue":null,"work_id":"d00ac88f-e11d-41eb-83e7-7503c46c0c2f","year":2025},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.505744Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:389131ad9adf115f8654449e87387d989d25a0a37d253a43bd47f5d3c2175eb4","observation_id":"488ed3cd-6c80-4473-9e9b-695ba33051af","resolution":{"observed_at":"2026-08-05T11:42:08.969493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.956728Z","title":"Econ: Explicit clothed humans optimized via normal integration","venue":null,"work_id":"c73ec2ec-526b-4014-a61d-b66f5c7367b0","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.508771Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:5b9267dcf994c6230d4719e70d353dbe6da7c5aacf8592e0f2c8e7bad6d4922d","observation_id":"d39db48c-2f3f-4b50-97b0-d3f7389f6f18","resolution":{"observed_at":"2026-08-05T11:42:08.959710Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-05T11:42:08.511370Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.511370Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:fa858ad087ace88741f578577d614080dd9b64dbc9a322e9e15e5eec6ee32328","observation_id":"f79b5d2c-5289-4b32-98f4-1bfcba3c583c","resolution":{"observed_at":"2026-08-05T11:42:08.511370Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08529","last_updated":"2024-05-13T14:12:23Z","snapshot_observed_at":"2026-08-08T09:48:16.449024Z","submitted_at":"2023-10-12T17:22:24Z","title":"GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08529","snapshot_observed_at":"2026-08-05T11:42:08.514241Z","title":"Gaussian- dreamer: Fast generation from text to 3d gaussian splatting with point cloud priors","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.514241Z"},"links":{"cited_paper":"/paper/2310.08529","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:f921dc5d774e0a441141ec762b8cfb728627d833fa452bd1462b17f80def518e","observation_id":"9936fe16-fcfd-4953-bc55-a3841274925e","resolution":{"observed_at":"2026-08-05T11:42:08.514241Z","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":"2026-08-05T11:42:08.947166Z","title":"Doublefu- sion: Real-time capture of human performances with inner body shapes from a single depth sensor","venue":null,"work_id":"9f53326e-15ee-4a16-9cf4-fe6b5ee9f40b","year":2018},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.517169Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:72fc5a7dc292e635f8958f309c542071d11eb7e247c4d1224694878f9bf70310","observation_id":"daa59887-c32b-471a-a24c-5d4de1242c73","resolution":{"observed_at":"2026-08-05T11:42:08.950426Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.937926Z","title":"Function4d: Real-time human vol- umetric capture from very sparse consumer rgbd sensors","venue":null,"work_id":"ee412140-c120-49b9-93f2-24a737e63b0f","year":2021},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.520026Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:9e9cbbe77c3fc48b64bc6440b85d0efaca1958e2481dfef82597df072fb08dff","observation_id":"c0782af3-831f-41d6-b7f1-6c78040335dd","resolution":{"observed_at":"2026-08-05T11:42:08.941218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.09864","last_updated":"2023-06-16T14:18:51Z","snapshot_observed_at":"2026-07-06T15:43:27.458645Z","submitted_at":"2023-06-16T14:18:51Z","title":"AvatarBooth: High-Quality and Customizable 3D Human Avatar Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09864","snapshot_observed_at":"2026-08-05T11:42:08.522875Z","title":"Avatarbooth: High-quality and customizable 3d human avatar generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.522875Z"},"links":{"cited_paper":"/paper/2306.09864","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:076959326b8a04c24474cf1a42fdc9ce3e0f70551ea6c3a45b876a6831017321","observation_id":"39863d65-bb72-4548-8dae-fee7bb71b2fb","resolution":{"observed_at":"2026-08-05T11:42:08.522875Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.07125","last_updated":"2023-09-13T17:59:56Z","snapshot_observed_at":"2026-07-06T16:18:06.415304Z","submitted_at":"2023-09-13T17:59:56Z","title":"Text-Guided Generation and Editing of Compositional 3D Avatars","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.07125","snapshot_observed_at":"2026-08-05T11:42:08.525692Z","title":"Text-guided generation and editing of compositional 3d avatars","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.525692Z"},"links":{"cited_paper":"/paper/2309.07125","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:56cb13ecabcc6e8f6957ad6da8c8a0441e89dcb2fbc6d3efb7bf06f62ccc8232","observation_id":"74f1f61f-ca61-448c-b0be-615a874f2f2c","resolution":{"observed_at":"2026-08-05T11:42:08.525692Z","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":"2026-08-05T11:42:08.929031Z","title":"Avatarverse: High-quality & stable 3d avatar creation from text and pose","venue":null,"work_id":"311790ab-c6d0-4fa0-b0b9-f1113da29782","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.528653Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:cb0042b001b35bbe63336625546579b776aca8e4249aaff0ad5f086c0836eea4","observation_id":"a9653280-6bc2-4d4e-8798-66d6ac7cfbcc","resolution":{"observed_at":"2026-08-05T11:42:08.932090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.920626Z","title":"Fate: Full- head gaussian avatar with textural editing from monocular video","venue":null,"work_id":"0c84567c-f2c5-4d3d-833f-dc93dccaed69","year":2025},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.531298Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:68f51f8e620af000b4e8c331649840a0938d46cf19cad2a0341b3db28332f0f5","observation_id":"7adeb297-99d1-4a59-80ae-e8e2cf953f4a","resolution":{"observed_at":"2026-08-05T11:42:08.923480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.533953Z","title":"Adding conditional control to text-to-image diffusion models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.533953Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:4e85335c42361aaf8c1c48a82dd8eb7947f612be106ff2cf5c1b279d3f08dd36","observation_id":"57ac5fe2-5466-4b66-b4ea-a34cedb3f9ef","resolution":{"observed_at":"2026-08-05T11:42:08.533953Z","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":"2026-08-05T11:42:08.906183Z","title":"Clay: A controllable large-scale generative model for creat- ing high-quality 3d assets","venue":null,"work_id":"46d3ed97-0345-458b-820f-95ff07faafd9","year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.536588Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:95176e6b3549750dc34d939bef5295a5201203ea34df063195591bf8daaa9663","observation_id":"f7e86165-7621-46bb-9046-a2e00cbadae2","resolution":{"observed_at":"2026-08-05T11:42:08.909389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.897830Z","title":"E3gen: Efficient, expressive and ed- itable avatars generation","venue":null,"work_id":"d723b1fd-1fe5-40b5-8d53-259a50c7a957","year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.539111Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:97a87f658c985a3c6b83abd0d644c572171675bb99cb8fc70882544cc4b9c7b7","observation_id":"5526fb6c-82e5-4b0a-8874-9851a96a9218","resolution":{"observed_at":"2026-08-05T11:42:08.900842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.888909Z","title":"Zero-shot text-to-parameter translation for game character auto-creation","venue":null,"work_id":"0a119a8c-9a8f-495f-b5e8-41ac57e3f6ef","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.542017Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:e55f3cd1c7b314f3b37e9df7ed2812bac60e825d9f457cb1fa2f60e5e9a6de1f","observation_id":"d269afdd-8dbc-4600-a2c8-cc579d68c83d","resolution":{"observed_at":"2026-08-05T11:42:08.891922Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.880711Z","title":"Uni-controlnet: All-in-one control to text-to-image diffusion models","venue":null,"work_id":"e28603b5-0e3f-49c6-9de0-b61523bbfca1","year":2023},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.544779Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:c0693313e0acb856eb824caf88a413f7a5f3cc65faa5d63cedf2c3ab2f4b5cce","observation_id":"d4513ced-34d8-4e56-a661-92ca69de8c45","resolution":{"observed_at":"2026-08-05T11:42:08.883490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15957","last_updated":"2024-12-04T12:54:44Z","snapshot_observed_at":"2026-07-06T19:37:03.013065Z","submitted_at":"2024-10-21T12:36:27Z","title":"CamI2V: Camera-Controlled Image-to-Video Diffusion Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.15957","snapshot_observed_at":"2026-08-05T11:42:08.547485Z","title":"Cami2v: Camera-controlled image-to-video dif- fusion model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.547485Z"},"links":{"cited_paper":"/paper/2410.15957","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:3a6ac39246a79275f9a05b669e54a4268a9f994c8084fb0baf584faf4001999f","observation_id":"78806793-234f-4eee-a329-93b53be9e0cc","resolution":{"observed_at":"2026-08-05T11:42:08.547485Z","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":"2026-08-05T11:42:08.871925Z","title":"Pamir: Parametric model-conditioned implicit representa- tion for image-based human reconstruction","venue":null,"work_id":"6814aea7-f764-4982-9efc-9d3723c679ae","year":2021},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.550507Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:2774dbcc1952ed001c64e3feddfe6a79b471603a17d3d3e5ea33b1cb1f119241","observation_id":"1a43a1c3-30ad-4308-b275-da5d03ebe137","resolution":{"observed_at":"2026-08-05T11:42:08.875631Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.863262Z","title":"Detailed avatar recovery from single im- age","venue":null,"work_id":"fd623f1d-e2a2-4556-a9ce-9d8b2fe28b58","year":2021},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.553217Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:d9e377c077087f4dc0a2e9fe6597d5acc5373c81d433bc6c96fd38a47a24082c","observation_id":"5c862847-e019-43a3-ac70-8d576c977940","resolution":{"observed_at":"2026-08-05T11:42:08.866517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.854847Z","title":"Champ: Controllable and consistent human image an- imation with 3d parametric guidance","venue":null,"work_id":"70a4b0fd-91d4-44df-9c7b-442fcb9a8035","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.555802Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:2701e84f4b1047bbeb49758b6fea989277832bc16b0afe54820c1e7eabd40595","observation_id":"ae3dd39a-5e1e-4467-abba-ab86a734f8c7","resolution":{"observed_at":"2026-08-05T11:42:08.857783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.846209Z","title":"Dagsm: Disentangled avatar generation with gs-enhanced mesh","venue":null,"work_id":"656e69a8-23cc-4d7a-a787-8070088c642c","year":2025},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.558568Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:9e0018ad99782886013e3a79f9c0024db54991fbddd2fbccf70b37d7cbbab0c4","observation_id":"1a4e8a5a-065e-4fd2-b439-8d21611f61dc","resolution":{"observed_at":"2026-08-05T11:42:08.849225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.837729Z","title":"Mofanerf: Morphable facial neural radiance field","venue":null,"work_id":"8cd14ef9-fd8c-4655-9d6c-32e7217b450d","year":2022},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.561400Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:0b1e334944d2c9507e473a4c5f3514f18e3016db08e0a993c96717b73354661c","observation_id":"b6da3423-5b96-4267-98dc-afb924f24b4c","resolution":{"observed_at":"2026-08-05T11:42:08.840766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01226","last_updated":"2024-10-02T04:04:10Z","snapshot_observed_at":"2026-07-06T19:25:42.156795Z","submitted_at":"2024-10-02T04:04:10Z","title":"Towards Native Generative Model for 3D Head Avatar","version":1},"cited_work":{"arxiv_id":"2410.01226","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.01226","snapshot_observed_at":"2026-08-05T11:42:08.610784Z","title":"Towards Native Generative Model for 3D Head Avatar","venue":"cs.CV","work_id":"7b56ad2f-f087-4ef6-b960-238ca7fb8a75","year":2024},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.564522Z"},"links":{"cited_paper":"/paper/2410.01226","citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:c5608e00a7007f9f5ff5aec143b7f77e54bc464c3d5f095dc90689ab7cf11928","observation_id":"d46894fa-ca60-4af6-8e14-cf1c38580250","resolution":{"observed_at":"2026-08-05T11:42:08.615932Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.828831Z","title":"Idol: Instant photorealistic 3d human creation from a sin- gle image","venue":null,"work_id":"82271252-c546-45bc-8e5c-daea8e3b80f6","year":2025},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.567332Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:9552a86b25699abe7f0dd173e5508b03ba27c4a003b96f32bbb68169f779619f","observation_id":"2175d1c5-d62a-4ece-870e-cb3019cd5cc2","resolution":{"observed_at":"2026-08-05T11:42:08.831907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.818834Z","title":"6.And as shown in Tab","venue":null,"work_id":"cd270fb4-95c2-425b-94cd-b8daaa38c917","year":2050},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.569815Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:eff58da9c2aae471982f283b4d1dc51cc60b67003b8e7c8fd02a29cb4bdc5efe","observation_id":"ab6d7f42-a3e9-419a-9674-344baa45fb7d","resolution":{"observed_at":"2026-08-05T11:42:08.821525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-05T11:42:08.810106Z","title":null,"venue":null,"work_id":"0a1ad668-2a14-46d9-8b04-147c6cca80eb","year":null},"citing_paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-05T11:42:08.572680Z"},"links":{"citing_paper":"/paper/2509.02466"},"observation_digest":"sha256:09e96b61d86f1c1011c60b889ba7edaa4a802724efe805df443742ca434c0d8d","observation_id":"2c8f6aaf-f96c-49a8-bef9-b625ac0e23d2","resolution":{"observed_at":"2026-08-05T11:42:08.813005Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2509.02466","last_updated":"2025-09-02T16:20:20Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T09:51:53.618217Z","submitted_at":"2025-09-02T16:20:20Z","title":"TeRA: Rethinking Text-guided Realistic 3D Avatar Generation"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":49,"verified_exact":2,"verified_fuzzy":49},"total_outbound_references":103},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 100 of 103 outbound references and 1 inbound Pith citation observation for arXiv:2509.02466."}