{"as_of":"2026-08-10T10:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fdcbe6c28099959ccf281d7bdd1eb12b08c9556030355ffc538d22757359412d","coverage":[{"denominator":71,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":71,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:52:26.826668Z","state":"measured"},{"denominator":71,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":71,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.09748/citation-record","integrity":"/paper/2507.09748/integrity","json":"/paper/2507.09748/citation-record.json","paper":"/paper/2507.09748"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.730367Z","title":"Genie: Gen- erative interactive environments, 2024","venue":null,"work_id":"4dec1cef-1040-495f-9e01-cd0f9ff30755","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.602352Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:8e8b8a2fdd66a7cfa91be908a254be04071e62643334b78ff94519e4d469e391","observation_id":"804f00d1-f8cc-4a30-b641-d404c2eaf573","resolution":{"observed_at":"2026-08-06T17:52:27.733338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.722161Z","title":"Fan- tasia3d: Disentangling geometry and appearance for high- quality text-to-3d content creation, 2023","venue":null,"work_id":"39f07207-3ab0-49ed-9c82-6f43c85fcd57","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.606016Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:1d8def34819bf4236bd25ed9f6f2bde5d62aa46f933947a9ed8bfe21ec0a475e","observation_id":"8c5f232d-3370-48d7-ab85-90848bb378cc","resolution":{"observed_at":"2026-08-06T17:52:27.724858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.712437Z","title":"Cinematic techniques in narrative visualization,","venue":null,"work_id":"a66eb69b-67ab-452b-8ea1-945c8370a32f","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.609166Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:9602fb7ff73d3ccb4734314c70f5d28e76f690e7f14bc73179f1beec0c8f84fa","observation_id":"9f9d3b65-3440-453d-b7d4-b2850de2324e","resolution":{"observed_at":"2026-08-06T17:52:27.716796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.702878Z","title":"Inclusive ar/vr: accessibility barriers for immersive technologies","venue":null,"work_id":"2c390c4a-7ca8-476d-98ce-94554cd66300","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.611947Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:a8e64f0989064985c6abc3b3d3989a87d6429594e384f9124b2b974aeb3e710a","observation_id":"62359b52-1de7-417e-aa0d-e764adda2dbb","resolution":{"observed_at":"2026-08-06T17:52:27.706879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.694640Z","title":"threestudio: A unified framework for 3d content generation","venue":null,"work_id":"defb734a-aed1-40be-a6fc-e54134706e73","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.614822Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:6239ff05f25fea347b372a82ffe8bb3a02f485e187924cafa6ad83977260ead3","observation_id":"69e55dc7-b253-468d-8f1d-b9dae4054103","resolution":{"observed_at":"2026-08-06T17:52:27.697999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.686083Z","title":"CLIPScore: a reference-free evaluation met- ric for image captioning","venue":null,"work_id":"a8aed83d-23bf-44dd-acc3-dd5888f53bc7","year":2021},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.617761Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:4f22ffd057c0e336ed7dd335b147f743d0bf698f41600110596536282b486118","observation_id":"da2ac1d8-376b-4fe0-8bb8-d8ec84fd0c10","resolution":{"observed_at":"2026-08-06T17:52:27.689263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.677973Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilib- rium","venue":null,"work_id":"69b392d4-91b4-40eb-91ef-2ebae783a01c","year":2017},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.620748Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:8b39ec6afbfa4ef46938bd3a87778d553d5321295591ef2dd9860459bc70ae7f","observation_id":"ace06e87-81a6-49d5-8108-aeecdb5dedd7","resolution":{"observed_at":"2026-08-06T17:52:27.680998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.669226Z","title":"Classifier-free diffusion guidance, 2022","venue":null,"work_id":"c4a665cb-3729-459e-89a2-08f57c0a2a23","year":2022},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.623827Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:1722693e0f32043f7f5f8ddd4380339523b3f2be16aeb1baee8f73be57eece79","observation_id":"b1d3d1fb-9972-4568-a75b-04571f05ceae","resolution":{"observed_at":"2026-08-06T17:52:27.672290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.660388Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":"c9061bd0-e861-4afb-9912-77fa5f130810","year":2020},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.626833Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:35ad5d8eb1d811dd08581e47bb99aed357c8c4e2f2642af619dff19682431dd5","observation_id":"ba5a0bc9-5ec9-4b50-ad10-d814eada7968","resolution":{"observed_at":"2026-08-06T17:52:27.663423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.15413","last_updated":"2023-12-19T22:03:12Z","snapshot_observed_at":"2026-08-05T02:31:34.038857Z","submitted_at":"2023-03-27T17:31:13Z","title":"Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.15413","snapshot_observed_at":"2026-08-06T17:52:26.629743Z","title":"Debi- asing scores and prompts of 2d diffusion for robust text-to-3d generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.629743Z"},"links":{"cited_paper":"/paper/2303.15413","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:4275457e00f3cb34b0b649ef785df7e65f1b3ba43f20c3d7034121a407c46362","observation_id":"bd84b2b2-2182-45ac-b81c-39089f2b4611","resolution":{"observed_at":"2026-08-06T17:52:26.629743Z","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":"2026-08-06T17:52:27.651359Z","title":"Lora: Low- rank adaptation of large language models","venue":null,"work_id":"13eafb20-4f30-4481-8732-b3fbafd64986","year":2021},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.633761Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:42ae1497fab6d96ad9a84f3db2cc53f19c7ec4e9b0c59048e2bc46be02f2d0e0","observation_id":"1a7df2fd-9546-4c1e-8ccf-2ae1e9584d98","resolution":{"observed_at":"2026-08-06T17:52:27.654628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.12422","last_updated":"2024-05-06T14:23:25Z","snapshot_observed_at":"2026-08-10T09:59:17.325832Z","submitted_at":"2023-06-21T17:59:45Z","title":"DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.12422","snapshot_observed_at":"2026-08-06T17:52:26.636549Z","title":"Dreamtime: An improved optimiza- tion strategy for text-to-3d content creation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.636549Z"},"links":{"cited_paper":"/paper/2306.12422","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:2f00b788ca82f8593e3928cdc92794838d2b1ffbd06d292a111a897c6eed984f","observation_id":"0de2466e-e43e-429b-9be4-69b500d01c48","resolution":{"observed_at":"2026-08-06T17:52:26.636549Z","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":"2026-08-06T17:52:27.642939Z","title":"Vectorfusion: Text-to-svg by abstracting pixel-based diffusion models","venue":null,"work_id":"fc3acbb1-2562-401b-ad98-0ac0d3468de7","year":1911},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.639721Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:6b6e44cce30299152bb1de666c0acbac2086c9039255f860e82629f00dc824ac","observation_id":"c620eb2a-38b2-4ed3-8ba0-66550b2c626f","resolution":{"observed_at":"2026-08-06T17:52:27.645911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.633449Z","title":"A survey on text-to-3d contents generation in the wild, 2024","venue":null,"work_id":"f1b0970c-661b-42f2-96ee-4afa51dfcbf3","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.642584Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:0a67f6698f453c49e50df1d8728490f7fec0a736ff465512d4ef2b4793bf4562","observation_id":"d8e74448-3090-47f4-9f4b-a6fd9886e69a","resolution":{"observed_at":"2026-08-06T17:52:27.637572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.625404Z","title":"Noise-free score distillation, 2023","venue":null,"work_id":"d33ef4b4-89c1-4dd6-91ad-ca02f62b2167","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.645419Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:3a2ef6eadcf982e9af3b5a942afeafc5774070730dbf177ee726302b72756b7c","observation_id":"e58491a4-20f5-4087-ab9f-aed19f070784","resolution":{"observed_at":"2026-08-06T17:52:27.628384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.616905Z","title":"Automatic differentiation in deep learning","venue":null,"work_id":"4edd49a7-82c8-42f6-92a4-ff97577e5030","year":2021},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.648513Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:4c9d63378e31dec8b6169bfe2500e0b38291380f1120e38adfb09fc4b543c493","observation_id":"2eb67919-0268-49e0-abe7-db3f543aaee8","resolution":{"observed_at":"2026-08-06T17:52:27.619775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.608063Z","title":"Text2video-zero: Text- to-image diffusion models are zero-shot video generators","venue":null,"work_id":"f1da4208-8961-457a-8dad-2da7027f8e5a","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.651152Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:a8363d71077a515517375c737f834f814ea6b9acd86d1f34d82b15ba664735be","observation_id":"aaa099ef-375e-4838-95da-05db9966fb55","resolution":{"observed_at":"2026-08-06T17:52:27.611616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.598671Z","title":"Kingma, Tim Salimans, Ben Poole, and Jonathan Ho","venue":null,"work_id":"cfcddcd3-cb29-4f54-b4d4-f312f2bf78b6","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.654303Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:e5abdda30dde03d47f6061f57324d908462c694d182e1383952eb31ebbfd884c","observation_id":"8c4295ba-276c-4b14-a34c-77ff27455094","resolution":{"observed_at":"2026-08-06T17:52:27.601860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.587287Z","title":"Instant-3d: Instant neural radiance field training towards on- device ar/vr 3d reconstruction, 2024","venue":null,"work_id":"e5c110bf-ac84-422e-b54f-2487106da4ae","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.657167Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:4d6ddf055de518b7607c8e83999049ded80b27f5eebc85bff80c576459aa2b62","observation_id":"141f7ebc-09d1-4f61-a8e9-91b0e2b27c3b","resolution":{"observed_at":"2026-08-06T17:52:27.591207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.577316Z","title":"Magic3d: High-resolution text-to-3d content creation, 2023","venue":null,"work_id":"0ac7e32c-5d70-4fd9-b921-3c6a670b3a30","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.659907Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:4887f07008097f4bf1eb9848012a99de46f119d7a49e2d2510369d72a943388c","observation_id":"48d21b0a-0b61-4dd7-9d80-7c3544060b15","resolution":{"observed_at":"2026-08-06T17:52:27.581409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.567760Z","title":"Point- voxel cnn for efficient 3d deep learning","venue":null,"work_id":"0af0b13f-8354-4c4d-8c4f-5fab695b2581","year":2019},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.662875Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:8a3a776cfa15b93a91356c0311d627948347e40c0c3b52cdf744448637b63fd2","observation_id":"0dc53afc-5039-43be-84a1-ed533c210a48","resolution":{"observed_at":"2026-08-06T17:52:27.571097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.559553Z","title":"Scaledreamer: Scalable text-to- 3d synthesis with asynchronous score distillation","venue":null,"work_id":"9c6948b6-eb5a-48c6-938b-b6bbbc7b9357","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.665657Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:7bb82bf91aea529d6954f4644a5ca79d0c3bf64ccdc9530594a79a05215d3789","observation_id":"0e283e93-03f2-43a7-8670-60f521c0ea0e","resolution":{"observed_at":"2026-08-06T17:52:27.562367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.04391","last_updated":"2023-09-29T18:22:58Z","snapshot_observed_at":"2026-08-10T08:18:58.508599Z","submitted_at":"2023-05-07T23:00:47Z","title":"A Variational Perspective on Solving Inverse Problems with Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.04391","snapshot_observed_at":"2026-08-06T17:52:26.668644Z","title":"A variational perspective on solving inverse problems with diffusion models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.668644Z"},"links":{"cited_paper":"/paper/2305.04391","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:b9eb168b60bead1e94ba34038c9e4836543a787fab47066edab68b2f29fd5c3c","observation_id":"8793694d-3753-4d86-9ec1-d0fa25883caa","resolution":{"observed_at":"2026-08-06T17:52:26.668644Z","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":"2026-08-06T17:52:27.550847Z","title":"Occupancy networks: Learning 3d reconstruction in function space","venue":null,"work_id":"808ee246-a890-47d1-bdf4-253e046ab4df","year":2019},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.672169Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:73e1c4b11a54b83b21cdf73d02de99ee76430176d527a21f9b90e29a6e8ed0fe","observation_id":"d1f26951-335d-44b9-aa36-40bedb80d396","resolution":{"observed_at":"2026-08-06T17:52:27.553840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:26.675797Z","title":"Srinivasan, Matthew Tancik, Jonathan T","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.675797Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:5b2f089036203b7ba1a47d7b017d30dd0cefdba1174dedaaa65cdf38764c4a64","observation_id":"daae6520-f191-4c35-8bc6-5c5f968d5811","resolution":{"observed_at":"2026-08-06T17:52:26.675797Z","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":"2026-08-06T17:52:27.537142Z","title":"Instant neural graphics primitives with a mul- tiresolution hash encoding","venue":null,"work_id":"c79fa460-27eb-473d-8357-3c6350d7baed","year":2022},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.678939Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:cd46158beb7387aa6bc2dda8784908193df1fa8fde7fce7fc461dcf21b6dd907","observation_id":"da5659e8-c575-4291-b0a9-53cdd097abd6","resolution":{"observed_at":"2026-08-06T17:52:27.540140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.527338Z","title":"Robust deep reinforce- ment learning through adversarial loss","venue":null,"work_id":"8e5740d1-424f-4b19-bc16-098b235889b8","year":2021},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.681753Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:2df0ab6ba377ef783c04a85bf6f30c5bc2616d8de09a88aabe7e0645c855f556","observation_id":"7e1d4a05-2641-472f-a55f-e27b1e9df91a","resolution":{"observed_at":"2026-08-06T17:52:27.531004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.493579Z","title":"Automatic differentiation in pytorch","venue":null,"work_id":"05b70e2d-39d4-4ec1-bb3d-425aa097f3ef","year":2017},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.684887Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:fdb8df5070f18b8581d44c1c2583065d394a161fb47b0ecb0dd713420896041c","observation_id":"2de34cfc-1073-42f9-93ab-47ccd3428c63","resolution":{"observed_at":"2026-08-06T17:52:27.517552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.396512Z","title":"Dreamfusion: Text-to-3d using 2d diffusion","venue":null,"work_id":"0e88261f-68d7-4830-9a2f-7f4e725d9b1d","year":2022},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.687955Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:331a55a2547c3101a11ebb8a4f7d095975d8d277ec391e52953ac874a58fc29e","observation_id":"56921b33-7a2a-4ca9-a1c9-625bfb81af71","resolution":{"observed_at":"2026-08-06T17:52:27.411387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.373501Z","title":"Learning transferable visual models from natural language supervi- sion","venue":null,"work_id":"d0ca2261-dfc8-4dba-9daf-1de1e76914a8","year":2021},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.691151Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:c0d70c11c21391672e70a5887aa552ea4fffaaaf9067d8dd2622a33d6e02a9ec","observation_id":"e23c0ac8-15ef-447e-a3c7-89ce9b886f51","resolution":{"observed_at":"2026-08-06T17:52:27.379582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.361676Z","title":"Zero-shot text-to-image generation","venue":null,"work_id":"cb94dbeb-841a-4d59-ae8d-72bf56738a9f","year":2021},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.693986Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:cb354c480308220449b1ace83a45a05bb894d5f8e7c924c4aee845e98dbe9559","observation_id":"e6d1b72d-2351-47e5-885c-da28d0c275a3","resolution":{"observed_at":"2026-08-06T17:52:27.365763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"2026-08-06T17:52:26.697072Z","title":"Hierarchical text-conditional image gener- ation with clip latents","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.697072Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:7d3e728356ed3f0fd71055bf848631e3b7da17f4f674fcacc3928b768a95630d","observation_id":"eb2a38d6-93ab-4cc8-a951-d48e77b705ff","resolution":{"observed_at":"2026-08-06T17:52:26.697072Z","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":"2026-08-06T17:52:27.348141Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"bf512a08-100f-46d1-bd41-db5212c5b6c7","year":2022},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.700191Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:f461afb5912e2374e01d5b432655c06ce9b5d87697ea9e1e8ba257c0441dd0be","observation_id":"ffd1eee7-c278-422d-86b4-f38a2f8d0d95","resolution":{"observed_at":"2026-08-06T17:52:27.353760Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.07937","last_updated":"2024-02-06T06:49:43Z","snapshot_observed_at":"2026-08-10T01:19:25.519733Z","submitted_at":"2023-03-14T14:24:31Z","title":"Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.07937","snapshot_observed_at":"2026-08-06T17:52:26.703287Z","title":"Let 2d diffusion model know 3d- consistency for robust text-to-3d generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.703287Z"},"links":{"cited_paper":"/paper/2303.07937","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:a33cce416a981ea6643428cc2b643b6791154fdf5baa7f232e5b2ddecf19c86a","observation_id":"3a155794-37b0-4869-ba0f-f6681d038ab4","resolution":{"observed_at":"2026-08-06T17:52:26.703287Z","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":"2026-08-06T17:52:26.706901Z","title":"Deep marching tetrahedra: a hybrid repre- sentation for high-resolution 3d shape synthesis","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.706901Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:8380cd52f0850c06a6956bb3fe2b0eb6753fddd1969e269132ead42b4accaca1","observation_id":"8787dc70-4c31-424d-bccb-7316713c0ae7","resolution":{"observed_at":"2026-08-06T17:52:26.706901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.16512","last_updated":"2024-04-18T04:12:32Z","snapshot_observed_at":"2026-07-06T16:12:38.269310Z","submitted_at":"2023-08-31T07:49:06Z","title":"MVDream: Multi-view Diffusion for 3D Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.16512","snapshot_observed_at":"2026-08-06T17:52:26.711247Z","title":"Mvdream: Multi-view diffusion for 3d gen- eration","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.711247Z"},"links":{"cited_paper":"/paper/2308.16512","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:7d1fb8f37b38c92f4dc2aae91ab174ecc1078af2aa9b521bc5b085bf9daf2ecc","observation_id":"97d89da5-b57d-4075-a181-e7bbf9b6a7c5","resolution":{"observed_at":"2026-08-06T17:52:26.711247Z","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":"2026-08-06T17:52:27.331547Z","title":"Graphvae: Towards generation of small graphs using variational au- toencoders","venue":null,"work_id":"429f0196-f86d-4e3c-a3dd-38659c55421e","year":2018},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.714979Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:83cc87adcfba3e20c43eb310875eb3e02000abe78de9bd4c4d70f60af215ff2c","observation_id":"8b51dc97-1b8a-4773-a77b-aa1768b6d75a","resolution":{"observed_at":"2026-08-06T17:52:27.335843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14792","last_updated":"2022-09-29T13:59:46Z","snapshot_observed_at":"2026-07-06T13:57:47.051387Z","submitted_at":"2022-09-29T13:59:46Z","title":"Make-A-Video: Text-to-Video Generation without Text-Video Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14792","snapshot_observed_at":"2026-08-06T17:52:26.718368Z","title":"Make-a-video: Text-to-video generation without text-video data","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.718368Z"},"links":{"cited_paper":"/paper/2209.14792","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:35f5f9ff879e4e21a2bf53a4724ce9e3cc203a9e278312c6781c6b09221d66b1","observation_id":"4ddbea7a-6d83-4c6e-8b57-399afb5787ac","resolution":{"observed_at":"2026-08-06T17:52:26.718368Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.11280","last_updated":"2023-01-26T18:14:32Z","snapshot_observed_at":"2026-08-09T13:26:52.688919Z","submitted_at":"2023-01-26T18:14:32Z","title":"Text-To-4D Dynamic Scene Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.11280","snapshot_observed_at":"2026-08-06T17:52:26.721645Z","title":"Text-to-4d dy- namic scene generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.721645Z"},"links":{"cited_paper":"/paper/2301.11280","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:f7780260028e39c40636b4096dd1a4a2b1f89828eb2a76bebffc34e43cff3491","observation_id":"0a06e8fb-558b-4120-bb5d-3e7892c277e9","resolution":{"observed_at":"2026-08-06T17:52:26.721645Z","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":"2026-08-06T17:52:27.321221Z","title":"Deep- voxels: Learning persistent 3d feature embeddings","venue":null,"work_id":"d39eaa8c-c7f6-4cc0-a74f-c6087debaeeb","year":2019},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.725369Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:e385fd553ac45210120d7d4b04220e992fe14ccb2f37ca26e9554ff1b31e9058","observation_id":"e15a424e-379d-4432-a0d5-9bd716113475","resolution":{"observed_at":"2026-08-06T17:52:27.324861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.309730Z","title":"Implicit neural representa- tions with periodic activation functions","venue":null,"work_id":"b90fd820-b581-4cdd-9679-6f873d9a4aa1","year":2020},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.728383Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:0e866aa17715e4a89ac59ce3323baf7c0cebed7d7f222602d3c2e9ec2b8bd2e4","observation_id":"ce9c3852-19f2-41b8-b341-e14c7d9b9c5b","resolution":{"observed_at":"2026-08-06T17:52:27.314215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.299780Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics","venue":null,"work_id":"10427bef-4d99-4b8a-a13a-207d418ef902","year":2015},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.731728Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:31102250fb7f019df2900636283db1182ccff0d1dba44fc1bd7a13dc139d1a43","observation_id":"bb0962d8-f5ed-4009-820b-467b2643ca4b","resolution":{"observed_at":"2026-08-06T17:52:27.303653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.288497Z","title":"Score-based generative modeling through stochastic differential equa- tions","venue":null,"work_id":"31061647-3fa5-400f-a0e4-e618a0defc7b","year":2020},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.734991Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:ad2d86e2f37e70bac3ff126308460132baef8b0976704c2ddfab5ec151c95b8e","observation_id":"7e35e399-0b6d-43f7-ac24-8d488f5c56c1","resolution":{"observed_at":"2026-08-06T17:52:27.293633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.278321Z","title":"Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction","venue":null,"work_id":"ffdd3dba-a7be-4547-ab92-e78203c1fc5a","year":2022},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.738058Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:8581d8f72b6c50767fd635f6155df70a80da7ad8f783afde66f0259cef0f1c9f","observation_id":"ef5401ba-a834-4334-a371-43b65644c05c","resolution":{"observed_at":"2026-08-06T17:52:27.282722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.01910","last_updated":"2022-09-12T17:04:07Z","snapshot_observed_at":"2026-08-04T22:35:19.026899Z","submitted_at":"2020-08-05T02:33:04Z","title":"Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN","version":4},"cited_work":{"arxiv_id":"2008.01910","doi":null,"metadata_source":"pith","pith_arxiv_id":"2008.01910","snapshot_observed_at":"2026-08-06T17:52:27.009338Z","title":"Hierarchical Amortized Training for Memory-efficient High Resolution 3D GAN","venue":"eess.IV","work_id":"cfb7a7e5-de81-4afb-b618-ff16d45d5c8b","year":2020},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.741042Z"},"links":{"cited_paper":"/paper/2008.01910","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:d0789bb2fa6e492df903b23988c9458e0071119dace571ada40657be4217fc05","observation_id":"f388925c-7b29-4ccb-b71b-930fb1b38486","resolution":{"observed_at":"2026-08-06T17:52:27.013189Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.268055Z","title":"Sta- ble score distillation for high-quality 3d generation, 2024","venue":null,"work_id":"11c28263-3b29-40dd-ab0b-e75b4f19d92a","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.744901Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:198916cb92d2c730f0f8874f14811fe0c16c59b0fd2e8d39b534a50b2f10736f","observation_id":"1ebe106f-811a-4bc5-9e6d-df0e33520f73","resolution":{"observed_at":"2026-08-06T17:52:27.271259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.258792Z","title":null,"venue":null,"work_id":"4d6c20b4-12e7-4ad5-be62-7e565153b4cc","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.748143Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:516338f362221f41a1dc9dc795b5acf98881550a708a667725ed105df593ee86","observation_id":"9e3233af-402c-499c-a24e-7464869d1c2f","resolution":{"observed_at":"2026-08-06T17:52:27.261946Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12439","last_updated":"2023-04-24T20:29:41Z","snapshot_observed_at":"2026-08-07T23:38:32.289718Z","submitted_at":"2023-04-24T20:29:41Z","title":"TextMesh: Generation of Realistic 3D Meshes From Text Prompts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12439","snapshot_observed_at":"2026-08-06T17:52:26.751068Z","title":"Textmesh: Gen- 10 eration of realistic 3d meshes from text prompts","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.751068Z"},"links":{"cited_paper":"/paper/2304.12439","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:df43ba36f5fa331118f3d2799665804a3c1fc29f985678c72288675779708cdd","observation_id":"b7ed78dd-be6b-419d-aa74-65579fa526ae","resolution":{"observed_at":"2026-08-06T17:52:26.751068Z","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":"2026-08-06T17:52:27.247616Z","title":"Atlasnet: Multi-atlas non-linear deep networks for medical image segmentation","venue":null,"work_id":"4582d41d-4390-482b-b3c9-d1a8bcad67c1","year":2018},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.754576Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:745177e6dceac68c0f481faf57c04f9adce2d93eaf746cd6647f805c7f0b48aa","observation_id":"0b332cf5-4b57-4ff0-997d-60122ea4aecc","resolution":{"observed_at":"2026-08-06T17:52:27.252509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:26.757619Z","title":"A connection between score matching and denoising autoencoders","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.757619Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:643393d3193f218ea6dd47a75ecb049bdd9014d104d37b15aa422510e2cb7c99","observation_id":"bed8f39c-8152-4e9f-92be-dca7c7a162a8","resolution":{"observed_at":"2026-08-06T17:52:26.757619Z","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":"2026-08-06T17:52:27.233166Z","title":"Taming mode col- lapse in score distillation for text-to-3d generation, 2024","venue":null,"work_id":"3579421a-aa83-4fac-9289-ea473267dd92","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.760645Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:7c943b83016690fdefe082e565c7c94cfeaecf4438de23a1c92e60a64865b9fc","observation_id":"6ed3f138-fa74-4c31-a6fd-47c707c482f1","resolution":{"observed_at":"2026-08-06T17:52:27.236723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.224294Z","title":"Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion, 2023","venue":null,"work_id":"7b07d786-add3-4750-97d2-809f6a6d0adf","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.763760Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:2263a8904cb53a9095dd1f11d4c173dc4a1a19442ac6fc0fca5091e518aff046","observation_id":"50e5b489-b5aa-4340-b406-d9059d8313fd","resolution":{"observed_at":"2026-08-06T17:52:27.227874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.214399Z","title":"Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distilla- tion","venue":null,"work_id":"1c5dea1e-0ed3-4db6-bd7d-cbd3631d9418","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.766786Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:f66962889961f47c4996c7b94ddc4c67ee78302534a186b9397eab792ea2c370","observation_id":"37c4527f-7437-45e5-a58b-81983e65233d","resolution":{"observed_at":"2026-08-06T17:52:27.219033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.204944Z","title":"Adversarial score distillation: When score distillation meets gan, 2023","venue":null,"work_id":"0ff72d46-adcb-4c34-b6ac-87a700ac7a89","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.769546Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:6eeac7d6ed831447fc6b83d21dea27d7e4756cbd69162153dbe1f369e709e7a6","observation_id":"ed055bb8-35c0-42a4-a53f-15b7a114b107","resolution":{"observed_at":"2026-08-06T17:52:27.209221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.196653Z","title":"Adversarial score distillation: When score distillation meets gan","venue":null,"work_id":"68542545-042d-4409-aefb-6fb862146bfc","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.773745Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:95c49a0af6b5d89c9b2108a13e91105f9af5a5c36a988c0f578116e52b5fa135","observation_id":"38691c99-29b1-48a9-b31a-f97daca293bc","resolution":{"observed_at":"2026-08-06T17:52:27.199855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.187182Z","title":"Video2game: Real-time, interactive, realistic and browser-compatible environment from a single video, 2024","venue":null,"work_id":"4704f59e-1af3-4bf4-a11d-4839d0d7c230","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.776672Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:710ebe8fa390987ce50e2c1339992c6d967485d0f56c33f102800cae59dabcb8","observation_id":"16eb8157-d93e-4dc3-8743-8e59e2b20d27","resolution":{"observed_at":"2026-08-06T17:52:27.190675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.178351Z","title":"Neurallift-360: Lifting an in-the-wild 2d photo to a 3d object with 360deg views","venue":null,"work_id":"7e95123d-49a7-4f2a-9993-26f91304b0bd","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.780017Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:9a755c763eb4c4380726792d73b142d6bbbf3980af73b7ada27df567cfe396f8","observation_id":"423a6e46-3040-48c1-83ff-5a7f5d556224","resolution":{"observed_at":"2026-08-06T17:52:27.181782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.169570Z","title":"Neurallift-360: Lifting an in-the-wild 2d photo to a 3d object with 360deg views","venue":null,"work_id":"81f464a0-fc9f-40e7-8e5b-168615aac459","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.782686Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:13f4260917714657525097e2cbc40a2b453a441b9d5d48413a1505ca335e5d2f","observation_id":"4be2162a-201a-4495-a352-fcebd792c4b9","resolution":{"observed_at":"2026-08-06T17:52:27.173250Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.160274Z","title":"Pointflow: 3d point cloud generation with continuous normalizing flows","venue":null,"work_id":"2f5a42a0-97e1-42bc-b772-97f7028da273","year":2019},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.786152Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:1edc115b3a1bf72ba8999a63b603c5a18c77139a9bd3e9cba42f02978a95856d","observation_id":"b7a3e5a5-2211-4808-bd89-654361b1271f","resolution":{"observed_at":"2026-08-06T17:52:27.164030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.150532Z","title":"Learn to optimize denoising scores for 3d generation: A unified and improved diffusion prior on nerf and 3d gaussian splatting,","venue":null,"work_id":"8360c393-bbf5-4df1-9f23-096b2fede4b3","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.789202Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:c8c27b758be31be1be4c0f36b853d3ba6d582e4312651e2c2f8b40ebcf83eb1e","observation_id":"a6c870d4-4a79-49e3-bace-dfc1663513d2","resolution":{"observed_at":"2026-08-06T17:52:27.154558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.141017Z","title":"Graphrnn: Generating realistic graphs with deep auto-regressive models","venue":null,"work_id":"b2e1f52c-cdc6-45fc-af4a-eb5d75887b25","year":2018},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.792079Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:5a2666a75599d2536a359cd8d12fb56fc6e9510f8f61828aea0392f59a3e8ee0","observation_id":"ac5c906d-a443-42b2-95e7-3edfcf649699","resolution":{"observed_at":"2026-08-06T17:52:27.145126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.131640Z","title":"Text-to-3d with classifier score distillation, 2023","venue":null,"work_id":"1c577fac-6046-4aaf-b5de-0da9199a0e5f","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.795432Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:c0bd35880e0507777ca4141284dc82466b6422e842b34dbee9f015520357f87a","observation_id":"3373f3ef-521c-49ae-93cb-6ffe2dfc9248","resolution":{"observed_at":"2026-08-06T17:52:27.134546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.13223","last_updated":"2024-03-21T06:45:32Z","snapshot_observed_at":"2026-07-06T16:10:19.589022Z","submitted_at":"2023-08-25T07:39:26Z","title":"EfficientDreamer: High-Fidelity and Robust 3D Creation via Orthogonal-view Diffusion Prior","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.13223","snapshot_observed_at":"2026-08-06T17:52:26.799919Z","title":"Efficientdreamer: High-fidelity and robust 3d cre- ation via orthogonal-view diffusion prior","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.799919Z"},"links":{"cited_paper":"/paper/2308.13223","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:12dff80a8666290b6982d7d80d8bb851a970a2d750834e55101bb2427446b9ac","observation_id":"bcc821e0-7a21-4f88-836e-bea85e55a9d2","resolution":{"observed_at":"2026-08-06T17:52:26.799919Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17082","last_updated":"2024-05-20T15:53:32Z","snapshot_observed_at":"2026-08-06T09:10:15.770251Z","submitted_at":"2023-11-28T01:28:58Z","title":"DreamPropeller: Supercharge Text-to-3D Generation with Parallel Sampling","version":3},"cited_work":{"arxiv_id":"2311.17082","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.17082","snapshot_observed_at":"2026-08-06T17:52:26.975340Z","title":"DreamPropeller: Supercharge Text-to-3D Generation with Parallel Sampling","venue":"cs.CV","work_id":"bc4ef43b-9c20-4d18-a886-980835199df8","year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.803307Z"},"links":{"cited_paper":"/paper/2311.17082","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:b7a68f3cab22b330c550e2ba513215a1845eb8cf49255db2e5157115c76bfd6a","observation_id":"e7ed1d14-debd-4ec7-b6ac-970fad886c4e","resolution":{"observed_at":"2026-08-06T17:52:26.979233Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.04057","last_updated":"2024-05-24T17:20:46Z","snapshot_observed_at":"2026-08-09T23:59:11.522112Z","submitted_at":"2024-04-05T12:30:19Z","title":"Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation","version":3},"cited_work":{"arxiv_id":"2404.04057","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.04057","snapshot_observed_at":"2026-08-06T17:52:26.958556Z","title":"Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation","venue":"cs.LG","work_id":"db5350e4-30aa-4221-9fcc-90c814a7f03e","year":2024},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.806552Z"},"links":{"cited_paper":"/paper/2404.04057","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:f0b2f1ec5c88423367f0c9e689e0b19d128cf56e0a822c444103c716f2590ea9","observation_id":"0b7ddd94-e28e-4349-8a11-ba5b0197d661","resolution":{"observed_at":"2026-08-06T17:52:26.964448Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.18766","last_updated":"2024-03-11T06:14:31Z","snapshot_observed_at":"2026-07-06T15:35:15.564727Z","submitted_at":"2023-05-30T05:56:58Z","title":"HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.18766","snapshot_observed_at":"2026-08-06T17:52:26.810417Z","title":"Hifa: High- fidelity text-to-3d generation with advanced diffusion guid- ance","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.810417Z"},"links":{"cited_paper":"/paper/2305.18766","citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:02f25e5f79567358260df2b42be0b9a45bc25bfec74edf6f3c5ed9dfd43458c5","observation_id":"84da716a-4a88-4547-83aa-7997d804d9e5","resolution":{"observed_at":"2026-08-06T17:52:26.810417Z","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":"2026-08-06T17:52:27.122933Z","title":"Diffusion Models","venue":null,"work_id":"4eee940e-a7ad-4d5c-b0ac-1f86628a5ee3","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.814335Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:ddafaf6ac3724c03094be10dc7ace22b1fa5ea6cae313d4dace8e1540cbca839","observation_id":"c7efb843-b379-4505-befc-cd097f46d0a1","resolution":{"observed_at":"2026-08-06T17:52:27.125861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.114156Z","title":"Better Convergence? Maybe No","venue":null,"work_id":"a9da3b56-1df5-4176-8a6d-88182ee677c2","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.817346Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:282dd0afb52298d528f38bd320dd74d5f2f470bab275cfec739040f41dc41e11","observation_id":"d164e176-10be-48c4-83bf-3446082528ac","resolution":{"observed_at":"2026-08-06T17:52:27.117499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.104464Z","title":"Compare VSD with L-VSD","venue":null,"work_id":"8b82475a-6ec5-4122-89c9-982d6923999a","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.820469Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:d4ddc854c52dc86d88959631c3d46683dfc2e331f2101a2efd46ff18b2def74a","observation_id":"18efb933-14e4-430b-91ce-f10cb870ab20","resolution":{"observed_at":"2026-08-06T17:52:27.108251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.095400Z","title":"Settings","venue":null,"work_id":"8c9c156d-19c6-490f-a118-0882757ba7f6","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.823418Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:4fcf4fe29adbfccc464c72bb753d162ce0f7557b5bb03bf27ffee982402d312e","observation_id":"a24475f6-54a9-411b-bc01-6679b8e92a83","resolution":{"observed_at":"2026-08-06T17:52:27.098843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T17:52:27.086256Z","title":"sum\") + F.mse_loss(q_sigmao, r_sigma, reduction=","venue":null,"work_id":"d70983b0-064c-4c8f-b7d3-35fe655b6c82","year":null},"citing_paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T17:52:26.826668Z"},"links":{"citing_paper":"/paper/2507.09748"},"observation_digest":"sha256:ad5b433392cdba05bf2f472a678ff664b6bd6c820e4eb70972f54bfa480054bb","observation_id":"0cfe015a-8495-4b05-8296-49deb84f8362","resolution":{"observed_at":"2026-08-06T17:52:27.089701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.09748","last_updated":"2025-07-13T18:57:45Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T07:40:15.921462Z","submitted_at":"2025-07-13T18:57:45Z","title":"Advancing Text-to-3D Generation with Linearized Lookahead Variational Score Distillation"},"reference_resolution":{"displayed":71,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":3,"verified_fuzzy":53},"total_outbound_references":71},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 0 inbound Pith citation observations for arXiv:2507.09748."}