{"as_of":"2026-08-11T01:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:200da53738377277e97a6ce780b6a16a2c88ae586cb1d933669ebbcfb9a98511","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T10:15:52.615399Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"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/2509.04379/citation-record","integrity":"/paper/2509.04379/integrity","json":"/paper/2509.04379/citation-record.json","paper":"/paper/2509.04379"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T10:15:53.595832Z","title":"Sgdm: An adaptive style- guided diffusion model for personalized text to image generation,","venue":null,"work_id":"4cb965fb-594b-4db0-8b7d-6e57e95e0b00","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.390521Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:a6300196927995615a9643a296cc9bfb5be61fc097332be7c42973a1a6c3db5b","observation_id":"766356b6-4889-4530-9627-91386ca8594b","resolution":{"observed_at":"2026-08-05T10:15:53.599525Z","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":"2026-08-05T10:15:53.584032Z","title":"Mmginpainting: Multi-modality guided image inpainting based on diffusion models,","venue":null,"work_id":"eabc6efc-dacc-488b-9775-c422ef933450","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.394977Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:1d41ef8df505ae3227e10c6c547e9f39c7adcde3b401357f6314ec22f5c48234","observation_id":"f318b770-783a-472c-9197-aeda54625632","resolution":{"observed_at":"2026-08-05T10:15:53.588815Z","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":"2026-08-05T10:15:53.573024Z","title":"Animediff: Customized image generation of anime characters using diffusion model,","venue":null,"work_id":"898f3d35-42f5-46e7-9ae3-f1bac7a317ce","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.400024Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:ad5c2ccf1bb0a9a191508bcbf8b25ca3c301ac3ccf99aa1613b9ef153dc32830","observation_id":"0d9f2a20-0314-438a-909b-8b40fcd5ed0b","resolution":{"observed_at":"2026-08-05T10:15:53.576722Z","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":"2026-08-05T10:15:53.561580Z","title":"Videodreamer: Customized multi-subject text-to-video generation with disen-mix finetuning on language-video foundation models,","venue":null,"work_id":"98669075-d221-4266-8920-84ccd773b53c","year":2025},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.404201Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:ccd842c1eaa269d4eb42632778fab6b8f3ac20d3ff29f9fed6ae4cc23f77df02","observation_id":"f12ee7ef-cf49-4c95-9bd4-44164d57da2f","resolution":{"observed_at":"2026-08-05T10:15:53.565692Z","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":"2026-08-05T10:15:53.550297Z","title":"High- resolution image synthesis with latent diffusion models,","venue":null,"work_id":"68100c1b-7ea9-4205-8ce8-7a71d0db52e0","year":2022},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.408539Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:b002e54dbd6673ca9ba3b6e08b3ef44fa586f3ec4c302543ceaed89bec040336","observation_id":"c6ed46db-a4be-4e0a-826c-53bc33a9340c","resolution":{"observed_at":"2026-08-05T10:15:53.553976Z","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":"2308.06721","last_updated":"2023-08-13T08:34:51Z","snapshot_observed_at":"2026-07-06T16:05:39.158819Z","submitted_at":"2023-08-13T08:34:51Z","title":"IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.06721","snapshot_observed_at":"2026-08-05T10:15:52.412763Z","title":"Ip-adapter: Text compatible image prompt adapter for text-to-image diffusion models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.412763Z"},"links":{"cited_paper":"/paper/2308.06721","citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:793812ecf859ead07ee4c9e5795c38b4906acecb2625e035770b659920029ce9","observation_id":"cf3d7711-6e9d-4c35-8684-874791f55ab7","resolution":{"observed_at":"2026-08-05T10:15:52.412763Z","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":"2026-08-05T10:15:53.537001Z","title":"Nerf: Representing scenes as neural radiance fields for view synthesis,","venue":null,"work_id":"54398a66-c076-4bbb-9624-5db0d9040d0d","year":2021},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.417559Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:b2520b98f491b80af1e1f8960d1a22aee3c9187e9c57cf4f0f953a0f5f836935","observation_id":"70bda88e-dd34-4230-bce4-3c52d6d20530","resolution":{"observed_at":"2026-08-05T10:15:53.541773Z","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":"2026-08-05T10:15:53.524673Z","title":"3d gaussian splatting for real-time radiance field rendering","venue":null,"work_id":"8c8292ef-e81b-4995-aaa6-e57c5c605492","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.422166Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:6f2ae2634f5ab079aecc23bdabd439134d2cbdf50134791fe4fd383f40a16287","observation_id":"539b0194-eefe-4da5-9928-688176fe0f65","resolution":{"observed_at":"2026-08-05T10:15:53.528776Z","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":"2026-08-05T10:15:53.512285Z","title":"Dreamfusion: Text- to-3d using 2d diffusion,","venue":null,"work_id":"02d0fde8-7651-47b9-a7df-e866c1135d09","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.425913Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:f0b60be02e6074523b152d2dbbfd6ce6d8334702a38ba30605e2d854e1717fd8","observation_id":"69265a70-7a67-4326-a8b8-d08bbd06a82f","resolution":{"observed_at":"2026-08-05T10:15:53.516504Z","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":"2026-08-05T10:15:53.501489Z","title":"Magic123: One image to high-quality 3d object generation using both 2d and 3d diffusion priors,","venue":null,"work_id":"731b1c34-e942-4458-8b0f-8966136eb15e","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.429697Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:e95c7dc8576d102deb589668fc786e8d2ec980b677fc98d91399b888b3ee9743","observation_id":"f2edf6e8-7c7b-42ec-9a97-99c35985fe42","resolution":{"observed_at":"2026-08-05T10:15:53.505239Z","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":"2026-08-05T10:15:53.489558Z","title":"Realfusion: 360deg reconstruction of any object from a single image,","venue":null,"work_id":"a1215aa6-4ab0-45d1-a9c0-ee1a1c8092ea","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.433548Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:2e59a31ecf68ad327964151ee59e679dd6455118ab3c7f9a4faa387553c21efb","observation_id":"eac5e5e9-103f-443a-92de-09cb911cf82f","resolution":{"observed_at":"2026-08-05T10:15:53.494075Z","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":"2026-08-05T10:15:53.477749Z","title":"Instruct-nerf2nerf: Editing 3d scenes with instructions,","venue":null,"work_id":"71409db5-432a-489a-87ec-caf6bce3d1be","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.437563Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:6dbba13e5f648232536339a85279f0edd0d9b33cc9f787f0956524d368fb80dc","observation_id":"b5c7f5da-bba7-4f78-b047-ee393142780c","resolution":{"observed_at":"2026-08-05T10:15:53.481484Z","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":"2026-08-05T10:15:53.465469Z","title":"Gaussianeditor: Swift and controllable 3d editing with gaussian splatting,","venue":null,"work_id":"1afaff85-e8a2-4051-b28f-109619ca578b","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.441609Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:220f516cd94e8923a773bac078e22a2e9dd6769e0dcb10b40e6079389b13ef2c","observation_id":"17c56c8e-541e-42ef-84a6-68ba000e7146","resolution":{"observed_at":"2026-08-05T10:15:53.469586Z","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":"2408.04249","last_updated":"2024-08-26T10:57:15Z","snapshot_observed_at":"2026-08-09T11:04:59.788671Z","submitted_at":"2024-08-08T06:29:32Z","title":"InstantStyleGaussian: Efficient Art Style Transfer with 3D Gaussian Splatting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.04249","snapshot_observed_at":"2026-08-05T10:15:52.445546Z","title":"Instantstyle- gaussian: Efficient art style transfer with 3d gaussian splatting,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.445546Z"},"links":{"cited_paper":"/paper/2408.04249","citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:0b6c69727055ee40cda828de458c605c2d82ed6af36c385183369f0c2b525588","observation_id":"ed7cecb9-e60f-4b19-808c-d6e8a86421e9","resolution":{"observed_at":"2026-08-05T10:15:52.445546Z","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":"2026-08-05T10:15:52.449770Z","title":"Instructpix2pix: Learning to follow image editing instructions,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.449770Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:80390df50b92eee4942f1c5fca9891fcfa5edae493719310f20297087b4c0d63","observation_id":"793e64d3-c4b6-451d-953f-e14ab4990779","resolution":{"observed_at":"2026-08-05T10:15:52.449770Z","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":"2026-08-05T10:15:53.445590Z","title":"Learning to stylize novel views,","venue":null,"work_id":"9406b539-d7dc-4ad3-883f-4869ee3021fb","year":2021},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.453704Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:c6259e4774a221185abc120cbd14083e782785598e1d1b5575ffbdcd852a2474","observation_id":"a87aa453-a629-42e4-b4c9-182de8a8ccd3","resolution":{"observed_at":"2026-08-05T10:15:53.449418Z","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":"2026-08-05T10:15:53.433713Z","title":"3d photo stylization: Learning to generate stylized novel views from a single image,","venue":null,"work_id":"d03083e5-72fa-40cd-96ea-5e346703a5f7","year":2022},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.457380Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:42eaa93aa289ffb0e10bf70d4b64224862f2d41695bc2ee8d31dbda4ca090b57","observation_id":"00bc91ce-e249-452d-961e-5a8a3ef4133f","resolution":{"observed_at":"2026-08-05T10:15:53.437670Z","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":"2026-08-05T10:15:53.422298Z","title":"3dstylenet: Creating 3d shapes with geometric and texture style variations,","venue":null,"work_id":"ca58438c-3c7d-4ace-b10d-ff800d2d8eeb","year":2021},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.460885Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:96b4aef5e2e916916dc0fcaeea90c9dd28a9dc40a1cefc2633f2dc5c8fa1da9a","observation_id":"8b0978a4-355f-4ed2-8af5-6c1608a1ffa9","resolution":{"observed_at":"2026-08-05T10:15:53.426269Z","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":"2026-08-05T10:15:53.410661Z","title":"Text2mesh: Text-driven neural stylization for meshes,","venue":null,"work_id":"4b540391-7dcf-4234-ac63-9ea424bb7829","year":2022},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.464639Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:452ea3b3f380e0dc265f4dfb02f495cb28c4723c39c14ce286894ca8b65b2057","observation_id":"42cbab18-c1d4-4edc-8e63-5e8705b65945","resolution":{"observed_at":"2026-08-05T10:15:53.414656Z","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":"2026-08-05T10:15:53.398426Z","title":"Arf: Artistic radiance fields,","venue":null,"work_id":"0ee9ca6d-91a9-49d4-9788-fde80fb71993","year":2022},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.468245Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:ffbda62e599258784596da1b32e7f7aad19a60df4b688e087c13c82f45e4f6ae","observation_id":"acdee0b8-69f3-429d-b5c1-8784d14596dc","resolution":{"observed_at":"2026-08-05T10:15:53.402129Z","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":"2026-08-05T10:15:53.387112Z","title":"Stylerf: Zero-shot 3d style transfer of neural radiance fields,","venue":null,"work_id":"589bbece-5e9a-4b5c-b486-1121dd0852fa","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.472149Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:3f41c205ec2afb52f78396f41bb3d6faef2b2bab1a34f77ea81bc622f911dd73","observation_id":"e52cb48e-ed92-49c8-b6fc-686eabc38187","resolution":{"observed_at":"2026-08-05T10:15:53.390873Z","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":"2026-08-05T10:15:53.375148Z","title":"Stylegaussian: Instant 3d style transfer with gaussian splatting,","venue":null,"work_id":"6e31c68a-e1c7-4339-a9b8-3721104d16b9","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.476199Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:f8a4cd622fb23b4beef47255a6a0b2bdb94d36286018da559ec47a3288f0823c","observation_id":"92835250-1136-4be3-8ca4-35e61480629f","resolution":{"observed_at":"2026-08-05T10:15:53.379223Z","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":"2026-08-05T10:15:53.362168Z","title":"G-style: Stylized gaussian splatting,","venue":null,"work_id":"8209d126-a8b7-4a3f-93a4-b7cbc9c9d9cf","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.479908Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:8e180b9242f5d553f7c97c2b87c22d3633a9baa2536bf14fd93ba187c6b3f250","observation_id":"81754d31-9b1a-4327-ad9b-b7960ec49ce7","resolution":{"observed_at":"2026-08-05T10:15:53.367567Z","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":"2026-08-05T10:15:53.349939Z","title":"Gaussian grouping: Segment and edit anything in 3d scenes,","venue":null,"work_id":"fe50e545-116c-4aea-baf4-9611defb7263","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.483543Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:0d0b9f19b284eec21ef22dbe71c72b88313e900242e10538730f52179f6a94ea","observation_id":"d867ba74-fee8-4161-b2ac-6a7bc3225cb5","resolution":{"observed_at":"2026-08-05T10:15:53.353945Z","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":"2026-08-05T10:15:52.487270Z","title":"U-net: Convolutional networks for biomedical image segmentation,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.487270Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:999d2d38d6a12e783aaff7c9cea399fc29c38c04b8dfc95309f8de7a93d20681","observation_id":"6e684bb7-c973-42c0-b1ca-df7b9b31ce3c","resolution":{"observed_at":"2026-08-05T10:15:52.487270Z","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":"2026-08-05T10:15:53.326935Z","title":"Neural style palette: A multimodal and interactive style transfer from a single style image,","venue":null,"work_id":"fcaac702-d759-434c-aefc-280d9c1a933f","year":2021},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.490906Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:ded2597ffa4d28bb5ca88b5ccf0a4d61734dc5594e17bee93b3f1759a6037fd4","observation_id":"fd09174d-49e4-4655-bef0-3ef2a9a43719","resolution":{"observed_at":"2026-08-05T10:15:53.331345Z","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":"2026-08-05T10:15:53.315285Z","title":"Structure-guided arbitrary style transfer for artistic image and video,","venue":null,"work_id":"f7b371d1-c67c-40e4-95f2-fc5902ae26fd","year":2022},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.495378Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:c6eec4f5679fd3b0942da0962deefad617e0da3ac41e6d3af9d0062322edb842","observation_id":"376d2f8a-c6f3-4ca1-a295-ff34749ba240","resolution":{"observed_at":"2026-08-05T10:15:53.319413Z","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":"2026-08-05T10:15:53.304314Z","title":"Texture preserving photo style transfer network,","venue":null,"work_id":"90aba7c4-6ec2-4c23-a322-c3f8d547b1f8","year":2022},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.499239Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:52f893c17d063265c5f2c64af2f9d50271ba116cb2f91f7bd164b881a6664e5e","observation_id":"2df38972-1a9d-43f1-825a-c272ee72f9cd","resolution":{"observed_at":"2026-08-05T10:15:53.307908Z","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":"2026-08-05T10:15:53.293114Z","title":"Lccstyle: Arbitrary style transfer with low computational complexity,","venue":null,"work_id":"289df711-a312-41a2-83f8-9156d60a04bc","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.503448Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:d41784878c334e69fcc259c744b704303e9182b9509e43236343513999dc8f16","observation_id":"e61d2e47-0fcf-4cc3-9b9d-79777eb6d0b0","resolution":{"observed_at":"2026-08-05T10:15:53.296859Z","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":"2026-08-05T10:15:53.281727Z","title":"Towards high-quality photorealistic image style transfer,","venue":null,"work_id":"7c70c768-b259-44ab-97e9-dabd71600583","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.507624Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:2feba03e241116ea7f3d03159d29cdccedbf688a94323418c29eab404e5f5f61","observation_id":"80f803be-fdd8-42b8-82d5-07dba787191b","resolution":{"observed_at":"2026-08-05T10:15:53.285819Z","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":"2026-08-05T10:15:53.270083Z","title":"Image style transfer using convolutional neural networks,","venue":null,"work_id":"12891a88-b1a2-43de-9187-4f49e4380026","year":2016},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.511559Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:c8d72be76a66ddbc15e12ce7d1dfd07c6c887b598145dc35d095b0e88651d34a","observation_id":"ca544df3-914f-4996-8aec-c824bedc3d3d","resolution":{"observed_at":"2026-08-05T10:15:53.273862Z","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":"2026-08-05T10:15:53.258886Z","title":"Arbitrary style transfer in real-time with adaptive instance normalization,","venue":null,"work_id":"82e9a411-5d55-4959-a178-5391db413774","year":2017},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.515252Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:72f7c6783ae0c46902de4c88bed8ca59f7e0c26f59d6a4ef9aeaafbaad5a8aba","observation_id":"8b28a9bd-b102-4e24-8664-8d2dacbce405","resolution":{"observed_at":"2026-08-05T10:15:53.262856Z","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":"2026-08-05T10:15:53.247569Z","title":"Neural style transfer: A review,","venue":null,"work_id":"d885fc2a-319c-4a34-a832-5a07524af4d9","year":2019},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.518898Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:78498fd78bfea57a5f34d1f03a31ec0e72d367e4aa194149cbc0278dd0d66192","observation_id":"9b4ce0ef-98af-410a-b225-165057a6b9cd","resolution":{"observed_at":"2026-08-05T10:15:53.251416Z","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":"2026-08-05T10:15:53.235522Z","title":"Styledrop: text-to-image generation in any style,","venue":null,"work_id":"a675950b-ea13-400a-a3c7-eca09205d1ca","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.522731Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:2c4e074ac31c282721d73983e4f485485bbf8357b92823bb4f8bf95563fb2b18","observation_id":"3bde6b72-e3cb-49b7-b28a-b324d921e0d3","resolution":{"observed_at":"2026-08-05T10:15:53.239705Z","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":"2026-08-05T10:15:53.223929Z","title":"Styleadapter: A unified stylized image generation model,","venue":null,"work_id":"aafec349-fcd2-4ebc-ac6d-c7688229f413","year":1911},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.526452Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:a36b2facac60697af88cc90bdbcce517c4025380aae1e40c9f8744202a8cb2a8","observation_id":"8dc58cfd-48e9-4429-8519-db13da4bf727","resolution":{"observed_at":"2026-08-05T10:15:53.227817Z","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":"2026-08-05T10:15:53.211963Z","title":"Style aligned image generation via shared attention,","venue":null,"work_id":"7186b2fd-26d0-4204-a904-5817f3de0c0d","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.530137Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:e017abfc54927ee7df75a3546dd9f5126bd009b28affe22cf259cf6a76571b76","observation_id":"cf48b8e7-54f1-4c39-acd8-ea13dccf75b6","resolution":{"observed_at":"2026-08-05T10:15:53.216244Z","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":"2026-08-05T10:15:53.198260Z","title":"Style injection in diffusion: A training-free approach for adapting large-scale diffusion models for style transfer,","venue":null,"work_id":"08b794af-785a-4bde-8e2d-31e4a6dd9510","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.534981Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:d02b6d988ca30794bbb4cfd31f2840ebe2709953b2926eac16a6fb89aacd6efe","observation_id":"348ad40a-082b-4e83-a991-0b0230f6dbdf","resolution":{"observed_at":"2026-08-05T10:15:53.202562Z","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":"2404.02733","last_updated":"2024-04-04T19:42:32Z","snapshot_observed_at":"2026-08-10T02:44:02.758679Z","submitted_at":"2024-04-03T13:34:09Z","title":"InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02733","snapshot_observed_at":"2026-08-05T10:15:52.539768Z","title":"Instantstyle: Free lunch towards style-preserving in text-to-image gen- eration,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.539768Z"},"links":{"cited_paper":"/paper/2404.02733","citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:31912fc4157fbe07932d0f780fc895c04fec5c8bec6cdf6ae277a57414835d75","observation_id":"3dcd9faf-62d5-4898-bae7-132419a052d5","resolution":{"observed_at":"2026-08-05T10:15:52.539768Z","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":"2026-08-05T10:15:53.185128Z","title":"Vica-nerf: View-consistency-aware 3d editing of neural radiance fields,","venue":null,"work_id":"e0f8aa4a-1096-4cd7-b5cb-eb387f16e3d0","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.543960Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:35049d7ef8b9bc76ffe671a20435287a8c39e0df2b79e1bf6509e75b9d2d083c","observation_id":"3330bb31-c4de-459e-838c-5573fc0df16e","resolution":{"observed_at":"2026-08-05T10:15:53.189819Z","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":"2026-08-05T10:15:53.171089Z","title":"Dreameditor: Text- driven 3d scene editing with neural fields,","venue":null,"work_id":"032e5332-333a-485a-9096-75bb0049f6ac","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.548617Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:d6ce5b0818507ddacca6ae35a7942afaffd33264cba55f55da81d07068503508","observation_id":"dcef12a6-fe06-435b-b8c4-0060841e5a25","resolution":{"observed_at":"2026-08-05T10:15:53.175291Z","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":"2026-08-05T10:15:53.158493Z","title":"Gaussctrl: Multi-view consistent text-driven 3d gaussian splatting edit- ing,","venue":null,"work_id":"9ef69174-575b-4688-98c7-09e3bcb9f2bd","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.552482Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:7e4ac468d73abbfe036786685b8159a03bc983a8f5b9804769affffe7e5682d9","observation_id":"eaabd3db-9ba2-4237-9c9e-44bc136e6434","resolution":{"observed_at":"2026-08-05T10:15:53.163318Z","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":"2026-08-05T10:15:53.146080Z","title":"Zero-shot text-driven dynamic neural radiance fields stylization,","venue":null,"work_id":"279e842f-d15f-4abc-a34d-bfde39fbd7cc","year":2025},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.556570Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:40950aac2d4b2a9996b092da1d2c22701a00d52930b0fc9944d09f870aacbec9","observation_id":"0b0867b0-5f44-43aa-8fd6-d0e057d4d321","resolution":{"observed_at":"2026-08-05T10:15:53.150727Z","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":"2026-08-05T10:15:53.133418Z","title":"Learning transferable visual models from natural language supervision,","venue":null,"work_id":"e34ad6a7-f71b-47bf-aeb0-df9c68040021","year":2021},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.560519Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:01722d231a64d77375cb700f7e34676ec931b5d8293070de202e89b168818c09","observation_id":"f0197516-e669-4286-82bc-f1c87dee0bf2","resolution":{"observed_at":"2026-08-05T10:15:53.138128Z","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":"2026-08-05T10:15:53.120842Z","title":"Locally stylized neural radi- ance fields,","venue":null,"work_id":"e6a78420-cab9-4d29-964a-37ad554ee2f9","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.565228Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:7788280ab7dd9f0e9ded516af8d58b9670c0901dfb4ad8d56d7cb85420522d00","observation_id":"3076a8ae-a816-412d-aa1a-f9e4f0ea2ef3","resolution":{"observed_at":"2026-08-05T10:15:53.124784Z","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":"2026-08-05T10:15:52.569177Z","title":"Segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.569177Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:872da488c720074c072c7fdf3da3d4c33046ab436a47610285ecebfc8b459424","observation_id":"ca0fb905-5767-4b8c-8a83-0a138b7c0783","resolution":{"observed_at":"2026-08-05T10:15:52.569177Z","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":"2026-08-05T10:15:53.098871Z","title":"Tracking anything with decoupled video segmentation,","venue":null,"work_id":"4ed530f0-981f-4b8a-8578-e7438642c715","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.572776Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:d5e7086ecf659a811a40173db70ef6d9d01410bf9aae78cd19b67b838c9986c1","observation_id":"d4fcda4e-aaa3-490e-8771-d81308be9694","resolution":{"observed_at":"2026-08-05T10:15:53.103060Z","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":"1607.06450","last_updated":"2016-07-21T19:57:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-07-21T19:57:52Z","title":"Layer Normalization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1607.06450","snapshot_observed_at":"2026-08-05T10:15:52.576368Z","title":"Layer normalization,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.576368Z"},"links":{"cited_paper":"/paper/1607.06450","citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:9051bbdf8339b307a914ce5f9467fab57f0d2ee1eefa6c203504e4743c68f6ee","observation_id":"a6674f6c-28c6-40b9-90f6-79aef44ecb56","resolution":{"observed_at":"2026-08-05T10:15:52.576368Z","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":"2026-08-05T10:15:53.085441Z","title":"Adding conditional control to text-to-image diffusion models,","venue":null,"work_id":"17cb79ba-fca4-4113-83f2-c6fe884b29dc","year":2023},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.581284Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:77dbc5644907ac0d3a4c4a772d64c6c2debf0184b286136a1b79d26365e7344a","observation_id":"fba742eb-faa7-4e35-bfdf-c0892c52bdfa","resolution":{"observed_at":"2026-08-05T10:15:53.089819Z","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":"2026-08-05T10:15:53.072789Z","title":"Denoising diffusion implicit models,","venue":null,"work_id":"f0415baf-d95e-463c-91e6-850372aeec10","year":2021},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.584889Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:5363d10ff45899cb471921865a6f62019e2f534e4db807005baffe8a7d9a41d4","observation_id":"f56192ee-f0e3-4cc7-95a7-48c1341ad414","resolution":{"observed_at":"2026-08-05T10:15:53.076817Z","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":"2026-08-05T10:15:52.588593Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.588593Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:ff91bafd753d99c02bc7e40ea42517756a0c7125d5d104933dac2a815860f451","observation_id":"4cd05f62-bcf0-4ebd-b23e-bdcbdc2aea92","resolution":{"observed_at":"2026-08-05T10:15:52.588593Z","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":"2026-08-05T10:15:53.054230Z","title":"Local light field fusion: Practical view synthesis with prescriptive sampling guidelines,","venue":null,"work_id":"e6fec844-1d9b-4ecd-bf66-da8ceb4ea0f3","year":2019},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.592064Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:99d9bdeeef1fb9598254f80c3abb12c7781f907613d8bf374e49c08ce810a435","observation_id":"cf277090-1f1d-428a-9ae7-f888af481366","resolution":{"observed_at":"2026-08-05T10:15:53.058049Z","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":"2026-08-05T10:15:52.596064Z","title":"Tanks and temples: Benchmarking large-scale scene reconstruction,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.596064Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:3317913e81c20112dacd31edcd86ca67f5680b5895b987c670ffaed3cfdfe52d","observation_id":"4081e4b4-3f12-4fac-b742-40a1081f6d65","resolution":{"observed_at":"2026-08-05T10:15:52.596064Z","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":"2026-08-05T10:15:53.033074Z","title":"Raft: Recurrent all-pairs field transforms for op- tical flow,","venue":null,"work_id":"ed74489d-31a9-4ee5-b5f6-37cef459bad6","year":2020},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.600254Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:4002f62f7ff2b3276c2153bc97108f1215efa587021d78433e5e1e3c8727ab4d","observation_id":"7e07e02e-de8d-48c9-984c-88b642cc9d5b","resolution":{"observed_at":"2026-08-05T10:15:53.037225Z","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":"2026-08-05T10:15:53.020818Z","title":"Softmax splatting for video frame interpolation,","venue":null,"work_id":"49a302e7-3ce4-4232-bd78-02e2e0f0fa71","year":2020},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.603884Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:781cc596d9de10d16c57b9c1bf8175a1078d81ee01262fffe488d065f3c7baa6","observation_id":"46af37a3-4c4d-4d3c-979c-aa8da5f40a18","resolution":{"observed_at":"2026-08-05T10:15:53.025098Z","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":"2026-08-05T10:15:52.607376Z","title":"The unreasonable effectiveness of deep features as a perceptual metric,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.607376Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:b371936c7fba54b20f23c7292a3102d9cc2bacbb1ac81e603fc0325663581403","observation_id":"48391bb6-bf9d-463b-8c4a-a4aebfccf38e","resolution":{"observed_at":"2026-08-05T10:15:52.607376Z","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":"2026-08-05T10:15:52.995994Z","title":"Anyv2v: A tuning- free framework for any video-to-video editing tasks,","venue":null,"work_id":"2d122470-9f2d-4e79-bfa2-c381e083279d","year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.611749Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:5c1ec84a908ffa3502c2a46a0d176254bde4d70836bc0eb0d239d7a11db509e3","observation_id":"1b2511b4-cd93-4cef-a7b4-63a3d492ec6e","resolution":{"observed_at":"2026-08-05T10:15:53.002235Z","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":"2026-08-05T10:15:52.615399Z","title":"Univst: A unified framework for training-free localized video style transfer,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T10:15:52.615399Z"},"links":{"citing_paper":"/paper/2509.04379"},"observation_digest":"sha256:c2cb37d967f3a573ea87c0e4ee3b5039a64f5d5305f6339aa888c360a31e1b2b","observation_id":"3b0ad28b-18ee-449e-a343-1736c9edf875","resolution":{"observed_at":"2026-08-05T10:15:52.615399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.04379","last_updated":"2025-09-04T16:40:44Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T03:26:09.345084Z","submitted_at":"2025-09-04T16:40:44Z","title":"SSGaussian: Semantic-Aware and Structure-Preserving 3D Style Transfer"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":46},"total_outbound_references":57},"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 11 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2509.04379."}