{"as_of":"2026-08-23T01:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0b4177b8715e43c234596f16e79b2946d8538b54b994875aa0fd406c2376be86","coverage":[{"denominator":53,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":53,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:57:39.935785Z","state":"measured"},{"denominator":53,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":53,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+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/2504.14231/citation-record","integrity":"/paper/2504.14231/integrity","json":"/paper/2504.14231/citation-record.json","paper":"/paper/2504.14231"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T11:57:40.787745Z","title":"Beit: Bert pre-training of image transformers","venue":null,"work_id":"e8f77376-bd92-4605-9790-5c3939f341d3","year":2022},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.728120Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:4ccbe880b2c9811ba5ef54cde89270c377f49ee47c14a872b32434d4652cafa1","observation_id":"b49a7460-3b83-44a8-bef1-63936a31163e","resolution":{"observed_at":"2026-08-16T11:57:40.791532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.774274Z","title":"Cycle and seman- tic consistent adversarial domain adaptation for reducing simulation-to-real domain shift in lidar bird’s eye view","venue":null,"work_id":"ccc71227-2267-4d24-a75f-10ff6e5169b5","year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.732621Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:ad5f368cbcd6ed427110344e74e521c6d74dcde62bb0c30461ff5777fecc629f","observation_id":"1f33d511-44e9-4487-b184-506199a7aac2","resolution":{"observed_at":"2026-08-16T11:57:40.778560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.760631Z","title":"Se- mantickITTI: A dataset for semantic scene understanding of LiDAR sequences","venue":null,"work_id":"0d875764-12b5-4ed7-85dc-91da6c10d19d","year":2019},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.736958Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:b3953716646097de68cb8eeeb87659ee7a75cd8ad44989c52a70cf5a7a34b6f8","observation_id":"d99b96db-2736-40e6-be7c-dc11a2b66f2e","resolution":{"observed_at":"2026-08-16T11:57:40.765503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10791","last_updated":"2025-01-27T13:45:16Z","snapshot_observed_at":"2026-08-20T06:53:33.071397Z","submitted_at":"2024-10-14T17:56:20Z","title":"CAFuser: Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes","version":2},"cited_work":{"arxiv_id":"2410.10791","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.10791","snapshot_observed_at":"2026-08-16T11:57:39.998287Z","title":"CAFuser: Condition-Aware Multimodal Fusion for Robust Semantic Perception of Driving Scenes","venue":"cs.CV","work_id":"5e54bec8-2e85-4687-ad8b-b6fce5f5c0d5","year":2024},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.740891Z"},"links":{"cited_paper":"/paper/2410.10791","citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:fed5f2e0cdadb462e9034a491780a9d69b55ffe2e3563a5d1a86d0aba00a292b","observation_id":"633bd2d3-a5e7-4650-8ce4-9da3c5e4f3dd","resolution":{"observed_at":"2026-08-16T11:57:40.004873Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:39.745591Z","title":"nuscenes: A mul- timodal dataset for autonomous driving","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.745591Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:e69cb4b707ccf1ebdb3d0013929208585a6e57372ed83900d3acd0a83909351f","observation_id":"6294d9d6-fdf1-4a5a-a229-3f909f14e874","resolution":{"observed_at":"2026-08-16T11:57:39.745591Z","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":"2026-08-16T11:57:40.740055Z","title":"Mopa: Multi-modal prior aided domain adaptation for 3d semantic segmentation","venue":null,"work_id":"4d288d97-79e7-401f-94da-b7364634cd2f","year":2024},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.749583Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:8ad0623b53e1c59e30f69bee15b3746137d9468d57032be301fcc3ed6371f937","observation_id":"27a1494f-4def-4dd8-afb4-1f3dac3b9353","resolution":{"observed_at":"2026-08-16T11:57:40.744043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.726761Z","title":"Exploiting the complementarity of 2d and 3d networks to address domain-shift in 3d semantic segmentation","venue":null,"work_id":"4483b834-8745-4214-ba7f-91e121e86a69","year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.753744Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:6b2bbb9b0dea3625b94479c621ecffcc54a50535f3f502f1ac7391312689eff4","observation_id":"5636d3dc-05f3-4f36-a678-7fbdd7ad5c91","resolution":{"observed_at":"2026-08-16T11:57:40.731353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.712487Z","title":"Emerg- ing properties in self-supervised vision transformers","venue":null,"work_id":"9fecd0a3-42d8-44fa-99c1-bdbcaffa6726","year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.757511Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:3156304b92df3404cf35425af7458660680c24b91b4e5cf592a3155d40a069ec","observation_id":"c154e098-20d9-4964-8989-4855e1222ba7","resolution":{"observed_at":"2026-08-16T11:57:40.717333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.698153Z","title":"Self-training avoids using spurious features under domain shift","venue":null,"work_id":"251f3dfa-68af-4fb0-873d-4bc66d8114b1","year":2020},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.761473Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:8542ee0777a29624ced240e35a7aadb661608db58e5b6f69d975895e1ecac6ab","observation_id":"68c672ad-7c54-4cad-9bf8-b93191c520b3","resolution":{"observed_at":"2026-08-16T11:57:40.702551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.683647Z","title":"Stargan: Unified genera- tive adversarial networks for multi-domain image-to-image translation","venue":null,"work_id":"65196d7e-5713-4af6-be44-ab47b4478c39","year":2018},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.765504Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:f43aecd9276399de998141c4540082bd3ffe715131cf4b64d4e7d326bf6151b3","observation_id":"d1d7d7de-3368-44a8-b096-987fad6d5fd9","resolution":{"observed_at":"2026-08-16T11:57:40.688525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.668508Z","title":"An image is worth 16x16 words: Trans- formers for image recognition at scale","venue":null,"work_id":"4f08b943-b3e9-4e4f-a1c3-c3c1ae6bf80b","year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.769679Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:2b6d8d8c0e1bce85f31ec580825013c4b782f329c354ed31fc5dc4735eee9d24","observation_id":"b6d60685-5ac2-49b0-9e75-348c3ae3bdd0","resolution":{"observed_at":"2026-08-16T11:57:40.673323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.655903Z","title":"Virtual worlds as proxy for multi-object tracking anal- ysis","venue":null,"work_id":"11d1ad90-60d9-4a7a-8b74-53df6e4ca784","year":2016},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.773487Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:d1b07ed8629220dc9e56c0bec3bfdfe1df110399e4911ae0d944c962bcd9d8e8","observation_id":"9bdae310-f2bf-48ed-892a-34bb4a2acb6f","resolution":{"observed_at":"2026-08-16T11:57:40.660166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.643304Z","title":"Domain-adversarial training of neural networks","venue":null,"work_id":"21be49f0-1084-492c-8c2c-cbe9abe407b5","year":2016},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.777478Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:f50eddafcc018f350e0c2a1076365494540ca4cf39d10a9def61a94643155ab3","observation_id":"1ec089f6-9e01-4ba2-a194-1ca178c55468","resolution":{"observed_at":"2026-08-16T11:57:40.647362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.06320","last_updated":"2026-07-27T21:25:47Z","snapshot_observed_at":"2026-08-17T17:30:50.394667Z","submitted_at":"2020-04-14T06:45:07Z","title":"A2D2: Audi Autonomous Driving Dataset","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.06320","snapshot_observed_at":"2026-08-16T11:57:39.781022Z","title":"A2d2: Audi autonomous driving dataset","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.781022Z"},"links":{"cited_paper":"/paper/2004.06320","citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:6606247e9333f7d3859072d772ea777a0ba0bc7ae436cfddaf5418a48893a532","observation_id":"f020ff30-6ea6-4e7e-8b7c-b2dfb0431630","resolution":{"observed_at":"2026-08-16T11:57:39.781022Z","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":"2026-08-16T11:57:39.784768Z","title":"3d semantic segmentation with submanifold sparse convolutional networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.784768Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:19467cecca9ecdec06259f01ce5edc3def085d468daa1a51c29d73c609f34cef","observation_id":"770274d9-133a-446b-8b40-b9e384d92f1e","resolution":{"observed_at":"2026-08-16T11:57:39.784768Z","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":"2026-08-16T11:57:39.789244Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.789244Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:10569f46ff25e738b0bc644bc36d0180dff4eb9c7eb06cf1cb353f2c117da713","observation_id":"3646c11f-acf5-4c91-89ac-a58ea158473c","resolution":{"observed_at":"2026-08-16T11:57:39.789244Z","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":"2026-08-16T11:57:40.614817Z","title":"Cycada: Cycle-consistent adversarial domain adaptation","venue":null,"work_id":"f6a881d4-21fb-4cdd-a0ba-8ba13baea2f2","year":1989},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.793218Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:82e6a14f5b623b69a068f5f2f8e1d16d844ef429197bffe4f1898f93b86c585b","observation_id":"34a6f71c-04aa-4e2b-9754-a996ffc88a6e","resolution":{"observed_at":"2026-08-16T11:57:40.618800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.602009Z","title":"xMUDA: Cross-modal unsuper- vised domain adaptation for 3D semantic segmentation","venue":null,"work_id":"6839b048-3d01-4ac5-a7cc-2ec71e972ce6","year":2020},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.797182Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:7d16d64ee00f684f5e829ee365e6dc2da858b3fdd177dd8023568416f1bf8832","observation_id":"9601391e-8a1f-4c8d-b60f-4c8a39774110","resolution":{"observed_at":"2026-08-16T11:57:40.606366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.588449Z","title":"Cross-modal learning for domain adaptation in 3D semantic segmentation","venue":null,"work_id":"ee0a680e-9e33-468c-80a0-2f5d31c04422","year":2022},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.800940Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:3ce0bd2c154d6133a90d420eb1318af29efdc4ae19cf7ed2d8b0746eac7d8792","observation_id":"b1a47038-4e35-4bfa-a39d-23d5f76b0b10","resolution":{"observed_at":"2026-08-16T11:57:40.592707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.575298Z","title":"Scaling up visual and vision-language representation learning with noisy text supervision","venue":null,"work_id":"03740358-288b-4df8-bf30-a8141e5031fc","year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.804741Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:551e32732567ed7498c95fa1499a1e9dfc11bc7209ae930b58056e4d01a32fa8","observation_id":"c808be14-e56a-4a43-9f49-1c1cbe4cb1be","resolution":{"observed_at":"2026-08-16T11:57:40.579747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.563216Z","title":"Segment any- thing","venue":null,"work_id":"984e356b-9c36-454a-9e1a-443e8ebf2226","year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.809379Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:24396ebe86671cdf6ee72f27f1b09d27c34a2b7587ee4afac0ca7990d941c9a5","observation_id":"a7e66568-4dcb-445c-801f-faccf57fb0e8","resolution":{"observed_at":"2026-08-16T11:57:40.567550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.551160Z","title":"Temporal ensembling for semi- supervised learning","venue":null,"work_id":"86c828ea-4545-402f-81e7-47ae7b9090f0","year":2017},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.813205Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:42eee60013c0f9b25f17592ce420fbee4f4c59a7a42d24287c45ef9c250338ef","observation_id":"99c764b7-9250-4e8d-82c0-d5068a2e5d95","resolution":{"observed_at":"2026-08-16T11:57:40.554985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.538637Z","title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","venue":null,"work_id":"336d2daa-7cd7-454c-961c-69086b0f68c3","year":2013},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.816895Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:6e8e1ae5909601cb2e60b4fb4594783e882cbd829459fbe36a0bcbad13fbcea0","observation_id":"6a85b042-d164-431d-89f5-3a936496d5d7","resolution":{"observed_at":"2026-08-16T11:57:40.543011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.526247Z","title":"Mseg3d: Multi-modal 3d semantic segmentation for autonomous driv- ing","venue":null,"work_id":"ed92627d-7ef1-4537-9fe7-2ac47c3ec242","year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.820939Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:691e3958c77558bf87c7e80573ee608c40c3bbb0c47ad935af6a3c4f178335bd","observation_id":"1c247baf-3733-410f-ad39-2ac76a800ede","resolution":{"observed_at":"2026-08-16T11:57:40.530471Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:39.824849Z","title":"Adaptive batch normalization for practical do- main adaptation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.824849Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:bac0d227813bf67a64ef7a5bb30d21e7721ea41fc7e60ae06510ff0a071d8844","observation_id":"3b675444-d96d-48df-b0d0-4a04bd9c485f","resolution":{"observed_at":"2026-08-16T11:57:39.824849Z","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":"2026-08-16T11:57:40.374554Z","title":"Cycle self-training for domain adaptation","venue":null,"work_id":"fb07cb8f-9181-42d0-b7dd-29eb2247e4bb","year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.828467Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:7db6461764f04e98b065d1d24948629b3b0cf1aa537c67d395dffe19cee44d6f","observation_id":"288f3db1-2798-4aa9-afef-bd7a2ee3cc8b","resolution":{"observed_at":"2026-08-16T11:57:40.378663Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.360495Z","title":"Adversarial unsupervised domain adaptation for 3d semantic segmentation with multi-modal learning","venue":null,"work_id":"c1e1a8bc-2458-4d33-92dc-c61ecc2e46e8","year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.832147Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:927ee2db7bcc86813db0c5ee3bc82711de6b6aad489ff02d281e52a4802f4741","observation_id":"40982932-a089-487c-8102-3c53a5e59d17","resolution":{"observed_at":"2026-08-16T11:57:40.365706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.347180Z","title":"Segment any point cloud sequences by distilling vision foundation models","venue":null,"work_id":"b7f6ff7c-b2fd-485f-9deb-5bf62b0afc53","year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.835793Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:2ce6a21df6e2d0543baaa86445fde42cd1438b50d4beaf3f3f0917f26aef4fae","observation_id":"0bbbb9cd-c236-4ab1-9756-ce257a7ad335","resolution":{"observed_at":"2026-08-16T11:57:40.351980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.333880Z","title":"A convnet for the 2020s","venue":null,"work_id":"e8816747-33c9-49db-a10c-f001e44777b0","year":2022},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.839660Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:0e0eb8c26b0be9ac6274a5218d3fce269019524c90865825dc992c44a881ad2b","observation_id":"18a9be52-f6b9-43ba-a02d-6aef0fbab971","resolution":{"observed_at":"2026-08-16T11:57:40.338276Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.318163Z","title":"In- stance adaptive self-training for unsupervised domain adap- tation","venue":null,"work_id":"239bd84f-af7b-44a1-b0eb-bb8aa28bc89c","year":2020},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.843504Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:7051a467187d968bf417daf18795986d43f9ff988628031d35dc1b6266943212","observation_id":"e0950d15-34a3-406e-8baf-70b8ef01eb53","resolution":{"observed_at":"2026-08-16T11:57:40.324588Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.302646Z","title":"Saluda: Surface- based automotive lidar unsupervised domain adaptation","venue":null,"work_id":"740fbf59-2955-4653-964c-d423db35caf2","year":2024},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.847174Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:fdff777982eedaa08cec9850f112b614051a352cbde90a725e3bc55bdf21cfd5","observation_id":"b3635756-a666-478d-a2bd-8d65f6913a55","resolution":{"observed_at":"2026-08-16T11:57:40.307969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.288130Z","title":"The norm must go on: Dynamic unsuper- vised domain adaptation by normalization","venue":null,"work_id":"cb53623e-a6dd-49f3-963d-53c0dfff79cc","year":2022},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.850598Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:06da7c0d38b0b939010867a7c98a6f8a304a52f7a3674b50960786e8da1b5a24","observation_id":"e533cabd-edab-4d6e-b283-58101adcd0a3","resolution":{"observed_at":"2026-08-16T11:57:40.292356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.275377Z","title":"Minimal-entropy correlation alignment for unsupervised deep domain adaptation","venue":null,"work_id":"45e99efc-f644-4599-b47a-dfb6d366001f","year":2018},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.854143Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:bafa19a0c8f4df47da8e5fb1de3017e73a3bd1ed7dca7bba65eead56cc7d61cd","observation_id":"6a0ec51d-4266-4ff4-ac95-aaa37ff93cbc","resolution":{"observed_at":"2026-08-16T11:57:40.279860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-17T13:03:40.359628Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-16T11:57:39.857822Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.857822Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:6853ee7e055842335289f0ba8f56fd99b59dd837c9be2e6c47ba9f4b1f6218a4","observation_id":"f47bcfba-6328-4d7c-a667-c5229edeadca","resolution":{"observed_at":"2026-08-16T11:57:39.857822Z","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":"2026-08-16T11:57:40.260804Z","title":"Sparse-to-dense feature matching: Intra and inter do- main cross-modal learning in domain adaptation for 3d se- mantic segmentation","venue":null,"work_id":"aa69141b-c75c-42a9-8862-395b60c34dac","year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.861839Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:7a31795c8d78f6b975def8b1101196a91ab81069fdb20e09179d4097085a5a02","observation_id":"7f936962-150c-4886-bc6c-95613816534b","resolution":{"observed_at":"2026-08-16T11:57:40.266494Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.248004Z","title":"Learning to adapt sam for segmenting cross-domain point clouds","venue":null,"work_id":"4d1bc77a-d5ac-4f16-8edd-313955d9867f","year":null},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.865538Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:a632cd3a9b0f09da0e022aaecbfd99def10ad89e4dcf27f090ed987a98504825","observation_id":"46fbfc93-b5f1-453a-8189-636cb2b23121","resolution":{"observed_at":"2026-08-16T11:57:40.252164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.234878Z","title":"Three pillars improving vision foundation model distillation for lidar","venue":null,"work_id":"d40bcba2-6eb1-492c-9c5b-647159e541b4","year":null},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.869689Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:2aea4aaa1892362c15d19530400b60dc3a66b1b1fc01acbaf35bb3de6aac3449","observation_id":"7cdc1878-1f9d-4dbd-9370-efb5db3c34f9","resolution":{"observed_at":"2026-08-16T11:57:40.239441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:39.873535Z","title":"Learn- ing transferable visual models from natural language super- vision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.873535Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:f95d982ac953421d76c37fa21527c7d65028641bc7604ef2d9accc5b6280697e","observation_id":"c7ad13b1-9405-43a3-9e5e-3042952dbddf","resolution":{"observed_at":"2026-08-16T11:57:39.873535Z","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":"2026-08-16T11:57:40.209931Z","title":"Am-radio: Agglomerative vision foundation model reduce all domains into one","venue":null,"work_id":"29128c77-9c55-46cf-8faa-4fd39a3f92f7","year":2024},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.877707Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:a3e3051db4a22f46e59219b95cb586b019fb4323db829963da0ba0924b637f26","observation_id":"12d047ac-053d-4ad5-924d-55381fda8a86","resolution":{"observed_at":"2026-08-16T11:57:40.214632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.195427Z","title":"U-net: Convolutional networks for biomedical image segmentation","venue":null,"work_id":"5e36f7b4-c514-401a-b268-db003a66b0cc","year":2015},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.881710Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:5e93ff499e3e5f47a0b13cdd7d1c5bbc93eef015daa5ccdb029cc401e48dc0d6","observation_id":"9c45cb3b-86d4-4c32-88a7-d6133c2e7065","resolution":{"observed_at":"2026-08-16T11:57:40.200779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.183092Z","title":"Image-to-lidar self-supervised distillation for autonomous driving data","venue":null,"work_id":"c13ba0f6-511f-4c98-9ae8-ca556c15d1be","year":2022},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.886438Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:217e74d848c25657ebaa4c46a4ec8f34ab96855840653ed6bccc280692a5a8ca","observation_id":"abb34bee-e20e-44d4-b55b-36300e2f04ad","resolution":{"observed_at":"2026-08-16T11:57:40.187345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.170589Z","title":"Deep coral: Correlation alignment for deep domain adaptation","venue":null,"work_id":"cc244930-5bfe-4408-9a43-3bbee56d2ad7","year":2016},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.891582Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:77dc1c72dfd9a7fe156923b0a2aab50be170afcc2699fd35d7c80030705d154d","observation_id":"86d5109f-84c5-416e-990d-934fd8ee1f91","resolution":{"observed_at":"2026-08-16T11:57:40.175159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.157108Z","title":"Cross-modal unsu- pervised domain adaptation for 3d semantic segmentation via bidirectional fusion-then-distillation","venue":null,"work_id":"96d3cffb-9b8d-4525-b9b0-ae701b8a43b4","year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.896159Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:8a48108386f108fe6972c591a76e6b08bd8306bc5b627454bc967abc08c62569","observation_id":"c7afe072-e402-46ec-b952-d08b95850408","resolution":{"observed_at":"2026-08-16T11:57:40.161458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.144526Z","title":"Unidseg: Unified cross-domain 3d semantic segmentation via visual foundation models prior","venue":null,"work_id":"215e8000-e502-4249-ab2b-88ba5be12417","year":2024},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.900183Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:481dfd202ada77b2588bc34510d6d2e51788eb8014879d6adbdc1f3730f28bb4","observation_id":"cce93922-c4b9-4c04-86f3-4c6ac88519eb","resolution":{"observed_at":"2026-08-16T11:57:40.149207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.129729Z","title":"Fusion-then-distillation: Toward cross-modal positive distillation for domain adaptive 3d semantic seg- mentation, 2024","venue":null,"work_id":"5bd9bce6-d11a-401b-894e-6c3ea57229ea","year":2024},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.904179Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:66ad78fea133de1c9c85f42472c9d6c525aac59ac3608a902c1dff41dc22ed92","observation_id":"91b1d294-3806-4346-b782-a28afec32ee8","resolution":{"observed_at":"2026-08-16T11:57:40.134893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.110721Z","title":"Cross-modal contrastive learning for domain adaptation in 3d semantic segmentation","venue":null,"work_id":"17b2b9ee-272e-4f1c-afe2-0dba427d2a9e","year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.908278Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:cf193111da102ff2da163e4e6fb3ae79863f1f6d46ef92a8a99ef1cf2161ccb0","observation_id":"2de46bec-4e9b-4a98-b36f-9d4b7e47d237","resolution":{"observed_at":"2026-08-16T11:57:40.118799Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.096452Z","title":"Visual foundation models boost cross-modal unsupervised domain adaptation for 3d semantic segmentation, 2024","venue":null,"work_id":"cb8569f6-c164-4570-8273-d758c6804ac7","year":2024},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.911906Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:6a13b72aa0f7e3f397836ac03362a80a5eafd1da51d08ada1a719b5599cc89f8","observation_id":"69de93a8-50e4-4aed-9946-97a7357fdeea","resolution":{"observed_at":"2026-08-16T11:57:40.100852Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.080889Z","title":"Complete & label: A domain adaptation approach to semantic segmen- tation of lidar point clouds","venue":null,"work_id":"db0f79f3-a4e0-4446-9033-0e9b20feeda3","year":null},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.915380Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:d46b79e67dd8fb987c7cb6c59f7c0bec0cbbb777cdbbb797f16d8b4d29e240ca","observation_id":"16b824a2-09a1-45ed-b885-0d35228e4207","resolution":{"observed_at":"2026-08-16T11:57:40.086319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.066195Z","title":"Prototype-guided multitask adversarial network for cross-domain lidar point clouds semantic segmentation","venue":null,"work_id":"288f2c54-e871-4cc2-80e0-1c79ca5ee92f","year":2023},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.919303Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:0eea01eee818811a2a40c1a6ab016c0107ba65eaff151563a127ed3f65822a29","observation_id":"511408c9-b3fb-4473-9654-f28234bed04e","resolution":{"observed_at":"2026-08-16T11:57:40.071394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.052558Z","title":"Wide residual net- works, 2017","venue":null,"work_id":"4468714e-15f6-4bd3-9108-a1c7bdbafe02","year":2017},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.922904Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:200858e18074cf86617da0230fd5bc4fecd91ab4dfe603b1d99eec26ac69d632","observation_id":"ecc17320-7e07-4cdd-a57f-18aeb067df82","resolution":{"observed_at":"2026-08-16T11:57:40.056645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:40.038369Z","title":"Self-supervised ex- clusive learning for 3d segmentation with cross-modal unsu- pervised domain adaptation","venue":null,"work_id":"e6e4444f-773c-4f28-884c-0a1770023bd2","year":null},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.926492Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:512d6ac674a67a1d05d0ee4c1aac42e2006f8759521b7d6d2cf142b6904dfa18","observation_id":"482a17a8-69a6-40e5-be5f-b02cc4e8d046","resolution":{"observed_at":"2026-08-16T11:57:40.042989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-16T11:57:39.930892Z","title":"Segment everything everywhere all at once","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.930892Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:d1ab5a1afba63996d5804e878acb3f71823fd53b3d4e372acd2c21c994f39ef1","observation_id":"79badf17-9136-4109-b65f-a8994eb284ac","resolution":{"observed_at":"2026-08-16T11:57:39.930892Z","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":"2026-08-16T11:57:40.014020Z","title":"Confidence regularized self-training","venue":null,"work_id":"cd31729f-c969-4e88-9aa5-a93901048bd7","year":2019},"citing_paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-16T11:57:39.935785Z"},"links":{"citing_paper":"/paper/2504.14231"},"observation_digest":"sha256:0d63502c74eb305c057284a17e122a3a21d103bf5082996753ba955fa0882640","observation_id":"88aba1b9-42c5-4134-8213-c80126271a53","resolution":{"observed_at":"2026-08-16T11:57:40.018686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.14231","last_updated":"2025-04-19T08:53:54Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T22:30:32.753258Z","submitted_at":"2025-04-19T08:53:54Z","title":"Exploring Modality Guidance to Enhance VFM-based Feature Fusion for UDA in 3D Semantic Segmentation"},"reference_resolution":{"displayed":53,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":1,"verified_fuzzy":44},"total_outbound_references":53},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2504.14231."}