{"as_of":"2026-08-19T08:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:584b0e44e6e9fa004af514fdbe3a71004e36418d666abf48c8e82f846b6b2d15","coverage":[{"denominator":59,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":59,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:32:26.392220Z","state":"measured"},{"denominator":59,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":59,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2504.12599/citation-record","integrity":"/paper/2504.12599/integrity","json":"/paper/2504.12599/citation-record.json","paper":"/paper/2504.12599"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:32:27.066562Z","title":"Domain adaptive lidar point cloud segmentation with 3d spatial consistency,","venue":null,"work_id":"88e1981d-d949-4090-9728-c9413927f5ad","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.194261Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:72d0fc12b2cbba8560d9868581b685e3d44c3c9f637cef12f8d54e96395f6779","observation_id":"7a987b26-8499-4666-af90-7850b13e5dc4","resolution":{"observed_at":"2026-08-16T12:32:27.070298Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:27.055643Z","title":"Region-enhanced feature learning for scene semantic segmentation,","venue":null,"work_id":"84861936-e9fc-4d25-ab91-79e79fcec274","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.198755Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:fcf3a34fee436394c481930c81e7a6658b37a20b5ea51e43a1a42817fae390d9","observation_id":"d499a49b-a01f-4bb9-886c-0deeacf801f1","resolution":{"observed_at":"2026-08-16T12:32:27.059523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:27.044844Z","title":"Lif-seg: Lidar and camera image fusion for 3d lidar semantic segmentation,","venue":null,"work_id":"38fd9874-4e29-4a0c-98b6-517ae22caedd","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.203159Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:b553a71b3a3aee3c400051e7849f4a081c19aa80d4a58fb6bf4d8f35d70823ab","observation_id":"87bae1c0-812e-4838-97c4-f692e967afb2","resolution":{"observed_at":"2026-08-16T12:32:27.048544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:27.033552Z","title":"Adaptive margin contrastive learning for ambiguity-aware 3d semantic segmentation,","venue":null,"work_id":"063b2669-f2ed-4481-89fe-996be32436b0","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.206814Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:e6bb3f292b21db4fffbe14ed09727544ec1816e3c30746339d65a5d2f96f3b2d","observation_id":"b13b7c22-8bf0-4d58-abb6-160fd859ba2a","resolution":{"observed_at":"2026-08-16T12:32:27.037655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.00173","last_updated":"2025-01-31T21:30:59Z","snapshot_observed_at":"2026-08-15T21:00:45.696433Z","submitted_at":"2025-01-31T21:30:59Z","title":"Lifting by Gaussians: A Simple, Fast and Flexible Method for 3D Instance Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.00173","snapshot_observed_at":"2026-08-16T12:32:26.210750Z","title":"Lifting by gaussians: A simple, fast and flexible method for 3d instance segmentation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.210750Z"},"links":{"cited_paper":"/paper/2502.00173","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:6ae7e753c229ba319da0dba327d69200292d3f0a7f3a569e9f6867c6ccdbd674","observation_id":"517a53a3-fc56-4ca5-b316-46807c36fc8a","resolution":{"observed_at":"2026-08-16T12:32:26.210750Z","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":"2026-08-16T12:32:27.022274Z","title":"Efficient 3d semantic segmentation with superpoint transformer,","venue":null,"work_id":"3fcd1278-766c-41f9-8f69-132ea6b95392","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.214773Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:164fc3f7c61c9538e9b1fd460f7fc62158d8528619a5fa8db6d7bf87d3497277","observation_id":"46ef22ad-bfb7-4f35-b44b-23778eecce1d","resolution":{"observed_at":"2026-08-16T12:32:27.026119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:27.011382Z","title":"Large-scale point cloud semantic seg- mentation with superpoint graphs,","venue":null,"work_id":"0766fc93-afc9-4773-8d64-bd3dba2ab809","year":2018},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.218533Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:5bf2845cda97109fb25e354c8935ceafe08058927376d2740532122dba651027","observation_id":"4fd0e73c-4855-4a2f-a316-4b8fac41fa0f","resolution":{"observed_at":"2026-08-16T12:32:27.014875Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:27.000641Z","title":"Toward better boundary preserved supervoxel segmentation for 3d point clouds,","venue":null,"work_id":"89048b8a-17be-4058-b058-b72e9fa1561b","year":2018},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.222041Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:4b660504a6e06d7fccbf8c39413db57e659228872def7b9fc2b6c07a9e6fd349","observation_id":"6ae38225-e6fd-408a-9d62-848fc11a2342","resolution":{"observed_at":"2026-08-16T12:32:27.004501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.04995","last_updated":"2025-01-09T06:20:00Z","snapshot_observed_at":"2026-08-10T21:18:24.275595Z","submitted_at":"2025-01-09T06:20:00Z","title":"IPDN: Image-enhanced Prompt Decoding Network for 3D Referring Expression Segmentation","version":1},"cited_work":{"arxiv_id":"2501.04995","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.04995","snapshot_observed_at":"2026-08-16T12:32:26.524179Z","title":"IPDN: Image-enhanced Prompt Decoding Network for 3D Referring Expression Segmentation","venue":"cs.CV","work_id":"cecc86d0-e374-4b00-a75f-a5f843f2c2e6","year":2025},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.225404Z"},"links":{"cited_paper":"/paper/2501.04995","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:f5f57a33225662a8ccb89127928200b4eba154326f119839b222a87762efd8ff","observation_id":"e91528bb-4219-4830-89c2-e179720bf1a9","resolution":{"observed_at":"2026-08-16T12:32:26.528206Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.02402","last_updated":"2024-12-22T10:51:52Z","snapshot_observed_at":"2026-08-13T23:23:26.142043Z","submitted_at":"2024-12-03T11:50:16Z","title":"RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation","version":2},"cited_work":{"arxiv_id":"2412.02402","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.02402","snapshot_observed_at":"2026-08-16T12:32:26.509092Z","title":"RG-SAN: Rule-Guided Spatial Awareness Network for End-to-End 3D Referring Expression Segmentation","venue":"cs.CV","work_id":"0075672a-0101-4a6c-a03a-8a7bfc45161b","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.229162Z"},"links":{"cited_paper":"/paper/2412.02402","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:4e0bddbd07942be8d6d2da4a785ce6b167a1a71d8abca8aa81de4fa918e80f61","observation_id":"4dee1622-d5cf-41e2-bddb-97bef73fec1f","resolution":{"observed_at":"2026-08-16T12:32:26.513001Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.989957Z","title":"3d-gres: Generalized 3d referring expression segmentation,","venue":null,"work_id":"bad08766-f1fa-44a2-bc78-e6a4dc25c73d","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.232754Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:4c0d26fd3142c7dd3488b97a21ee07fba48e7626337c1b7b687165bd7cda33d9","observation_id":"f429324d-37c1-4255-8d44-11ba87365caf","resolution":{"observed_at":"2026-08-16T12:32:26.993490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.980043Z","title":"Refmask3d: Language-guided transformer for 3d referring segmentation,","venue":null,"work_id":"a3f72a37-e636-4f37-9bf6-734bcad6714d","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.236296Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:753888e586301df205285ab1287f8e60d0819bf8fec09373733aa2d0ab47b407","observation_id":"4b4dfd4b-91b3-478b-9399-fb27ca22dcdb","resolution":{"observed_at":"2026-08-16T12:32:26.983565Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.969545Z","title":"Segpoint: Segment any point cloud via large language model,","venue":null,"work_id":"0489ac66-7570-4ef1-80d0-f96bc5445d83","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.239748Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:6c72ce174ca73127ce4c3fa083b0671d104f6c592443317a5651c6d078af1b39","observation_id":"8e34238a-b5b8-4cf3-87aa-d510be40a93f","resolution":{"observed_at":"2026-08-16T12:32:26.973410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.958591Z","title":"3d-stmn: Dependency-driven superpoint-text matching network for end-to-end 3d referring expression segmentation,","venue":null,"work_id":"27d973ca-72ba-47e7-a3b0-718080a5a309","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.242813Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:6d42d1caf57bb7c8d6ac8ded5f2101c0f2834647ab3e713a678ae5f1c8d71094","observation_id":"f9da278d-09b3-40c2-a72f-a09ddfe5d1d7","resolution":{"observed_at":"2026-08-16T12:32:26.962733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.947830Z","title":"Text-guided graph neural networks for referring 3d instance segmentation,","venue":null,"work_id":"aba98289-1d3b-479e-8010-7c99750f25a1","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.246000Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:662577073edf65f1852787d4e13e0ac8fa53e4bd29534451b45ce5b60b1bc830","observation_id":"df7943d9-cd90-46d7-a50c-5df5f04f7002","resolution":{"observed_at":"2026-08-16T12:32:26.951582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.249124Z","title":"Scannet: Richly-annotated 3d reconstructions of indoor scenes,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.249124Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:e3b2da22507a99cf4a5b7618086974fa777b1e4bad065245581894b8a35108e9","observation_id":"079812dc-0070-421c-ad91-9d2183dff509","resolution":{"observed_at":"2026-08-16T12:32:26.249124Z","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":"2026-08-16T12:32:26.929867Z","title":"Referit3d: Neural listeners for fine-grained 3d object identification in real-world scenes,","venue":null,"work_id":"b619586f-6438-4736-afdf-a0906df1ad73","year":2020},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.252199Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:a96e19d59682b9cadafbdb83fc777cf759ccd5e2e401f1ca50c6708d289c5cf5","observation_id":"d2f49eb1-d522-4485-9b16-c0d0273cb340","resolution":{"observed_at":"2026-08-16T12:32:26.933717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.919227Z","title":"Microsoft coco: Common objects in context,","venue":null,"work_id":"1a2e6868-3a2e-4861-b12c-d9c6944e8670","year":2014},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.255339Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:14fb2cbb30862325f4b41e18f0a47b90aee0db78fe8342cb8730160c26a7d2e9","observation_id":"e4940e73-38e9-4412-9099-11428e79feb9","resolution":{"observed_at":"2026-08-16T12:32:26.922785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.258652Z","title":"Imagenet: A large-scale hierarchical image database,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.258652Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:468b14f23b7166ea24187daa25aff1448592a87652db8117eff08ca621fc0a93","observation_id":"4eddd14f-3ec5-41bf-8d81-9f422632c851","resolution":{"observed_at":"2026-08-16T12:32:26.258652Z","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":"2026-08-16T12:32:26.261896Z","title":"The cityscapes dataset for semantic urban scene understanding,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.261896Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:7b15416e208b0f4d9abbbfad8e0074b928b09e462bc97bccad57742b68171443","observation_id":"41090e6a-37b7-4cc9-ac3e-af4f97b8f0d3","resolution":{"observed_at":"2026-08-16T12:32:26.261896Z","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":"2026-08-16T12:32:26.895132Z","title":"Scanrefer: 3d object localization in rgb-d scans using natural language,","venue":null,"work_id":"66ce1014-18e2-43ab-bbb7-b14699118f52","year":2020},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.265364Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:938366d513d3bb22aacce3a5cf42833831e9ca1ecc63a90ad70847c2251ef318","observation_id":"43047fd1-1670-420c-954b-ec1a30098894","resolution":{"observed_at":"2026-08-16T12:32:26.899143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.884285Z","title":"Learning with pseudo- ensembles,","venue":null,"work_id":"78fb8533-1ea1-4bdc-ad9c-e6cd3a5180a9","year":2014},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.268622Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:16401922952da771092b4885888197fee8afdeffd518b2ba18b8d22fbe1f6a2e","observation_id":"8dbe6beb-dc4e-4367-bd56-befbe37c6ebc","resolution":{"observed_at":"2026-08-16T12:32:26.888134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.09785","last_updated":"2020-02-13T23:14:46Z","snapshot_observed_at":"2026-08-12T10:52:49.073310Z","submitted_at":"2019-11-21T23:44:25Z","title":"ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.09785","snapshot_observed_at":"2026-08-16T12:32:26.271803Z","title":"Remixmatch: Semi-supervised learning with distribution alignment and augmentation anchoring,","venue":null,"work_id":null,"year":1911},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.271803Z"},"links":{"cited_paper":"/paper/1911.09785","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:5e2f6f20d9de0244999279e5aab1ce47e3b3e26e67eec10a5e56fa9973b604bd","observation_id":"779565b0-a263-4133-9bc3-f12c5689c20e","resolution":{"observed_at":"2026-08-16T12:32:26.271803Z","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":"2026-08-16T12:32:26.275200Z","title":"Mixmatch: A holistic approach to semi-supervised learning,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.275200Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:6004706ff1a821517c937604840b86e708d50bd5aefd61b1d24897de800f012a","observation_id":"fd0b864d-f1e8-4ab8-b841-462c513d6cb6","resolution":{"observed_at":"2026-08-16T12:32:26.275200Z","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":"2026-08-16T12:32:26.866048Z","title":"Fixmatch: Simplifying semi-supervised learning with consistency and confidence,","venue":null,"work_id":"aa0af530-c229-4262-9fb9-4c8b21215f58","year":2020},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.278269Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:c7997e0eb55dabdc214d6959cb2415d6a2b9c4f6082852e71a0d24d029904891","observation_id":"f61fb15d-3a74-47c0-b64a-67b9d7e6e3f0","resolution":{"observed_at":"2026-08-16T12:32:26.869740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.853522Z","title":"Sspc-net: Semi-supervised semantic 3d point cloud segmentation network,","venue":null,"work_id":"dbd0432d-2bae-46f8-b2e1-a8a843a5fee0","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.281520Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:6206d6def2a564229c2cb706493d5b24c880bf7ded8963da062ad8500043e7c2","observation_id":"312fa1ac-6176-4047-9f43-8318b0cf5cc8","resolution":{"observed_at":"2026-08-16T12:32:26.857234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.843254Z","title":"Sess: Self-ensembling semi- supervised 3d object detection,","venue":null,"work_id":"8177d8fa-1bb3-48b2-a5ab-c6cb1dc985e1","year":2020},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.284606Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:46d7dea03b0ec54297faac381956578b195f08bdce877d479724f59c74964970","observation_id":"073968e5-0dd8-4d3b-84f0-e7b781f68f19","resolution":{"observed_at":"2026-08-16T12:32:26.846829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.832912Z","title":"Active teacher for semi-supervised object detection,","venue":null,"work_id":"d9e2d116-ef5c-4134-9062-784f49232785","year":2022},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.287786Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:ad84e8cc1ebed6b79fb5a19890aa3c09121027f8c2aef38e2a380e1e953860a8","observation_id":"4139387b-df8a-4c72-8f2f-a05dbd7e993a","resolution":{"observed_at":"2026-08-16T12:32:26.836465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.822459Z","title":"Beyond the label itself: Latent labels enhance semi-supervised point cloud panoptic segmentation,","venue":null,"work_id":"09bd8e3c-8db8-41ce-9265-b12ba895ee1e","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.291393Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:d0bb9a1e822ae0d7d236a51d48cd9f7d589986210a5ceadd77c9e13dd9eed56f","observation_id":"b156efd2-bdc4-4c5e-959c-6cdbad3bea54","resolution":{"observed_at":"2026-08-16T12:32:26.826153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.810908Z","title":"Lasermix for semi-supervised lidar semantic segmentation,","venue":null,"work_id":"b3f404e7-de8b-4271-870a-357496ccd84c","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.294652Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:4ce2a5698f324634d6c17aeb15515b261b3c7f0d410e85df99e2e9c6d6da6d88","observation_id":"7fde7a66-be5b-428b-af08-a79c8d07b863","resolution":{"observed_at":"2026-08-16T12:32:26.815078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.799709Z","title":"Hierarchical point-based active learning for semi-supervised point cloud semantic segmentation,","venue":null,"work_id":"32a9adf6-239d-45a9-9e35-d60edfdb196f","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.298038Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:aab98927f4aaad552d4413ab977d7499e3418717e47cb02cfdec0f183e40cb5a","observation_id":"5b63a927-df36-458e-a84f-e5f66662b2c4","resolution":{"observed_at":"2026-08-16T12:32:26.803294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.789014Z","title":"Guided point contrastive learning for semi-supervised point cloud semantic seg- mentation,","venue":null,"work_id":"9946238a-9316-4f3e-89b2-33589b4ce7b7","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.300952Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:851c9aedf857e1d7570504927a5fbaf1667e4b29805a8f443bfc91a578654ba1","observation_id":"1435c955-4f52-4cd0-b170-fdc79b62d136","resolution":{"observed_at":"2026-08-16T12:32:26.792656Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.777604Z","title":"Sdcl: Students discrepancy-informed correction learning for semi-supervised medical image segmentation,","venue":null,"work_id":"510f4436-6424-4c91-a6a0-3532ddc7140f","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.304348Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:7c0f62c9d579092eb0fbbc5fde7740c0bcd5f86c3fc38ea147e2a2ac1c877110","observation_id":"9fac6bf0-567d-46f2-a57d-9e81c02de892","resolution":{"observed_at":"2026-08-16T12:32:26.781328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.765506Z","title":"Data-uncertainty guided multi-phase learning for semi-supervised object detection,","venue":null,"work_id":"4568de06-bfab-4be1-8e74-a16037bf1cef","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.307552Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:9986a02bbc9a33ef5b78fdd8e667ad98081580c385f0af41a29f30742d544df7","observation_id":"2f8704ea-bf3a-4362-9785-91c7ec1902fa","resolution":{"observed_at":"2026-08-16T12:32:26.769266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.754379Z","title":"Consistency-based active learning for object detection,","venue":null,"work_id":"9f920836-458b-4c69-af07-2c60ed877b48","year":2022},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.311051Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:afd5df195f5a18eea26b3564728b51874b64a5c0110d969ca781ea33b4a1730c","observation_id":"22090617-8f1c-4678-91f9-e6f843a01948","resolution":{"observed_at":"2026-08-16T12:32:26.758145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.743088Z","title":"Multiple instance active learning for object detection,","venue":null,"work_id":"9f802aeb-95e8-41b7-b0ce-1c1d7a1c6362","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.314433Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:26017898409ba26c1fe2f87337e4e4da78473bd0a35396e6b816f026e1717b55","observation_id":"34e5af3c-3d9f-40e6-8cf2-ccc77e3ebaab","resolution":{"observed_at":"2026-08-16T12:32:26.746767Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.09428","last_updated":"2025-01-16T09:57:40Z","snapshot_observed_at":"2026-08-13T08:09:52.993146Z","submitted_at":"2025-01-16T09:57:40Z","title":"AugRefer: Advancing 3D Visual Grounding via Cross-Modal Augmentation and Spatial Relation-based Referring","version":1},"cited_work":{"arxiv_id":"2501.09428","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.09428","snapshot_observed_at":"2026-08-16T12:32:26.483708Z","title":"AugRefer: Advancing 3D Visual Grounding via Cross-Modal Augmentation and Spatial Relation-based Referring","venue":"cs.CV","work_id":"3ee9c982-3ff6-4f6f-997b-d06252ad97a8","year":2025},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.318116Z"},"links":{"cited_paper":"/paper/2501.09428","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:2307fdbc9f967fe84dccd42c7f8f7230110bf59b93358ad1ca29335027538ef3","observation_id":"32de10a1-8913-4495-91b0-e8e5d3c9d23a","resolution":{"observed_at":"2026-08-16T12:32:26.487344Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.732551Z","title":"Dense object grounding in 3d scenes,","venue":null,"work_id":"ea304328-2957-4496-89b6-52d64031f815","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.321749Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:84d95f73d1a6fc972874d1f687ecb201ee69275f6ab9ffdc8602dc5564027edc","observation_id":"58d3039c-03bc-494a-aca5-bce9aa4d8d7f","resolution":{"observed_at":"2026-08-16T12:32:26.736090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.721073Z","title":"3d-sps: Single-stage 3d visual grounding via referred point progressive selection,","venue":null,"work_id":"2bf2759f-90e1-401a-853e-86658b5ba95e","year":2022},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.325054Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:78fc6cedcff15b5d6b76955061bab42616ed05c4aef48415b3096ab97488bd37","observation_id":"4312c962-b62b-4cd7-a9f9-fc764e64006e","resolution":{"observed_at":"2026-08-16T12:32:26.725672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.708531Z","title":"Multi3drefer: Grounding text description to multiple 3d objects,","venue":null,"work_id":"45d0543c-61fd-4fe9-8c35-2d255eb1da49","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.328333Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:5fcbce33a2da67029165371f1bad7092381f10f2385ec2ccad4590c5db6856ed","observation_id":"de0d1f27-4f88-445a-b0f2-7a6d3244c4fe","resolution":{"observed_at":"2026-08-16T12:32:26.713049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.697239Z","title":"Language conditioned spatial relation reasoning for 3d object grounding,","venue":null,"work_id":"159cf169-9a39-4f91-a83a-dc26bdb967e6","year":2022},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.331602Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:a49499f79207a8449d2e6b72b39eefee95983404a00f858e305888c905ac8728","observation_id":"ec2feaf5-0daa-4e81-b23c-c2bf67be6455","resolution":{"observed_at":"2026-08-16T12:32:26.701349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.334793Z","title":"Aware visual grounding in 3d scenes,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.334793Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:a169de907c3dbaf7d06754df9df8b356816a24e6e6c05686efe918d03c25daea","observation_id":"7366ae71-79b9-4cd2-8ab1-dcaf91c12827","resolution":{"observed_at":"2026-08-16T12:32:26.334793Z","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":"2026-08-16T12:32:26.677155Z","title":"X-refseg3d: Enhancing referring 3d instance segmentation via structured cross-modal graph neural networks,","venue":null,"work_id":"22b942f3-6bb6-4b3d-884f-bb5cbfc60270","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.338036Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:772b7f0d4af3e87d3d91a20451e772f4771ec5a6904246a17efe0b2e61b8395c","observation_id":"35df36be-3430-49c7-8235-a650c2bd233c","resolution":{"observed_at":"2026-08-16T12:32:26.681690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.663969Z","title":"Pseudo-ris: Distinctive pseudo-supervision generation for referring image segmentation,","venue":null,"work_id":"f743846e-fc24-43f0-8fee-e7f2a0164ee4","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.341301Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:2915c6707443ec411bbfad7ca23bbdafecd14e9b8147bb0235751e3acc5eb9e2","observation_id":"a1b77bf2-fd3f-4238-8b3f-da55c15748aa","resolution":{"observed_at":"2026-08-16T12:32:26.668968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01451","last_updated":"2024-06-03T15:42:30Z","snapshot_observed_at":"2026-08-16T13:46:40.633965Z","submitted_at":"2024-06-03T15:42:30Z","title":"SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01451","snapshot_observed_at":"2026-08-16T12:32:26.344729Z","title":"Sam as the guide: Mastering pseudo-label refinement in semi-supervised referring expression segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.344729Z"},"links":{"cited_paper":"/paper/2406.01451","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:c70a5f7ca809d41338ac480f33ce95f01a71f56e4c4d7331e92d161a2374799b","observation_id":"3cdf8809-b751-495b-836d-9e1bf3913149","resolution":{"observed_at":"2026-08-16T12:32:26.344729Z","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":"2026-08-16T12:32:26.650887Z","title":"Refteacher: A strong baseline for semi-supervised referring expression comprehension,","venue":null,"work_id":"88d46523-1cc6-41c4-a9d5-338f8784a264","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.348420Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:fdd56411b3965bf9de8e50039836ca1d78ba8eeaad195abb24e5bd3c45335097","observation_id":"2f1c5718-02d8-456a-9a8f-5ab07c1345fd","resolution":{"observed_at":"2026-08-16T12:32:26.655375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11768","last_updated":"2023-05-25T04:20:46Z","snapshot_observed_at":"2026-08-16T15:31:40.014748Z","submitted_at":"2023-05-19T15:53:56Z","title":"Generating Visual Spatial Description via Holistic 3D Scene Understanding","version":2},"cited_work":{"arxiv_id":"2305.11768","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.11768","snapshot_observed_at":"2026-08-16T12:32:26.459337Z","title":"Generating Visual Spatial Description via Holistic 3D Scene Understanding","venue":"cs.CV","work_id":"e8a4f974-b9cf-4351-bc29-c27855855507","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.351564Z"},"links":{"cited_paper":"/paper/2305.11768","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:d609233841cd8b2f1dc0369ee4be4bb66798ebb3999af0d16426ab44521b992a","observation_id":"dbd29f08-30c9-4918-bb98-fd3dc98eed38","resolution":{"observed_at":"2026-08-16T12:32:26.463368Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.355012Z","title":"V-net: Fully convolutional neural networks for volumetric medical image segmentation,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.355012Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:2b15c51fd08974cdf7c1e0f44a4957c21110f1f69512b325c6dbe4381617c833","observation_id":"137a1f7d-fa72-40c6-afbd-8025e7cdb4e6","resolution":{"observed_at":"2026-08-16T12:32:26.355012Z","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":"2026-08-16T12:32:26.631333Z","title":"Superpoint transformer for 3d scene instance segmentation,","venue":null,"work_id":"e2bd22e4-1783-4ea8-9109-5bca7df52078","year":2023},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.358431Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:55b50f7036fa8b5b510fdca8335fcc0c406daf929e0dfbc1c26234f913be985c","observation_id":"dabcfcf1-30da-4086-851f-eefcc338f80b","resolution":{"observed_at":"2026-08-16T12:32:26.636066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.361586Z","title":"Unsupervised data augmentation for consistency training,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.361586Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:e30878a3611d7d1438d301c5d4601a2a6275ce0f35bcbeea8cd375e3d7d9997e","observation_id":"1e38dc45-b46e-4fc1-b3e2-d1bab3b99467","resolution":{"observed_at":"2026-08-16T12:32:26.361586Z","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":"2026-08-16T12:32:26.609761Z","title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learn- ing results,","venue":null,"work_id":"cb7ad6b5-8655-42ce-a697-c39a766933ce","year":2017},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.365209Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:e0b880ae8c50a5df4584099a3bdc46ac9b0da62c0d50b52c49dba02801491aa2","observation_id":"e56d988f-8b3c-403b-83f6-eb167a9b8a69","resolution":{"observed_at":"2026-08-16T12:32:26.614746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.594728Z","title":"Adaptive subgradient methods for online learning and stochastic optimization","venue":null,"work_id":"bfa2e184-85d7-4ff4-8fae-41393ecc2629","year":2011},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.368440Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:5a2b16a8b86afae494c1dc4af8a849d52af5e0857b1b27c8b86eeab8a7ddf18b","observation_id":"e2a65550-c0ad-4e96-a844-2a39b866d032","resolution":{"observed_at":"2026-08-16T12:32:26.599560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.18295","last_updated":"2025-02-17T23:10:49Z","snapshot_observed_at":"2026-08-16T13:48:34.074130Z","submitted_at":"2024-05-28T15:48:39Z","title":"Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.18295","snapshot_observed_at":"2026-08-16T12:32:26.371936Z","title":"Intent3d: 3d object detection in rgb-d scans based on human intention,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.371936Z"},"links":{"cited_paper":"/paper/2405.18295","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:92684ae2b43ff28de17428716fb9a9783e1e0280154d14246817dd0f014b364b","observation_id":"828ddd64-6cde-4f6e-8d80-8d640dce5168","resolution":{"observed_at":"2026-08-16T12:32:26.371936Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.00255","last_updated":"2025-02-20T18:06:19Z","snapshot_observed_at":"2026-08-16T13:13:56.200323Z","submitted_at":"2024-09-30T21:55:38Z","title":"Robin3D: Improving 3D Large Language Model via Robust Instruction Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.00255","snapshot_observed_at":"2026-08-16T12:32:26.375734Z","title":"Robin3d: Improving 3d large language model via robust instruction tuning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.375734Z"},"links":{"cited_paper":"/paper/2410.00255","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:b2bb73bf4313e8ee48c78926708d8ce4836c6d5f3e707128782f4dc88583a666","observation_id":"74047c55-2786-4d24-80fc-68d0ec00be40","resolution":{"observed_at":"2026-08-16T12:32:26.375734Z","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":"2026-08-16T12:32:26.581016Z","title":"Virtual reality for health care: a survey,","venue":null,"work_id":"f7b6c4cb-4454-46f5-bd21-c27d2719ba2c","year":1997},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.379121Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:0fddd471ebdcfe79681bd6821c3a0e0c2d3988591d4a9b84dc03dcd87996bd8d","observation_id":"3cf2327c-4d07-471c-ae6a-39c571dadd56","resolution":{"observed_at":"2026-08-16T12:32:26.586012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.568540Z","title":"Social virtual reality: ethical considerations and future directions for an emerging research space,","venue":null,"work_id":"2d07fdf0-e0cd-450f-9c75-5ba809c91c5f","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.382280Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:4c5fb997df0227214622b83793eb06b7c66063413547b86bedf0f7646bebaf47","observation_id":"e9600519-866c-4f94-b75e-1375f368ce24","resolution":{"observed_at":"2026-08-16T12:32:26.572553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.557599Z","title":"A review on human–ai interaction in machine learning and insights for medical applications,","venue":null,"work_id":"ae14a33e-f780-4735-b8e4-e505380fc3f0","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.385517Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:4d39610a2b50e2b298741e52f16fd58f332f7c598865d962368ff28785d3f832","observation_id":"3eedc8f0-51e0-4ae3-95a8-501559c5463f","resolution":{"observed_at":"2026-08-16T12:32:26.561353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T12:32:26.546075Z","title":"A systematic review of human–computer interaction and explainable artificial intelligence in healthcare with artificial intelligence techniques,","venue":null,"work_id":"28c01d6a-ae0d-49f0-b376-9fb8035a7170","year":2021},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.388809Z"},"links":{"citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:8d5d75ac7307747d3b288aedc419baf100be81df0f1a9467430876a23ace91c3","observation_id":"87a194cb-d67c-49a6-9788-04a492994d9d","resolution":{"observed_at":"2026-08-16T12:32:26.550051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.03251","last_updated":"2024-07-06T15:20:26Z","snapshot_observed_at":"2026-08-16T13:37:19.367607Z","submitted_at":"2024-07-03T16:33:31Z","title":"ACTRESS: Active Retraining for Semi-supervised Visual Grounding","version":2},"cited_work":{"arxiv_id":"2407.03251","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.03251","snapshot_observed_at":"2026-08-16T12:32:26.422880Z","title":"ACTRESS: Active Retraining for Semi-supervised Visual Grounding","venue":"cs.CV","work_id":"df8a2d55-3591-40af-814f-22c5ef4c943b","year":2024},"citing_paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-16T12:32:26.392220Z"},"links":{"cited_paper":"/paper/2407.03251","citing_paper":"/paper/2504.12599"},"observation_digest":"sha256:b7352183aa10a6f444e8564bae0e97b18fac3a4f262d9ad6a5705f06d605d104","observation_id":"c5c5c5f9-4eeb-4cda-bf02-6cf2006a3134","resolution":{"observed_at":"2026-08-16T12:32:26.428530Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.12599","last_updated":"2025-04-17T02:50:52Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T04:48:19.326173Z","submitted_at":"2025-04-17T02:50:52Z","title":"3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation"},"reference_resolution":{"displayed":59,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":5,"verified_fuzzy":42},"total_outbound_references":59},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2504.12599."}