{"as_of":"2026-08-09T21:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:290ada4bfa6fda5c85bdcb591ed087d228fc99dd467763790408a939b3fcf315","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T17:07:30.442634Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2607.17778/citation-record","integrity":"/paper/2607.17778/integrity","json":"/paper/2607.17778/citation-record.json","paper":"/paper/2607.17778"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T17:07:29.147668Z","title":"Language-grounded indoor 3d semantic segmentation in the wild,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.147668Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:5e4b30211370f08a4e02141fc1a9097c1f08fa09caee54d6a308f4895e04856c","observation_id":"aa2531ff-f515-430a-ba24-9dffba6784c9","resolution":{"observed_at":"2026-08-01T17:07:29.147668Z","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":"2026-08-01T17:07:29.161963Z","title":"Scannet++: A high- fidelity dataset of 3d indoor scenes,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.161963Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:bb9b2c35ec0cdb33d2463434e2d035d4d4597ad4fb3f92d5bb57cc5b56583c2e","observation_id":"4e8fce61-7537-40aa-863e-253a7bddd248","resolution":{"observed_at":"2026-08-01T17:07:29.161963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1709.06158","last_updated":"2017-09-18T20:34:48Z","snapshot_observed_at":"2026-08-02T16:47:23.623541Z","submitted_at":"2017-09-18T20:34:48Z","title":"Matterport3D: Learning from RGB-D Data in Indoor Environments","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.06158","snapshot_observed_at":"2026-08-01T17:07:29.174064Z","title":"Matterport3d: Learning from rgb-d data in indoor environments,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.174064Z"},"links":{"cited_paper":"/paper/1709.06158","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:ffaa4136066ea3e38cbb30d7dc5108d930da07ab3c12d340ec5370515def5a91","observation_id":"ace97584-13bb-4141-a289-26bbd02a93dd","resolution":{"observed_at":"2026-08-01T17:07:29.174064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.05797","last_updated":"2019-06-13T16:29:58Z","snapshot_observed_at":"2026-08-01T13:51:16.469557Z","submitted_at":"2019-06-13T16:29:58Z","title":"The Replica Dataset: A Digital Replica of Indoor Spaces","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.05797","snapshot_observed_at":"2026-08-01T17:07:29.242979Z","title":"The replica dataset: A digital replica of indoor spaces,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.242979Z"},"links":{"cited_paper":"/paper/1906.05797","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:e08ef677b28b69eed068933421d7219ecbcf0f8be500620817fc87733c76d3d4","observation_id":"3efae66e-df82-4b18-ac12-1d693933e847","resolution":{"observed_at":"2026-08-01T17:07:29.242979Z","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":"2026-08-01T17:07:29.312452Z","title":"Mask3d: Mask transformer for 3d semantic instance segmentation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.312452Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:0ad7f70b51bd385e150e6c5a82d0014d2c73ef83ed9835dd365d8f87a53944f1","observation_id":"d57cd245-7b6a-4aa0-ba15-971293bc89a5","resolution":{"observed_at":"2026-08-01T17:07:29.312452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13631","last_updated":"2023-10-29T14:04:25Z","snapshot_observed_at":"2026-08-05T15:00:57.933479Z","submitted_at":"2023-06-23T17:36:44Z","title":"OpenMask3D: Open-Vocabulary 3D Instance Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.13631","snapshot_observed_at":"2026-08-01T17:07:29.359298Z","title":"Openmask3d: Open-vocabulary 3d instance segmen- tation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.359298Z"},"links":{"cited_paper":"/paper/2306.13631","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:ab6a5993a59d71d221ff4572e3281cea48513b2bb770ecc6f79f5b205af61cab","observation_id":"b8b1db0d-d3b1-41b1-baff-25a9b424b597","resolution":{"observed_at":"2026-08-01T17:07:29.359298Z","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":"2026-08-01T17:07:29.414745Z","title":"Oneformer3d: One transformer for unified point cloud segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.414745Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:0422793f461cb5c9cadd62676087e97ea94790701d7fbfafdf8e4506717299a9","observation_id":"ed6f7097-def6-4432-9336-1d88f4441842","resolution":{"observed_at":"2026-08-01T17:07:29.414745Z","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":"2026-08-01T17:07:29.467872Z","title":"Ovir-3d: Open-vocabulary 3d instance retrieval without training on 3d data,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.467872Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:afbc7ef811f22de2687e6518578f11948deb08e196c1fd8b9c15ce911719f7e3","observation_id":"20fed2fd-84db-45c9-97d3-8633b485b55b","resolution":{"observed_at":"2026-08-01T17:07:29.467872Z","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":"2026-08-01T17:07:29.522809Z","title":"Unscene3d: Unsupervised 3d instance segmentation for indoor scenes,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.522809Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:0a499953c9d7d28cf64d9c9429c881242ae57004897beb548369019177720ce5","observation_id":"a001a221-bcd9-46a6-84ba-7454db6b51ee","resolution":{"observed_at":"2026-08-01T17:07:29.522809Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17707","last_updated":"2025-02-04T11:40:44Z","snapshot_observed_at":"2026-07-06T16:54:26.205948Z","submitted_at":"2023-11-29T15:11:03Z","title":"SAMPro3D: Locating SAM Prompts in 3D for Zero-Shot Instance Segmentation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17707","snapshot_observed_at":"2026-08-01T17:07:29.577628Z","title":"Sampro3d: Locating sam prompts in 3d for zero-shot scene segmentation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.577628Z"},"links":{"cited_paper":"/paper/2311.17707","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:6e6d9a8cd829cd6fcef7c8207f2c6a5b0cb456f06130f6ee45c1f6ddca98dfce","observation_id":"b351c82c-bba0-4306-945a-49ff129bf25d","resolution":{"observed_at":"2026-08-01T17:07:29.577628Z","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":"2026-08-01T17:07:29.629710Z","title":"Maskclustering: View consensus based mask graph clustering for open-vocabulary 3d in- stance segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.629710Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:2015b9a86cc3bb1de248e46c484a53d8173399d9ee875e420d7af8181bdcb603","observation_id":"0bda8482-bd0a-4aaa-b6da-ed2b23972a89","resolution":{"observed_at":"2026-08-01T17:07:29.629710Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03908","last_updated":"2023-06-06T17:59:51Z","snapshot_observed_at":"2026-08-07T21:29:04.973616Z","submitted_at":"2023-06-06T17:59:51Z","title":"SAM3D: Segment Anything in 3D Scenes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03908","snapshot_observed_at":"2026-08-01T17:07:29.670446Z","title":"Sam3d: Segment anything in 3d scenes,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.670446Z"},"links":{"cited_paper":"/paper/2306.03908","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:1ef3bf51908e8bab3eb0b773a4ea54fb5342023f86f4fcca805d114e24ecc48f","observation_id":"2c079c7c-edda-4503-b061-fd3edf0cd172","resolution":{"observed_at":"2026-08-01T17:07:29.670446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.08372","last_updated":"2024-08-02T09:56:14Z","snapshot_observed_at":"2026-08-05T14:31:55.532053Z","submitted_at":"2023-12-13T18:59:58Z","title":"SAM-guided Graph Cut for 3D Instance Segmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.08372","snapshot_observed_at":"2026-08-01T17:07:29.713248Z","title":"Sam-guided graph cut for 3d instance segmentation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.713248Z"},"links":{"cited_paper":"/paper/2312.08372","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:b7fbced25b1df6982b53e6d476db3aa103831eb65bb42fd6028d45892b8be011","observation_id":"01ab8141-3679-49cf-8ab3-46c67b809804","resolution":{"observed_at":"2026-08-01T17:07:29.713248Z","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":"2026-08-01T17:07:29.753597Z","title":"Ov-map: Open- vocabulary zero-shot 3d instance segmentation map for robots,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.753597Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:948526751791602de1c7d511d937449bc2e53a96bac3216c957fb28cd2278fa5","observation_id":"ed6a0604-9c29-4b3d-9463-698beeb0c6b0","resolution":{"observed_at":"2026-08-01T17:07:29.753597Z","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":"2026-08-01T17:07:29.800143Z","title":"Sai3d: Segment any instance in 3d scenes,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.800143Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:59d0d12f1a4f146f8fdef6d15c5d10eeeaf8be60116bbb480cfdc17fd1527a75","observation_id":"817b63cf-795b-4d5f-b61f-2e82fa162c68","resolution":{"observed_at":"2026-08-01T17:07:29.800143Z","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":"2026-08-01T17:07:29.851591Z","title":"Open3dis: Open-vocabulary 3d instance segmentation with 2d mask guidance,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.851591Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:ccc2c73f1015c5c1cf817dcbf323c996487200a3a027e22a5c8f003e1e874459","observation_id":"6b72f020-e027-4866-ae61-ff45951f0bb0","resolution":{"observed_at":"2026-08-01T17:07:29.851591Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17232","last_updated":"2023-12-28T18:57:11Z","snapshot_observed_at":"2026-08-07T09:50:05.585840Z","submitted_at":"2023-12-28T18:57:11Z","title":"Segment3D: Learning Fine-Grained Class-Agnostic 3D Segmentation without Manual Labels","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.17232","snapshot_observed_at":"2026-08-01T17:07:29.905195Z","title":"Segment3d: Learning fine-grained class-agnostic 3d segmentation without manual labels,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.905195Z"},"links":{"cited_paper":"/paper/2312.17232","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:246759d50cdb062b38a5077711df21dd6c7af9160f56353a8b6cb4fbd6895caa","observation_id":"081602f3-86e0-41bb-948e-bb5973e5bcda","resolution":{"observed_at":"2026-08-01T17:07:29.905195Z","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":"2026-08-01T17:07:29.960465Z","title":"Openins3d: Snap and lookup for 3d open-vocabulary instance seg- mentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:29.960465Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:fac3fbea5d69f0d963becbc2f946178579d9c6000505be818ade00f473bf93bf","observation_id":"8237fc55-8ed5-4521-8d23-5f5128cb5366","resolution":{"observed_at":"2026-08-01T17:07:29.960465Z","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":"2026-08-01T17:07:30.008018Z","title":"Per-pixel classification is not all you need for semantic segmentation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.008018Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:f49ffc866dd213cdc747eafbb3724786dd236d36f8d9c8a854bc16a8367646f0","observation_id":"1606e098-4894-4e28-9fa1-1b3848ca3b85","resolution":{"observed_at":"2026-08-01T17:07:30.008018Z","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":"2026-08-01T17:07:30.054014Z","title":"Masked-attention mask transformer for universal image segmenta- tion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.054014Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:c2a754fc78888735f600502507bc902eeb47a6567ea0194549f6ee505391f594","observation_id":"7af0457c-2c4c-4408-bd8e-3dd5727c00ab","resolution":{"observed_at":"2026-08-01T17:07:30.054014Z","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":"2026-08-01T17:07:30.108169Z","title":"Segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.108169Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:20fda700a57cc39ff55e29a04e299fd1ed04012fd519df67c61365587d72a953","observation_id":"53f7601c-3568-47d2-87e9-612f3e5d66fd","resolution":{"observed_at":"2026-08-01T17:07:30.108169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.05776","last_updated":"2023-04-02T22:01:17Z","snapshot_observed_at":"2026-07-31T08:06:57.921225Z","submitted_at":"2022-11-10T18:58:22Z","title":"High-Quality Entity Segmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.05776","snapshot_observed_at":"2026-08-01T17:07:30.148667Z","title":"High-quality entity segmentation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.148667Z"},"links":{"cited_paper":"/paper/2211.05776","citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:34ea90d3c7148f172186a6794b4bcaf38335936f61080ea2d62fd620f60e31a0","observation_id":"be16dbe2-da42-4813-9ffe-366c1ac7125f","resolution":{"observed_at":"2026-08-01T17:07:30.148667Z","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":"2026-08-01T17:07:30.202535Z","title":"DA-Fusion: De- formable attention-based rgb-d fusion transformer for unseen object instance segmentation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.202535Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:b579e0930a7c172bc5ec61f260b8ef087eaf783eb4d7709de0d5db412ea2885a","observation_id":"46e98e9b-c3f2-4c39-b6a3-03eb1b4cc4a1","resolution":{"observed_at":"2026-08-01T17:07:30.202535Z","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":"2026-08-01T17:07:30.256697Z","title":"3d-sis: 3d semantic instance segmen- tation of rgb-d scans,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.256697Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:f294005bc859bf03fb86cb5e9ae166fc9d0ddf897ac90e4c963726fcfa82c50f","observation_id":"75352f94-42ec-401a-95f9-b88b10329f57","resolution":{"observed_at":"2026-08-01T17:07:30.256697Z","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":"2026-08-01T17:07:30.300579Z","title":"Isbnet: a 3d point cloud instance segmentation network with instance-aware sampling and box-aware dynamic convolution,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.300579Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:474272c9382adea4218b19716a93a8e78736b7bfb66387d5f70971a67400b044","observation_id":"8a88addd-8e57-4f78-ba10-3eb16aecca4f","resolution":{"observed_at":"2026-08-01T17:07:30.300579Z","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":"2026-08-01T17:07:30.350638Z","title":"Efficient graph-based image segmentation,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.350638Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:255651bf9a5bfdd2bb6fb74273a133eae51049ad8a4b8437ee4d70fef6681f91","observation_id":"72fe1c37-38bc-4e20-b5e6-fed0553fa4a1","resolution":{"observed_at":"2026-08-01T17:07:30.350638Z","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":"2026-08-01T17:07:30.402692Z","title":"Rtab-map as an open-source lidar and visual simultaneous localization and mapping library for large-scale and long-term online operation,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.402692Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:7a0ce9fec7c8abe1a8bf688a582175557b49bb0bfbfab764212330a378ca05d7","observation_id":"dda33aac-1832-44fa-a7b8-ed720eba5dab","resolution":{"observed_at":"2026-08-01T17:07:30.402692Z","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":"2026-08-01T17:07:30.442634Z","title":"Kinectfusion: Real-time dense surface mapping and tracking,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T17:07:30.442634Z"},"links":{"citing_paper":"/paper/2607.17778"},"observation_digest":"sha256:54fe56c3cbf815ca626747ff1253a926679673e2708bbfd8ebc3681b82a43fc1","observation_id":"3a893a57-a799-4880-88fb-9e60bc47ca37","resolution":{"observed_at":"2026-08-01T17:07:30.442634Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.17778","last_updated":"2026-07-20T10:09:12Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T08:45:10.477832Z","submitted_at":"2026-07-20T10:09:12Z","title":"CDIS: Cross-Dimensional Class-Agnostic 3D Instance Segmentation via 2D Mask Tracking and 3D-2D Projection Merging"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":28,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":28},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.17778."}