{"as_of":"2026-08-11T13:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b3d42e58b77e68ad5d0075fceaa249a930bc1795be4dc86be0e1955af6ccb685","coverage":[{"denominator":56,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T22:19:18.217283Z","state":"measured"},{"denominator":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2501.18851/citation-record","integrity":"/paper/2501.18851/integrity","json":"/paper/2501.18851/citation-record.json","paper":"/paper/2501.18851"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:19:18.855240Z","title":"Neurocomputing 493, 626–646 (2022)","venue":null,"work_id":"5888918a-46c2-454f-8444-c469fc0bf90d","year":2022},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.964004Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:a94b75b8a3a7f77dc80bc2a6658d98ddf664b8d19b9fc86a45f8f07ec59425d2","observation_id":"fcf596e7-eee8-4dcf-b4b9-21a291fb29d2","resolution":{"observed_at":"2026-08-09T22:19:18.858941Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.843971Z","title":"In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"61745815-7ae4-4681-8a7d-59bc03357c17","year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.968075Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:e119d8a1a9ebabebc1b0a58a6e1d9ea30c24d43356c3971bab63a2ad3c052047","observation_id":"76eb76b2-0e67-495c-9199-f68da49d6315","resolution":{"observed_at":"2026-08-09T22:19:18.847610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-10T22:24:05.831832Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-09T22:19:17.971858Z","title":"arXiv preprint arXiv:1409.1556 (2014)","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.971858Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:3384b778b567e44b20d45fc53f8efa970a2daad3eaf17423eb0b4d3e5c935da7","observation_id":"db60c79b-9466-4853-a84c-948aa4bd01e9","resolution":{"observed_at":"2026-08-09T22:19:17.971858Z","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":"2026-08-09T22:19:17.976286Z","title":"In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.976286Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:0583e941c499efc7025e804bd1b1ad654e7e0631307f396eed2bee24bea1820f","observation_id":"2faa28b0-475f-4323-a571-f0c01fbe9b21","resolution":{"observed_at":"2026-08-09T22:19:17.976286Z","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":"2026-08-09T22:19:18.827012Z","title":"In: Pro- ceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"9765cadf-abb6-4c12-b3d7-5b2abed8acd6","year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.979978Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:f5dc898ca7a1d59be205505b1fbdc4d084ce9a582ce7b6f86eaa1add2075ae55","observation_id":"96bf86d0-0a53-4a11-bfab-b9f5c74fb634","resolution":{"observed_at":"2026-08-09T22:19:18.831035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.815980Z","title":"In: European Conference on Computer Vision, pp","venue":null,"work_id":"8b45ced1-0c12-4408-b078-bd7398eddebd","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.983629Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:67a9df12fb7867b6ee3e72c72a91844a8bfab79c7f25656de81e7ed86da5ca0c","observation_id":"2b188582-fc26-4b14-9a3b-4c3adad30d9e","resolution":{"observed_at":"2026-08-09T22:19:18.819950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.805038Z","title":"In: Proceedings of the AAAI Conference on Artificial Intelligence, vol","venue":null,"work_id":"026264f5-1b2c-480f-898a-2e9bd2c1c164","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.987479Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:aceeb738c1985557743967f10ab23f54ea502e37eb3dbc3cefc69e363fb1fec5","observation_id":"07884825-61f5-4272-9bc3-b0f62df6f0f4","resolution":{"observed_at":"2026-08-09T22:19:18.808809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:17.991002Z","title":"In: European Conference on Computer Vision, pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.991002Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:391a88e7f09d06aa8ae56920183eb492ba8011485bee1f187f55c4fe75aeb790","observation_id":"9156ac84-79dc-4918-af50-c85f11e033c2","resolution":{"observed_at":"2026-08-09T22:19:17.991002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-10T01:12:16.468283Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-09T22:19:17.994406Z","title":"arXiv preprint arXiv:2010.11929 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:17.994406Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:e122889d3ec7f6fa7e81d1deea091f1d0ca328f5952f1b4196d1cc97f11bf65c","observation_id":"78b00939-9b49-4ca1-855b-13ae86012007","resolution":{"observed_at":"2026-08-09T22:19:17.994406Z","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":"2026-08-09T22:19:18.787077Z","title":"Displays 70, 102080 (2021) 21","venue":null,"work_id":"317ad9b8-c58b-4f55-9e35-0acb99ccdceb","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.000201Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:d7816902db05521c74bf9b30f0b0f667bdfbf417ceec12a68b189898d8352d3c","observation_id":"633c77d3-857b-444b-be0d-1ae1a2ff1c5b","resolution":{"observed_at":"2026-08-09T22:19:18.790967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.775429Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"b2956fce-4174-426d-8f43-b1edfeb58600","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.006845Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:c3d02503c690eaae2f5fd9bd83978d6c03cf5f12f42e3151ed26479345e98d90","observation_id":"61358f79-dcec-44b8-9995-69530c9774f6","resolution":{"observed_at":"2026-08-09T22:19:18.779365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.764149Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"5f9ad5e9-aba2-4d5c-bdc1-22e72ac8cbd8","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.015473Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:ec1bebe0a087261d6e64daf1b1da5f74f1f919845b23249a5635c0b3f52aa410","observation_id":"ee956f32-c1c3-48dc-bdb6-4dcdff34c950","resolution":{"observed_at":"2026-08-09T22:19:18.767874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.753215Z","title":"In: International Conference on Image and Graphics, pp","venue":null,"work_id":"87c43689-0de2-4303-b9fa-6c6de21cd222","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.024757Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:b4f3053b0c316ad0f4b26123a1f5baa82d7427866b8085457096473af89f7498","observation_id":"59fbd46c-65a8-4509-9d13-de003f4f347b","resolution":{"observed_at":"2026-08-09T22:19:18.756983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.742354Z","title":"In: Proceedings of the AAAI Conference on Artificial Intelligence, vol","venue":null,"work_id":"28b39cb2-852b-4c8b-b69f-28712b13c41d","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.034753Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:3fc930d0ca5a2cfd1d0e5da9c6f6c18b237d5276d0d6e4af6963c06cc65d0590","observation_id":"c818dd64-aea7-4cf3-a5b2-9a5d66c3c844","resolution":{"observed_at":"2026-08-09T22:19:18.746219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.730813Z","title":"In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"6717e375-7c92-4093-b270-218177598783","year":2015},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.048521Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:d5a932491f64f67eab4e1a1c85a550dd0da035811129b79e97c6513cb0f0c8e1","observation_id":"dc8ffbae-ba61-4037-b06f-abe180ce1772","resolution":{"observed_at":"2026-08-09T22:19:18.734769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.052141Z","title":"In: International Conference on Medical Image Computing and Computer-assisted Intervention, pp","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.052141Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:2a06d8cc77630d2b128468b8bb8a3128610bf689c0245a3ecdf47d8ed48e943f","observation_id":"14fe8293-242b-4bd2-9c95-79f3aa686750","resolution":{"observed_at":"2026-08-09T22:19:18.052141Z","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":"2026-08-09T22:19:18.712160Z","title":"IEEE transactions on pattern analysis and machine intelligence 40(4), 834–848 (2017)","venue":null,"work_id":"937f0036-3e85-4981-b91c-27a3ee5c0f0d","year":2017},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.055621Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:5096de540c2cbc278d1e7fd1a6c3aa558401205ba3ba86b37226af4979c92662","observation_id":"ca9b60ea-a3f8-49a0-a520-09103169f3e9","resolution":{"observed_at":"2026-08-09T22:19:18.716859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.701094Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"083b2b92-6380-4f93-ab38-89ce0df952b0","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.059165Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:44050c2d5616bfcd39fd91f34fc22622e8544b26bddbf11f19ea9d7229626235","observation_id":"7f5ef267-338c-4d56-9e2d-7800aa5316f9","resolution":{"observed_at":"2026-08-09T22:19:18.705283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.690091Z","title":"CVPR (2018)","venue":null,"work_id":"418e2901-c473-4ceb-b014-c9b9a02ebb15","year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.062844Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:7384231db1e6b8caed7befb203f789da2d35769aaa145a8f81029e48bdd0e4dc","observation_id":"64d795f3-56e3-4dca-bf55-77ec3fc5cc03","resolution":{"observed_at":"2026-08-09T22:19:18.694006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.678346Z","title":"In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"dedfaa05-5307-4113-855d-f1d1727c0270","year":2019},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.066423Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:359c9f9ae004c8be24d65988eb8e568ff5df502a10f7cf4167ce369d846acfa9","observation_id":"f345e6ed-fd40-4815-92f4-f7200ca9890b","resolution":{"observed_at":"2026-08-09T22:19:18.682801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.667227Z","title":null,"venue":null,"work_id":"9b30077a-ea7e-4c26-965f-a17a5be1ff7a","year":2019},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.070589Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:a21ca99ee03609489e4460ef7809df2d6c2597034c1555916523da3b243b9e8e","observation_id":"25e53731-4408-49c8-a382-ae5bf6fbbd7a","resolution":{"observed_at":"2026-08-09T22:19:18.671120Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.656350Z","title":"Image and Vision Computing 105, 22 104042 (2021)","venue":null,"work_id":"615ae327-6971-4321-91e2-5adc7572154c","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.074193Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:c81c48c0f9c3b5ae8d4d4c214f1a89b99f22637a28d5dc705903ca20aeb0f824","observation_id":"0b9d7520-c4c8-4344-83d2-b86e8725b5b9","resolution":{"observed_at":"2026-08-09T22:19:18.660051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.645418Z","title":"Neurocomputing 462, 568–580 (2021)","venue":null,"work_id":"beb7bbb7-ab77-4514-bf7b-d51e22744deb","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.078290Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:457d9624fe410a9b8dfc54fb94e32e82b434074eff5bed945cef43d2359066bc","observation_id":"15dd2f25-1a69-405f-929d-05ea7993dccd","resolution":{"observed_at":"2026-08-09T22:19:18.649207Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.635103Z","title":"In: Asian Confer- ence on Computer Vision, pp","venue":null,"work_id":"53095701-3160-4f3d-bc81-5f4782c76e42","year":2016},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.082444Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:c40c6186ca05613309314eb3b9e7d58eb45ed12f91ffc750193157818e4cd0d8","observation_id":"20cc6f8a-c81f-4f2f-aa22-d44197183641","resolution":{"observed_at":"2026-08-09T22:19:18.638976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.624434Z","title":"In: Proceedings of the IEEE International Conference on Computer Vision, pp","venue":null,"work_id":"c059d38f-7f71-435f-89cb-bd40ccce8481","year":2017},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.086647Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:5d5d26be1088e575890e21d2b291fe9360107fdfea79e3753ec6fef74a410476","observation_id":"892e83cf-0d96-4529-8a22-6ef8c7b895ae","resolution":{"observed_at":"2026-08-09T22:19:18.628399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.613588Z","title":"In: Proceed- ings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"9e5e91d7-1302-465b-9de1-07752b81b7b0","year":2017},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.091560Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:8b51b8dea6a20191254ffb2416ab82311a2fafa0e10366a9a4450d609f8e1975","observation_id":"5f8ebc55-c178-48d9-bb6c-d1ca852b0798","resolution":{"observed_at":"2026-08-09T22:19:18.617477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.602736Z","title":"Advances in Neural Information Processing Systems 33, 4835–4845 (2020)","venue":null,"work_id":"0bb80e1a-6975-4a15-a47a-afd70463abda","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.095522Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:2a1c6d82fc3f39cb546c9816ffdca3ec52ace0b8794ffcaf910acdbaf9ad034b","observation_id":"dda6c1b0-e77a-4273-a3c1-1acad1267793","resolution":{"observed_at":"2026-08-09T22:19:18.606743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.10801","last_updated":"2021-01-26T14:26:07Z","snapshot_observed_at":"2026-08-10T10:39:07.423316Z","submitted_at":"2021-01-26T14:26:07Z","title":"Global-Local Propagation Network for RGB-D Semantic Segmentation","version":1},"cited_work":{"arxiv_id":"2101.10801","doi":null,"metadata_source":"pith","pith_arxiv_id":"2101.10801","snapshot_observed_at":"2026-08-09T22:19:18.279853Z","title":"Global-Local Propagation Network for RGB-D Semantic Segmentation","venue":"cs.CV","work_id":"a2649385-45b2-4aa4-b2ab-611868dba8c6","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.099400Z"},"links":{"cited_paper":"/paper/2101.10801","citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:bb5083f4e52f81c24feccdc391d6254f0689c489498f1c73ad7e505fa3494855","observation_id":"33d95018-647f-4ab5-a16f-ce203868b108","resolution":{"observed_at":"2026-08-09T22:19:18.285906Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.591777Z","title":"In: Proceed- ings of the European Conference on Computer Vision (ECCV), pp","venue":null,"work_id":"1bc36247-ac97-4440-97a2-1342a1b7cfb7","year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.104755Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:732939b756b4b273866c501c260731dfa80681b7a3c7a926948a98ea5c7e6ba0","observation_id":"f88f4cd5-c076-4aca-9774-f3da786fa371","resolution":{"observed_at":"2026-08-09T22:19:18.595372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.580537Z","title":"In: European Conference on Computer Vision, pp","venue":null,"work_id":"509a95f5-b558-418e-bd78-c53d3c498de9","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.108760Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:5f36e5f786987eb412969f8fc4e496f9288927ec644119c7a7cf6a124660a5d3","observation_id":"8e9cd522-1b4f-443d-934a-7739f5c31ec8","resolution":{"observed_at":"2026-08-09T22:19:18.584569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.569242Z","title":"In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp","venue":null,"work_id":"072d02f9-1743-4c88-95e1-7fc218bf97ce","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.112535Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:4748d81970853cc10ec58c7f0bfdf883aea4c4e6208b910efdf847317d04bdd3","observation_id":"20af9cf5-83b9-45cc-8689-0d1012b7e5a7","resolution":{"observed_at":"2026-08-09T22:19:18.573239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.553351Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"46cde49a-11aa-4d67-8902-9793aef336ce","year":2019},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.116253Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:3e8c347c845961afb5953c9f96c47f5a2a4ad31efaee2c0e9e66249780d5f661","observation_id":"75307e52-37a1-4cb9-a747-a83b8bf10cae","resolution":{"observed_at":"2026-08-09T22:19:18.557166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.541792Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"ff7e58e6-5d51-4dc9-afd3-6f5055e5cbda","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.119972Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:f7e64d48f9c2e9e1a26570f60c34a02132a0d4bd0dd0d8a3c30a589f7e6abeb1","observation_id":"9fae59ad-35a2-4164-8f1c-438c93d55355","resolution":{"observed_at":"2026-08-09T22:19:18.545761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.04838","last_updated":"2023-11-24T16:29:19Z","snapshot_observed_at":"2026-08-10T07:41:02.008144Z","submitted_at":"2022-03-09T16:12:08Z","title":"CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.04838","snapshot_observed_at":"2026-08-09T22:19:18.124005Z","title":"arXiv preprint arXiv:2203.04838 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.124005Z"},"links":{"cited_paper":"/paper/2203.04838","citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:ae1295f086fe21f2e3fbde48fac8104f68f9d2deb19c4eb61721fe61c5eb031b","observation_id":"5c6b0987-0a36-431e-b22a-0d3ba79b8a23","resolution":{"observed_at":"2026-08-09T22:19:18.124005Z","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":"2026-08-09T22:19:18.530519Z","title":"Pattern Recognition129, 108708 (2022)","venue":null,"work_id":"2a9b64c3-d929-4efd-8ff1-9ba05c7223e8","year":2022},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.128445Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:632da5bc75a9e3a2c86169c82128330eae7f63ce29e90774ad9bd65d2236c728","observation_id":"50a38ecf-8a62-44a8-91fe-9e74f4c4754c","resolution":{"observed_at":"2026-08-09T22:19:18.534386Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.519964Z","title":"In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp","venue":null,"work_id":"bbc34d52-79e3-482a-a5b7-ed492aad1caf","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.132683Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:1db62bcfb3f14a04655adede9abba6710670954d6da8ed15240d4835cfe7738c","observation_id":"177f50ad-ad3d-482b-ae8e-900737209113","resolution":{"observed_at":"2026-08-09T22:19:18.523786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.508398Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"78904855-34a9-4f6f-93ad-ba9980592e2c","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.137197Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:c863dda7046f6e1759ba17a51fa901534b6e134dd5b4e879615e918774af3d46","observation_id":"242bc2f1-56a7-4161-a699-c0e205b91832","resolution":{"observed_at":"2026-08-09T22:19:18.512467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.496900Z","title":"In: Proceedings of the AAAI Conference on Artificial Intelligence, vol","venue":null,"work_id":"b2925278-f615-41b7-a072-90e1fea1053f","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.141427Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:6f83fa9c0b3f3d222c08ace35e5b3814d80fe0ad8ca84b32cf59e012db34963f","observation_id":"63cbeef3-2ea9-4ae3-ae24-684c6d610e95","resolution":{"observed_at":"2026-08-09T22:19:18.500633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.485352Z","title":"In: Proceedings of the IEEE International Conference on Computer Vision, pp","venue":null,"work_id":"417ed896-8868-4050-9abf-40485d09745c","year":2017},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.145874Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:8e8e2736609b2d2dc85649439ebc4e52c11e5e2f60b069c8d6a3916e475955cb","observation_id":"0afa69bf-ca7f-4e67-9135-5789f992874a","resolution":{"observed_at":"2026-08-09T22:19:18.489316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.474415Z","title":"In: 2019 International Conference on 3D Vision (3DV), pp","venue":null,"work_id":"35648edd-df1f-4ff0-bd8b-36dd9e5de8cc","year":2019},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.150005Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:b01cc2cce6081d647879d8f201ab7830024b4c598f03eb0b03e0167750d5ed82","observation_id":"aa2012f4-0272-42c5-a5d5-4f13da67c73f","resolution":{"observed_at":"2026-08-09T22:19:18.478243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.463595Z","title":"Advances in Neural Information Processing Systems 31 (2018)","venue":null,"work_id":"b6b3d4ed-2dc4-4feb-b015-a170e4ee0ed6","year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.154350Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:63eda47ff4cb6e6229ea9ce0cc7501061663da1fb964ed2e9dc3212d055a79fc","observation_id":"111c329a-1627-4965-a989-e71a2d0123f5","resolution":{"observed_at":"2026-08-09T22:19:18.467404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.453190Z","title":"Advances in Neural Information Processing Systems 31 (2018)","venue":null,"work_id":"1c1c52fd-4f03-4c2a-adfd-98f93bdeef17","year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.158468Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:6ae8717a11296d15c8dec039ed4e9d368068ce7ed2be7042b1cdf81d9a2ffbd3","observation_id":"9bfc166f-358c-4986-b81e-b23353cc007b","resolution":{"observed_at":"2026-08-09T22:19:18.456929Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.442567Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"3db302ad-9893-44e4-9eca-29e5ff6010ff","year":2019},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.162601Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:1cb4d4c711c3a9cf204aec8a567a3a0ddbd17d8b7e67e1438bf1251a4f054f39","observation_id":"31ac7d1f-94ca-45de-99a9-0a6b12e6d0f8","resolution":{"observed_at":"2026-08-09T22:19:18.446418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-09T22:19:18.166647Z","title":"arXiv preprint arXiv:1609.02907 (2016)","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.166647Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:bc87145203086d9b410153f318f66aacb9089a900e6e29d36e443796c294ad70","observation_id":"f61a1a51-8411-4463-b554-cb598e436608","resolution":{"observed_at":"2026-08-09T22:19:18.166647Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.00272","last_updated":"2022-11-04T14:45:03Z","snapshot_observed_at":"2026-07-06T13:16:13.214340Z","submitted_at":"2022-06-01T07:01:04Z","title":"Vision GNN: An Image is Worth Graph of Nodes","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.00272","snapshot_observed_at":"2026-08-09T22:19:18.171751Z","title":"arXiv preprint arXiv:2206.00272 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.171751Z"},"links":{"cited_paper":"/paper/2206.00272","citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:8737fc986eca044a8cd572062d969c41e3205a622ee71750d80bd89fb081660a","observation_id":"dddfbf49-3e90-42ff-a37e-db061cbf1889","resolution":{"observed_at":"2026-08-09T22:19:18.171751Z","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":"2026-08-09T22:19:18.432188Z","title":"In: Proceedings of the ACM Web Conference 2022, pp","venue":null,"work_id":"19dba301-07f5-48c6-988f-4d0dd893a93b","year":2022},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.177157Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:1de60e93b13f4f4fa8647f94a3f7257b3f6d7e2eda70615e64594cda118d9611","observation_id":"f561f71a-dc8d-4eae-9a31-ee0d3a2c2081","resolution":{"observed_at":"2026-08-09T22:19:18.435775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.421185Z","title":"In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"e902aae1-ebbf-4d70-b375-0c5b8ce141ca","year":2018},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.181417Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:15424a797c54ff4cfd793b5d4fd2b2b3ccf6f4fbbfc9f2b01cbf6cd0087a575f","observation_id":"6aa9af23-34dd-4349-b013-7d4344aebc97","resolution":{"observed_at":"2026-08-09T22:19:18.425128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.409045Z","title":"In: IEEE International Conference on Image Processing, pp","venue":null,"work_id":"6e03b557-63b8-4531-9f58-c33695e4b247","year":2019},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.185510Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:4fdb1654b4238ee01b2ff8b2a5f1f4c2744e78b410b6ac4c9ac711a95c75acb8","observation_id":"7b96c5cc-bcc5-428d-b541-a0da3fb972b2","resolution":{"observed_at":"2026-08-09T22:19:18.413208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.396884Z","title":"In: European Conference on Computer Vision, pp","venue":null,"work_id":"dc2049ae-29a6-4d7e-bacf-b026db9ab293","year":2020},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.189618Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:4118c8d1aa4571ada82218568c1b0dc47684d9bcaf517faf59dadec2347cf645","observation_id":"32e25b09-0365-4bbc-acee-934c0a5bcf68","resolution":{"observed_at":"2026-08-09T22:19:18.401572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.385587Z","title":"In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"98f27c89-b8bb-4d0c-8016-27ab08002356","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.193387Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:ce2edba5693a808757893d2c07ccd322aa7a89af9f64009af11e7cb0a620f6d6","observation_id":"b2e2c750-c764-4f1c-8020-0e42b8d89edb","resolution":{"observed_at":"2026-08-09T22:19:18.389552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.373435Z","title":"Pattern Recognition 124, 108468 (2022)","venue":null,"work_id":"85796e2f-5e54-4f58-9c99-4d4903de1fd8","year":2022},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.197300Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:eff09e18ff9996c9253d993429c44ead7e9100ff7719a0f6aff2d5b59fe8fe90","observation_id":"5eb32d81-f6ac-47dc-8867-0e5d6c5f9aef","resolution":{"observed_at":"2026-08-09T22:19:18.377543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.361377Z","title":"In: European Conference on Computer Vision, pp","venue":null,"work_id":"80194e5f-0a3e-44de-89ef-5b4ae1974d94","year":2012},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.201173Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:aee9bb760f9f1dc1968441d465c6a58dda7823b5652c172b6cbc803b82ba361f","observation_id":"44647db4-f0f2-4e16-a67b-e39daf1b2975","resolution":{"observed_at":"2026-08-09T22:19:18.365335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.349625Z","title":"In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":"dea61c67-62d5-4ce0-bdb4-d3423591b429","year":2015},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.205181Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:12c2890ed7917425355897709180ea40a8467d35396ed5c6292ac7d105b2fb96","observation_id":"52ef494a-c028-4296-ac7e-85546e6ee7c1","resolution":{"observed_at":"2026-08-09T22:19:18.353753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.337799Z","title":"In: Consumer Depth Cameras for Computer Vision, pp","venue":null,"work_id":"2c2fc403-d509-4d22-98ea-2b79b468118e","year":2013},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.209095Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:a3af5dfbe4aa1c05710e5a50a5ba43d73fd266de54787593954f4b1ca85e997a","observation_id":"0e73cd73-eb1b-418b-af9b-aafe9b34405e","resolution":{"observed_at":"2026-08-09T22:19:18.341877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.325997Z","title":"In: Proceedings of the IEEE International Conference on Computer Vision, pp","venue":null,"work_id":"28e5d6a3-7384-4117-b911-6c6ab1bd7f4c","year":2013},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.212747Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:6b7c6e17abff666b099d8e67f93a8d8021a72335c03b433d444789b790267d0f","observation_id":"ff7b1edf-9edf-4b24-91ff-daa658f4953f","resolution":{"observed_at":"2026-08-09T22:19:18.329986Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-09T22:19:18.314759Z","title":"In: 2021 IEEE Interna- tional Conference on Robotics and Automation (ICRA), pp","venue":null,"work_id":"787403d1-63f5-40be-be33-9a29ea7aafaa","year":2021},"citing_paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-09T22:19:18.217283Z"},"links":{"citing_paper":"/paper/2501.18851"},"observation_digest":"sha256:1778196e413a8eba91ce8f735d6235e5a0b3e54e7dccebae5a5ae42d2500dbd6","observation_id":"99489387-cfc6-430b-926a-626754e8274d","resolution":{"observed_at":"2026-08-09T22:19:18.318502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.18851","last_updated":"2025-05-02T15:52:03Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T03:37:06.074601Z","submitted_at":"2025-01-31T02:24:13Z","title":"Project-and-Fuse: Improving RGB-D Semantic Segmentation via Graph Convolution Networks"},"reference_resolution":{"displayed":56,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":46},"total_outbound_references":56},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2501.18851."}