{"as_of":"2026-08-08T23:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8894bbcb50573162bd8a8cc1d2b905d69e1238b6cec3ca0232951a79433e0e3b","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T07:04:35.697412Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-15T13:52:01.152288Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-15T13:55:53.207763Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"cited_work":{"arxiv_id":"2601.21291","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2601.21291","snapshot_observed_at":"2026-07-01T02:16:56.703294Z","title":"Gaussian belief propagation network for depth completion","venue":null,"work_id":"051a8492-97c0-497b-9403-6b6664bb325e","year":2026},"citing_paper":{"arxiv_id":"2603.10584","last_updated":"2026-05-02T12:44:50Z","snapshot_observed_at":"2026-07-06T22:48:39.649787Z","submitted_at":"2026-03-11T09:40:03Z","title":"Need for Speed: Zero-Shot Depth Completion with Single-Step Diffusion","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-15T13:52:01.152288Z"},"links":{"cited_paper":"/paper/2601.21291","citing_paper":"/paper/2603.10584"},"observation_digest":"sha256:ab9e0c2983b856e991504e7017db3277ed4c3d0b88b635095c4e285d409f5a87","observation_id":"d8faea71-501d-4290-8ee5-82580c52b2e7","resolution":{"observed_at":"2026-07-01T02:16:56.703294Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2601.21291/citation-record","integrity":"/paper/2601.21291/integrity","json":"/paper/2601.21291/citation-record.json","paper":"/paper/2601.21291"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"0811.2518","last_updated":"2009-07-12T10:39:59Z","snapshot_observed_at":"2026-07-06T01:47:40.415467Z","submitted_at":"2008-11-15T18:37:36Z","title":"Gaussian Belief Propagation: Theory and Aplication","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"0811.2518","snapshot_observed_at":"2026-08-03T07:04:35.625895Z","title":"Gaussian belief propagation: Theory and aplication.arXiv preprint arXiv:0811.2518,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.625895Z"},"links":{"cited_paper":"/paper/0811.2518","citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:a77a89177fa39fc2be8b88eeae5c45ad669fb8fd1a55c74ee40d8cefa9e33c31","observation_id":"44cdcb82-72b8-4d41-8780-4a7cc498c6fb","resolution":{"observed_at":"2026-08-03T07:04:35.625895Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1301.6725","last_updated":"2013-01-23T16:00:02Z","snapshot_observed_at":"2026-08-06T07:12:47.346426Z","submitted_at":"2013-01-23T16:00:02Z","title":"Loopy Belief Propagation for Approximate Inference: An Empirical Study","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1301.6725","snapshot_observed_at":"2026-08-03T07:04:35.640441Z","title":"Loopy belief propagation for approximate inference: An empirical study.arXiv preprint arXiv:1301.6725,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.640441Z"},"links":{"cited_paper":"/paper/1301.6725","citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:d3b0e9116c6d0d3bae0047f2f5ca43054c1d3024a75b434e17cbcbefc5ff6555","observation_id":"98ffc202-cd11-4b1b-b3a7-21c100481f74","resolution":{"observed_at":"2026-08-03T07:04:35.640441Z","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":"2026-08-03T07:04:35.650525Z","title":"For training, we take the data proposed by Ma & Karaman (2018), utilizing 50,000 frames sampled from 249 scenes","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.650525Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:1a965211dc1d4d2a3f4989e2753ccb1afe8115fbf292dbb15be048e5a6fd1573","observation_id":"4eb3f785-6591-4e1b-a54a-edebbd829cee","resolution":{"observed_at":"2026-08-03T07:04:35.650525Z","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":"2026-08-03T07:04:35.653371Z","title":"Models are trained from scratch for approximately 300,000 iterations","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.653371Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:022dcdb64e457c73dda74ad2ba4e56b47f280f561ba6700118a4ddab79762ffc","observation_id":"b331b863-3d18-41df-8c46-c1efb91aa7a6","resolution":{"observed_at":"2026-08-03T07:04:35.653371Z","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":"2026-08-03T07:04:35.656147Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.656147Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:804c826efdbbadf76adbafae9f4608759c887969acd345ed29d9dbbfa31b6411","observation_id":"fa64a88c-2b23-445c-8fc5-b64cdada30f1","resolution":{"observed_at":"2026-08-03T07:04:35.656147Z","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":"2026-08-03T07:04:35.662251Z","title":"For clearer visualization, sparse depth points are enlarged","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.662251Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:5da079ed7037f483d418316a00242665109bb871b03fd85fe5330b72ab3a97b6","observation_id":"9905b512-1c17-4619-8cc8-8a4699be6b8c","resolution":{"observed_at":"2026-08-03T07:04:35.662251Z","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":"2026-08-03T07:04:35.668017Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.668017Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:4424f1f19d52de323cd15c9d76ce18e138503c23501470ff33c9788e02006a71","observation_id":"9b96877a-a518-4f36-a8ef-65062bab59bc","resolution":{"observed_at":"2026-08-03T07:04:35.668017Z","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":"2026-08-03T07:04:35.670796Z","title":"(2021) 735.81 217.15 2.20 0.98 0.106 0.015 – – NLSPN (Park et al.,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.670796Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:d32f802d73872e8ac2c03cc25a2d648af3162171bacb1fc6fb8afe4179ee9b79","observation_id":"8333b42e-076e-45ed-bf7d-cf33e32d2a40","resolution":{"observed_at":"2026-08-03T07:04:35.670796Z","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":"2026-08-03T07:04:35.673437Z","title":"(2022) 712.66 203.25 2.08 0.90 0.090 0.013 – – DySPN (Lin et al.,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.673437Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:a235e81c82212991d5db5d741272808b679e7ad2845f97fe025cb3a2de9c0057","observation_id":"86689f5f-245d-4801-8715-87d7aa4aa41e","resolution":{"observed_at":"2026-08-03T07:04:35.673437Z","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":"2026-08-03T07:04:35.676324Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.676324Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:63cbd2c23060a0e02633068081486b8dcc1c311ad156fad4e4e99b613ebd00ee","observation_id":"ac8e4919-3892-42aa-8173-2f22227dcd06","resolution":{"observed_at":"2026-08-03T07:04:35.676324Z","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":"2026-08-03T07:04:35.679015Z","title":null,"venue":null,"work_id":null,"year":1949},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.679015Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:8a3e8216af5b79622081f6d68a8411c2c2a281cb00215709bdb566568635d7be","observation_id":"14e50d20-82f3-4813-bb12-bb61c931a545","resolution":{"observed_at":"2026-08-03T07:04:35.679015Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-03T07:04:35.681516Z","title":"For a thorough evaluation, given a sparsity level, each test image is sampled 100 times with different random seeds to generate the input sparse depth 24 Preprint map","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.681516Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:fbef0e2cd6616fd5e35918a3a762b76edf4aa896536dac949eb570ef4b4b1379","observation_id":"db8845a0-4b5a-40b5-bea6-77d7ef8bb8fb","resolution":{"observed_at":"2026-08-03T07:04:35.681516Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-03T07:04:35.684175Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.684175Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:dcfa5f830b973f0a6814245f2b48f4d8e1cbabaf23aeb22fe0ea86101cbf367e","observation_id":"c5d7756b-2b5e-47da-a3e0-661209f7c263","resolution":{"observed_at":"2026-08-03T07:04:35.684175Z","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":"2026-08-03T07:04:35.687243Z","title":"Under extremely sparse input, 20 and 50 points, GBPN-1 achieves the lowest RMSE, significantly outperforming other methods","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.687243Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:2cf2fb491c06a654d9bb6eddb1c7a49d1d8f012e5e8c3fac1f541b177c1a0265","observation_id":"206eaeab-e6d5-40f5-af8a-ddc3b4785e3c","resolution":{"observed_at":"2026-08-03T07:04:35.687243Z","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":"2026-08-03T07:04:35.689755Z","title":"Similar phenomenon has also been observed by (Zuo & Deng, 2024), and we attribute this to the lack of robustness to changes in input sparsity","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.689755Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:6bb86eef6b4c9a987d1004e32399a9dc998ba404a088c056d338aa2d99ce932f","observation_id":"8a58ef09-305b-4acd-82bf-e2de7ecd55ac","resolution":{"observed_at":"2026-08-03T07:04:35.689755Z","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":"2026-08-03T07:04:35.692311Z","title":"In addition, these methods were trained exclusively with 500 valid points","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.692311Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:777e2b9f975d2b607a3830e34c2cf7839b89e43149d9a4a5916bab3996fdf15f","observation_id":"9aaaddbe-0404-4634-900e-9157ddd2d306","resolution":{"observed_at":"2026-08-03T07:04:35.692311Z","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":"2026-08-03T07:04:35.695038Z","title":"For each sparsity level, the first row is input image, the second row is sparse map","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.695038Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:317ba05dda52bb88e2c329d8cebf6b80057ac8d9fd80a03f845b0a0d0c5c8378","observation_id":"afc7a96b-5e7e-4853-a6ce-4d9d249fa3ac","resolution":{"observed_at":"2026-08-03T07:04:35.695038Z","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":"2026-08-03T07:04:35.697412Z","title":"Here, GuideNet demonstrates the fastest inference speed, while CFormer and OGNI-DC are notably slower","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.697412Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:d619e700ea2a299c84a7ac996f9ab94ba41e8c5f1c9926fc05de170de2077de1","observation_id":"5c100ec4-d365-4dae-8847-db947f7b728e","resolution":{"observed_at":"2026-08-03T07:04:35.697412Z","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":"2026-08-03T07:04:35.643783Z","title":"Unsupervised depth completion from visual inertial odometry.IEEE Robotics and Automation Letters, 5(2):1899–1906,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":1999,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.643783Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:656141aedf72d5db75711aaca6ffe289a0b85e161c4cd39d2419730773accebe","observation_id":"2f67dbe9-75e3-4d2f-a887-d4dbfae9c777","resolution":{"observed_at":"2026-08-03T07:04:35.643783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15001","last_updated":"2023-01-16T18:58:58Z","snapshot_observed_at":"2026-08-04T04:56:00.219481Z","submitted_at":"2022-09-29T17:57:08Z","title":"Dilated Neighborhood Attention Transformer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15001","snapshot_observed_at":"2026-08-03T07:04:35.633327Z","title":"Dilated neighborhood attention transformer.arXiv preprint arXiv:2209.15001,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.633327Z"},"links":{"cited_paper":"/paper/2209.15001","citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:90572d9ab12acde48488acf16eea5e29178fca35ffdbf30a41f07446a9bb057a","observation_id":"3e16cf6e-1082-4729-8b82-1acf2376e964","resolution":{"observed_at":"2026-08-03T07:04:35.633327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.14139","last_updated":"2022-11-07T16:18:13Z","snapshot_observed_at":"2026-08-05T01:58:15.055899Z","submitted_at":"2019-10-30T21:12:14Z","title":"FutureMapping 2: Gaussian Belief Propagation for Spatial AI","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.14139","snapshot_observed_at":"2026-08-03T07:04:35.629921Z","title":"Futuremapping 2: Gaussian belief propagation for spatial ai","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.629921Z"},"links":{"cited_paper":"/paper/1910.14139","citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:3a35c2ba19d778baa2682c8bb8c6c427896fcee343d0434944800fad738c83fe","observation_id":"21ab937c-5689-4b48-bf1f-37154fa86d45","resolution":{"observed_at":"2026-08-03T07:04:35.629921Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.07648","last_updated":"2017-05-26T18:53:56Z","snapshot_observed_at":"2026-08-08T19:03:12.030897Z","submitted_at":"2016-05-24T20:28:53Z","title":"FractalNet: Ultra-Deep Neural Networks without Residuals","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.07648","snapshot_observed_at":"2026-08-03T07:04:35.636926Z","title":"Fractalnet: Ultra-deep neural networks without residuals.arXiv preprint arXiv:1605.07648,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.636926Z"},"links":{"cited_paper":"/paper/1605.07648","citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:e59cde110d583a312ceda6657ebb4c6fe0bc83f36c25b9d090104690db1398c7","observation_id":"9d693891-b004-4fd7-977e-ea08e7dc5140","resolution":{"observed_at":"2026-08-03T07:04:35.636926Z","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":"2026-08-03T07:04:35.665187Z","title":"23 Preprint Table 5:Performance on KITTI and NYUv2 datasets.For the KITTI dataset, results are evaluated by the KITTI testing server","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.665187Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:23478079e7ef576f2d10da67d4806c20829d83929036794c4a37fcaf7424d902","observation_id":"301731c0-f5d4-4bb0-aadc-a8b70955c23e","resolution":{"observed_at":"2026-08-03T07:04:35.665187Z","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":"2026-08-03T07:04:35.659318Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.659318Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:376d6e6e428a5f4c8431221b9932e1cca63f7d92a3d31036f67505fdd3e8014c","observation_id":"97793e29-cba5-471d-a869-434ef80beb8c","resolution":{"observed_at":"2026-08-03T07:04:35.659318Z","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":"2026-08-03T07:04:35.647025Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-03T07:04:35.647025Z"},"links":{"citing_paper":"/paper/2601.21291"},"observation_digest":"sha256:a8733a7b15f310c80b2b43d33519e781e99f2399aa377982510937516da9db1a","observation_id":"dec4a457-7993-4ee4-a426-c8a166505992","resolution":{"observed_at":"2026-08-03T07:04:35.647025Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2601.21291","last_updated":"2026-06-30T02:06:32Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T11:58:44.529774Z","submitted_at":"2026-01-29T05:44:41Z","title":"Gaussian Belief Propagation Network for Depth Completion"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":23,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":25},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2601.21291."}