{"as_of":"2026-08-14T17:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ffc7ee04c2541987689620b396a320e38a48535f3cf1598cab7d9e20d8e277ff","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T20:23:10.453986Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":17,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2012.15000","last_updated":"2020-12-30T01:35:27Z","snapshot_observed_at":"2026-08-04T07:49:32.632826Z","submitted_at":"2020-12-30T01:35:27Z","title":"DeepSphere: a graph-based spherical CNN","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.15000","snapshot_observed_at":"2026-08-12T20:23:10.453986Z","title":"Deepsphere: a graph-based spherical cnn","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2411.09827","last_updated":"2024-11-14T22:24:59Z","snapshot_observed_at":"2026-08-14T09:26:35.790181Z","submitted_at":"2024-11-14T22:24:59Z","title":"The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-12T20:23:10.453986Z"},"links":{"cited_paper":"/paper/2012.15000","citing_paper":"/paper/2411.09827"},"observation_digest":"sha256:55b51414eb7ff7f5db654d22cf0f95e545342fb23cf9c9b63754038c1219b96d","observation_id":"8da4abb2-dc82-4105-816c-922da1baf066","resolution":{"observed_at":"2026-08-12T20:23:10.453986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.15000","last_updated":"2020-12-30T01:35:27Z","snapshot_observed_at":"2026-08-04T07:49:32.632826Z","submitted_at":"2020-12-30T01:35:27Z","title":"DeepSphere: a graph-based spherical CNN","version":1},"cited_work":{"arxiv_id":"2012.15000","doi":"10.48550/arxiv.2012.15000","metadata_source":"arxiv_reference","pith_arxiv_id":"2012.15000","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Defferrard, M","venue":"arXiv (Cornell University)","work_id":"0f585bae-bf98-4c1d-b399-080e9b36ec26","year":2020},"citing_paper":{"arxiv_id":"2509.00139","last_updated":"2026-05-10T13:52:49Z","snapshot_observed_at":"2026-08-08T03:38:37.770671Z","submitted_at":"2025-08-29T17:08:22Z","title":"Deep Learning for CMB Foreground Removal and Beam Deconvolution: A U-Net GAN Approach","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-18T20:03:06.197589Z"},"links":{"cited_paper":"/paper/2012.15000","citing_paper":"/paper/2509.00139"},"observation_digest":"sha256:8bf7a8c9f25ef7d820ea2057fb6953750351d53ac5484e4f967ba7956ac42e44","observation_id":"876cac43-6d4b-4192-a86e-d83f38cc8c87","resolution":{"observed_at":"2026-05-18T20:06:50.214574Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.15000","last_updated":"2020-12-30T01:35:27Z","snapshot_observed_at":"2026-08-04T07:49:32.632826Z","submitted_at":"2020-12-30T01:35:27Z","title":"DeepSphere: a graph-based spherical CNN","version":1},"cited_work":{"arxiv_id":"2012.15000","doi":"10.48550/arxiv.2012.15000","metadata_source":"arxiv_reference","pith_arxiv_id":"2012.15000","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Defferrard, M","venue":"arXiv (Cornell University)","work_id":"0f585bae-bf98-4c1d-b399-080e9b36ec26","year":2020},"citing_paper":{"arxiv_id":"2606.11309","last_updated":"2026-06-09T18:00:26Z","snapshot_observed_at":"2026-08-01T05:32:47.094252Z","submitted_at":"2026-06-09T18:00:26Z","title":"Dark Energy Survey Year 3 results: optimized $w$CDM simulation-based inference with weak lensing map-level hybrid statistics","version":1},"reference_index":124,"source":"arxiv_source","source_observed_at":"2026-06-27T11:58:47.558898Z"},"links":{"cited_paper":"/paper/2012.15000","citing_paper":"/paper/2606.11309"},"observation_digest":"sha256:efbba2106e73cf577732392ef54029f779e07a26199ef4a26305b3f9e586caad","observation_id":"fef07878-80af-4c40-b3fe-1dc8a8b0f92e","resolution":{"observed_at":"2026-06-27T12:00:53.224806Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.15000","last_updated":"2020-12-30T01:35:27Z","snapshot_observed_at":"2026-08-04T07:49:32.632826Z","submitted_at":"2020-12-30T01:35:27Z","title":"DeepSphere: a graph-based spherical CNN","version":1},"cited_work":{"arxiv_id":"2012.15000","doi":"10.48550/arxiv.2012.15000","metadata_source":"arxiv_reference","pith_arxiv_id":"2012.15000","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Defferrard, M","venue":"arXiv (Cornell University)","work_id":"0f585bae-bf98-4c1d-b399-080e9b36ec26","year":2020},"citing_paper":{"arxiv_id":"2606.27745","last_updated":"2026-07-15T13:11:28Z","snapshot_observed_at":"2026-08-14T02:48:07.276976Z","submitted_at":"2026-06-26T05:54:38Z","title":"Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-29T04:35:58.372801Z"},"links":{"cited_paper":"/paper/2012.15000","citing_paper":"/paper/2606.27745"},"observation_digest":"sha256:5b418e262a2d86e1bd7589ade629fdb6d20bf38f9d088c8cf045db7075e3eb53","observation_id":"9b8bcfc6-101d-474c-ba40-150d6aeb6f98","resolution":{"observed_at":"2026-06-29T20:03:56.675267Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.15000","last_updated":"2020-12-30T01:35:27Z","snapshot_observed_at":"2026-08-04T07:49:32.632826Z","submitted_at":"2020-12-30T01:35:27Z","title":"DeepSphere: a graph-based spherical CNN","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.15000","snapshot_observed_at":"2026-08-02T09:58:47.668297Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.27745","last_updated":"2026-07-15T13:11:28Z","snapshot_observed_at":"2026-08-14T02:48:07.276976Z","submitted_at":"2026-06-26T05:54:38Z","title":"Panoramic Scene Understanding: A Survey from Distortion-Aware Engineering to Sphere-Native Modeling","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T09:58:47.668297Z"},"links":{"cited_paper":"/paper/2012.15000","citing_paper":"/paper/2606.27745"},"observation_digest":"sha256:b40111273cfdb41cfd355c9b4c6ad70a77d511527001013d4a7ec16b0329c179","observation_id":"44b9ffdd-f42d-4602-9d13-d35ffc26dca8","resolution":{"observed_at":"2026-08-02T09:58:47.668297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2012.15000/citation-record","integrity":"/paper/2012.15000/integrity","json":"/paper/2012.15000/citation-record.json","paper":"/paper/2012.15000"},"outbound":[],"paper":{"arxiv_id":"2012.15000","last_updated":"2020-12-30T01:35:27Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-04T07:49:32.632826Z","submitted_at":"2020-12-30T01:35:27Z","title":"DeepSphere: a graph-based spherical CNN"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2012.15000."}