{"as_of":"2026-08-16T08:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:50bd029cf0367d1747d6bdff4cf8e7fc94deb85f49e449d495859488032e50b9","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T13:28:22.014498Z","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":"2026-05-11T03:10:53.753855Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1703.03208","last_updated":"2017-03-09T10:11:03Z","snapshot_observed_at":"2026-08-16T07:24:46.495734Z","submitted_at":"2017-03-09T10:11:03Z","title":"Compressed Sensing using Generative Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.03208","snapshot_observed_at":"2026-08-14T13:28:22.014498Z","title":", Jalal, A","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.05368","last_updated":"2020-08-22T06:44:50Z","snapshot_observed_at":"2026-08-16T07:24:04.525012Z","submitted_at":"2019-08-14T22:56:34Z","title":"Robust One-Bit Recovery via ReLU Generative Networks: Near-Optimal Statistical Rate and Global Landscape Analysis","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-14T13:28:22.014498Z"},"links":{"cited_paper":"/paper/1703.03208","citing_paper":"/paper/1908.05368"},"observation_digest":"sha256:5e91e26689166f4e628fe7baa5b0843c1eca2bb8ee3f461d18298ed70dd362e1","observation_id":"d2b16845-daa4-4654-96a8-9018487ccfc8","resolution":{"observed_at":"2026-08-14T13:28:22.014498Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1703.03208","last_updated":"2017-03-09T10:11:03Z","snapshot_observed_at":"2026-08-16T07:24:46.495734Z","submitted_at":"2017-03-09T10:11:03Z","title":"Compressed Sensing using Generative Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.03208","snapshot_observed_at":"2026-08-14T12:23:20.329274Z","title":"Compressed sensing using generative models","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07404","last_updated":"2019-08-20T14:49:45Z","snapshot_observed_at":"2026-08-16T07:24:50.856212Z","submitted_at":"2019-08-20T14:49:45Z","title":"Blind Image Deconvolution using Pretrained Generative Priors","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:23:20.329274Z"},"links":{"cited_paper":"/paper/1703.03208","citing_paper":"/paper/1908.07404"},"observation_digest":"sha256:184bd18f5ffaf4b184473f29a3efdc334d9bfa83df45d6d7f0499f4666c2dcf1","observation_id":"87b24378-908e-43d9-9f26-d847a270a210","resolution":{"observed_at":"2026-08-14T12:23:20.329274Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1703.03208","last_updated":"2017-03-09T10:11:03Z","snapshot_observed_at":"2026-08-16T07:24:46.495734Z","submitted_at":"2017-03-09T10:11:03Z","title":"Compressed Sensing using Generative Models","version":1},"cited_work":{"arxiv_id":"1703.03208","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1703.03208","snapshot_observed_at":"2026-07-04T21:48:54.656406Z","title":"arXiv preprint arXiv:1703.03208 , year=","venue":null,"work_id":"013e1589-9eeb-4a65-9b31-93d39bcc93da","year":null},"citing_paper":{"arxiv_id":"2605.07513","last_updated":"2026-05-08T09:44:33Z","snapshot_observed_at":"2026-08-12T15:32:32.654900Z","submitted_at":"2026-05-08T09:44:33Z","title":"Tessellations of Semi-Discrete Flow Matching","version":1},"reference_index":101,"source":"arxiv_source","source_observed_at":"2026-05-11T02:37:06.288757Z"},"links":{"cited_paper":"/paper/1703.03208","citing_paper":"/paper/2605.07513"},"observation_digest":"sha256:b105df526faf5a50a9a1b4a3307fdcf4e29a980a4cd4a70c34c51dbf55d70630","observation_id":"b2a247a4-a218-46d9-9a69-26d6b57caac8","resolution":{"observed_at":"2026-07-04T21:48:54.656406Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1703.03208/citation-record","integrity":"/paper/1703.03208/integrity","json":"/paper/1703.03208/citation-record.json","paper":"/paper/1703.03208"},"outbound":[],"paper":{"arxiv_id":"1703.03208","last_updated":"2017-03-09T10:11:03Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-16T07:24:46.495734Z","submitted_at":"2017-03-09T10:11:03Z","title":"Compressed Sensing using Generative Models"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1703.03208."}