{"as_of":"2026-08-16T07:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:48002fd236573f17a964f8261d2c24a75c8c05979147c00aafdb2b4309e5231e","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:25:52.929725Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/1908.07222/citation-record","integrity":"/paper/1908.07222/integrity","json":"/paper/1908.07222/citation-record.json","paper":"/paper/1908.07222"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:54.026696Z","title":"Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embed- ding","venue":null,"work_id":"a040fcff-634c-4413-9018-9013ec5c65eb","year":2012},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.653160Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:5721778b7dbdc2f236c280b1fe21c707690d31d62715203a3ccce47d818fa7f6","observation_id":"2ca03489-0624-413a-a844-ba1cc1b651a1","resolution":{"observed_at":"2026-08-14T12:25:54.033304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1809.07517","last_updated":"2019-01-31T07:44:49Z","snapshot_observed_at":"2026-08-14T18:25:58.807875Z","submitted_at":"2018-09-20T08:00:42Z","title":"The 2018 PIRM Challenge on Perceptual Image Super-resolution","version":3},"cited_work":{"arxiv_id":"1809.07517","doi":null,"metadata_source":"pith","pith_arxiv_id":"1809.07517","snapshot_observed_at":"2026-08-14T12:25:53.157445Z","title":"The 2018 PIRM Challenge on Perceptual Image Super-resolution","venue":"cs.CV","work_id":"30a11b10-9cf5-42f4-80e5-3ffa54ff04f8","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.658959Z"},"links":{"cited_paper":"/paper/1809.07517","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:513a5f6c4bb0e8bfbfd83ad0e510996eebd3ad6385bab3b7be363b2225829e4b","observation_id":"b64598aa-7ba8-4e33-9613-20becacce3b8","resolution":{"observed_at":"2026-08-14T12:25:53.164836Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":{"arxiv_id":"1511.05666","last_updated":"2016-03-01T18:26:13Z","snapshot_observed_at":"2026-08-14T22:22:28.378993Z","submitted_at":"2015-11-18T06:24:00Z","title":"Super-Resolution with Deep Convolutional Sufficient Statistics","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.05666","snapshot_observed_at":"2026-08-14T12:25:52.665166Z","title":"Super- resolution with deep convolutional sufﬁcient statistics","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.665166Z"},"links":{"cited_paper":"/paper/1511.05666","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:15db2c9d931b54ff78933c59d8fbfe39d8f0ee1d636245674073ca29885b3d92","observation_id":"8c3d008d-58bb-45fb-b9fa-161bd8a0ce63","resolution":{"observed_at":"2026-08-14T12:25:52.665166Z","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":"2026-08-14T12:25:54.001401Z","title":null,"venue":null,"work_id":"f7b3e64a-509a-4c25-9d64-e880a465834c","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.671092Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:8c8a9bbe3831c5329282d0021c4cfe121fc9feaa7ea128e5961dea830db0de34","observation_id":"fc6e4adf-e1b2-478e-ba1f-aef004d9a5ac","resolution":{"observed_at":"2026-08-14T12:25:54.008127Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.980424Z","title":"Image super-resolution using deep convolutional net- works","venue":null,"work_id":"97b2a54a-aca4-4125-a408-4a440f603e62","year":2014},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.676655Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:d9b69fa91c814669165ba603ee7ae4a5767b2133592d97a73d716481cc2e2caa","observation_id":"67690ea9-45eb-472c-b729-4cb53dec0747","resolution":{"observed_at":"2026-08-14T12:25:53.987140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.960824Z","title":"Learning a deep convolutional network for im- age super-resolution","venue":null,"work_id":"afe7da9b-a077-4669-b8f5-0aa330470d1f","year":2014},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.681744Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:5c94a49730ebfa252d877e72b7fb5a80fbf8bff84a5eef23102bd9e9f7ebf8c1","observation_id":"ed0dde7b-24f1-4892-ac2e-0fd6799fcd15","resolution":{"observed_at":"2026-08-14T12:25:53.966919Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.932417Z","title":null,"venue":null,"work_id":"6114019a-ed67-4efa-ac65-5241f70a80b3","year":2011},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.687446Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:c5f25014d0e67954d334aa21a2d166ebfd4c5690653d80a8a990d75299c5ecbb","observation_id":"06003fee-9184-4ce1-a17b-75234afd5bed","resolution":{"observed_at":"2026-08-14T12:25:53.939672Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1508.06576","last_updated":"2015-09-02T08:24:59Z","snapshot_observed_at":"2026-08-15T14:12:52.299669Z","submitted_at":"2015-08-26T17:14:42Z","title":"A Neural Algorithm of Artistic Style","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1508.06576","snapshot_observed_at":"2026-08-14T12:25:52.692540Z","title":"Gatys, Alexander S","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.692540Z"},"links":{"cited_paper":"/paper/1508.06576","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:6212e0fd7f427eca4c671882a37b65d7e9f5a35cf937f5013ef767ff03a98496","observation_id":"25fe3fbf-83ab-42a8-a076-25a2225876a7","resolution":{"observed_at":"2026-08-14T12:25:52.692540Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1505.07376","last_updated":"2015-11-06T13:55:09Z","snapshot_observed_at":"2026-08-15T05:09:56.901272Z","submitted_at":"2015-05-27T15:29:52Z","title":"Texture Synthesis Using Convolutional Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.07376","snapshot_observed_at":"2026-08-14T12:25:52.698152Z","title":"Gatys, Alexander S","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.698152Z"},"links":{"cited_paper":"/paper/1505.07376","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:26aa1a2c79f2c3a12f23564db76613c0b8dcb5b32e3eec3e753b0585bebae638","observation_id":"089268f5-4ebf-40e5-9fd4-0ed56bac31cc","resolution":{"observed_at":"2026-08-14T12:25:52.698152Z","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":"2026-08-14T12:25:53.910701Z","title":"The unreasonable effectiveness of texture transfer for single image super-resolution","venue":null,"work_id":"9fe3ae27-fba0-4de1-9d3e-048f656e91ed","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.703537Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:21d70fc691626c737c79c36ea4b5337202a98a3f7308648a122344b5f441f734","observation_id":"f72382d1-19d8-4e17-a064-18dea39a39ae","resolution":{"observed_at":"2026-08-14T12:25:53.917583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:52.710228Z","title":"Generative adversarial nets","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.710228Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:837eacba4b4f3bd82d59f78a4de3461e634b5994d167205929c053b0bbb95f0d","observation_id":"9c8f3d4d-7e37-49b4-87e3-4338c75079aa","resolution":{"observed_at":"2026-08-14T12:25:52.710228Z","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":"2026-08-14T12:25:53.878963Z","title":"Deep residual learning for image recognition","venue":null,"work_id":"af0a0d65-f69c-4942-86ca-be64609db923","year":2016},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.717073Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:e1b80e28fcaa1ec7a5bd2f7a2975efb607d384e0a33307f64096e418822f4dd8","observation_id":"59f21618-a38b-4111-95be-9aaff6d71143","resolution":{"observed_at":"2026-08-14T12:25:53.885542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.860815Z","title":"Identity mappings in deep residual networks","venue":null,"work_id":"e2829021-77e2-4edc-a465-265e350da4e2","year":2016},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.724306Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:f1ddb689f966b4758f9721407ecb178ebcf7fcab76940f050b0a48e5cdd2a3ca","observation_id":"face3078-33c5-444b-bf04-9e96b655cb67","resolution":{"observed_at":"2026-08-14T12:25:53.866192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.841279Z","title":"Sin- gle image super-resolution from transformed self-exemplars","venue":null,"work_id":"201f41ff-6f2a-4ada-a764-04e4935e4ce1","year":2015},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.730321Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:7407ca30cdddf4ebfb75245e8251fe3613826b4a0ab148c6a399c9a840a21611","observation_id":"f63247f9-5dbf-45bf-8aca-ffa3d9588880","resolution":{"observed_at":"2026-08-14T12:25:53.847630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:52.736289Z","title":"Perceptual losses for real-time style transfer and super-resolution","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.736289Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:6a95cd0525673b90cd1d3a339bda924daef6176c24fc62760bcea842bb6c4a79","observation_id":"e9c11728-510f-466e-acba-4385b26e6ad5","resolution":{"observed_at":"2026-08-14T12:25:52.736289Z","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":"2026-08-14T12:25:53.801441Z","title":"Accu- rate image super-resolution using very deep convolutional networks","venue":null,"work_id":"4db7cc73-50c8-410b-bcde-4a1255474252","year":2016},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.741825Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:e82db890312fc8993f7d28cc0d1aadc3e71856889fed1d1dafb39dd2e165dca1","observation_id":"3dc8fc40-1fb1-41cd-85b5-3d2df2bc6e0e","resolution":{"observed_at":"2026-08-14T12:25:53.808063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.778277Z","title":"Deeply- recursive convolutional network for image super-resolution","venue":null,"work_id":"073ee5a3-7251-48b4-a814-9cd9264c358c","year":2016},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.747550Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:4d2e6284271be789bcae920462538e127d86d924710f6b39e3e05ba3766533ee","observation_id":"bf04b299-0811-42fe-9f95-9e39b29579e1","resolution":{"observed_at":"2026-08-14T12:25:53.785543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.752411Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":"06a8d5b6-fb30-4936-bdcb-454e6678a1eb","year":2014},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.753853Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:7b2f4cb4d852d479e0991002b99a0389faf62b6d588bb5e2faf86a0d4c0b35ec","observation_id":"9e663cad-4c83-416d-b522-d9b9d448e88d","resolution":{"observed_at":"2026-08-14T12:25:53.758960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.729241Z","title":"Deep laplacian pyramid networks for fast and accurate super-resolution","venue":null,"work_id":"c8078975-41f2-45fd-95c2-b32490dabc85","year":2017},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.760403Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:90f1f74a6a52c2cfdaff236bdd9ed223a8a4bfc03c5aa4194a12d24323cf1c8e","observation_id":"1b8b4398-653f-4885-b350-1df5c03422c8","resolution":{"observed_at":"2026-08-14T12:25:53.736995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.705155Z","title":"Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi","venue":null,"work_id":"85b651de-fe57-458f-afcb-ca07513e7843","year":2017},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.766321Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:6e679bdea0df7aac888d03a57f8b0120fcb6b0fd3c6c00f80dbe6b9f99293a0f","observation_id":"8aebdc6d-5ff6-4b77-afc0-88f39425c08a","resolution":{"observed_at":"2026-08-14T12:25:53.712775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.682635Z","title":"Enhanced deep residual networks for single image super-resolution","venue":null,"work_id":"68611157-96e6-4df3-b27d-432c366588e4","year":2017},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.771844Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:20e9770b9e3594484b91e0e3f8312c68ef6bd1c3877ef621550ecda0882b15d9","observation_id":"ce59cf0c-0732-4fe0-bf12-c37f3b550818","resolution":{"observed_at":"2026-08-14T12:25:53.690110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:52.777142Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.777142Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:966be84eba09f5ef95d4937bf91425985d06066a158a3d65f8389376706427d5","observation_id":"b9057170-67ff-4e0c-9d9f-c565ac22943a","resolution":{"observed_at":"2026-08-14T12:25:52.777142Z","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":"2026-08-14T12:25:53.644821Z","title":"Visualizing deep convolutional neural networks using natural pre-images","venue":null,"work_id":"b33f0084-a8c7-4f91-870b-a52e5bb751a9","year":2016},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.782535Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:6b9f21451a5a51206fe1ab93c115791416a10d9237aa98a25981fce6f6dce4a7","observation_id":"0eabc92c-7b94-4093-8122-20f043beb15d","resolution":{"observed_at":"2026-08-14T12:25:53.651540Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1803.04626","last_updated":"2018-07-18T12:32:51Z","snapshot_observed_at":"2026-08-14T19:36:51.254161Z","submitted_at":"2018-03-13T05:19:26Z","title":"Maintaining Natural Image Statistics with the Contextual Loss","version":3},"cited_work":{"arxiv_id":"1803.04626","doi":null,"metadata_source":"pith","pith_arxiv_id":"1803.04626","snapshot_observed_at":"2026-08-14T12:25:53.047654Z","title":"Maintaining Natural Image Statistics with the Contextual Loss","venue":"cs.CV","work_id":"0b760921-052a-4d23-9cb2-553162a4d16d","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.788252Z"},"links":{"cited_paper":"/paper/1803.04626","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:360fdde0ed7028020ffbdac4b007aefac29dea50071dbd2afadc60a84ecf3bea","observation_id":"1f83197f-1093-4fec-997e-e2eb8967a03a","resolution":{"observed_at":"2026-08-14T12:25:53.058006Z","resolver_source":"local_arxiv","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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.620003Z","title":null,"venue":null,"work_id":"3684db88-1fb6-4002-86e6-ab0ef4db1b2d","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.794481Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:d6a882adb10bdc7681e136cf600314d8d1280a38b569e7c0dfad9932a9986b72","observation_id":"d9079a8f-b489-4b99-96fc-a3e5e2ecbd6b","resolution":{"observed_at":"2026-08-14T12:25:53.626137Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.595061Z","title":"Beneﬁting from multitask learn- ing to improve single image super-resolution","venue":null,"work_id":"73aff243-626d-4d3e-9c10-f9d0986c1f7e","year":2019},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.799835Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:83fdd2676fb77959ad8daf183a766d8776b29fc32790ccf73683e0e753055533","observation_id":"9dc207e0-0d2b-4cb3-9fc5-96c255e6d60d","resolution":{"observed_at":"2026-08-14T12:25:53.601889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.575300Z","title":null,"venue":null,"work_id":"1ae76653-5237-4c67-89ab-3b7aa54c42e1","year":2017},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.805588Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:470f8eebf163af1f281ca87f6a694fe01b49f909d1382ead1fab008b7d9b724b","observation_id":"f3f09864-5959-486a-ba68-fccfdb585299","resolution":{"observed_at":"2026-08-14T12:25:53.581116Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6034","last_updated":"2014-04-19T11:54:52Z","snapshot_observed_at":"2026-07-06T03:31:30.452356Z","submitted_at":"2013-12-20T16:45:54Z","title":"Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6034","snapshot_observed_at":"2026-08-14T12:25:52.812072Z","title":"Deep inside convolutional networks: Visualising image clas- siﬁcation models and saliency maps","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.812072Z"},"links":{"cited_paper":"/paper/1312.6034","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:9453c89fdf65d1ed9229e87dc5bace116afd87213adf45bb4b3c5bf2020ead47","observation_id":"22f2acf9-9109-41c1-9274-0f7cb9249afa","resolution":{"observed_at":"2026-08-14T12:25:52.812072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-14T23:20:42.336514Z","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":"2026-08-14T12:25:52.820825Z","title":"Very deep convo- lutional networks for large-scale image recognition","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.820825Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:05f532e4a62bb867d174f6ddc34ce52543fc2e5c4422ce7819273b5046098ff4","observation_id":"ffe6fef2-2476-4a0b-8d44-1336905d7a29","resolution":{"observed_at":"2026-08-14T12:25:52.820825Z","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":"2026-08-14T12:25:53.556282Z","title":null,"venue":null,"work_id":"99afe857-e920-4bbc-b1dd-c85cf0a590fc","year":2010},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.828810Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:7d4088a279c842428e19b914f46056a63e2673714b2f6d4cacd257a165714d4f","observation_id":"7d73e70c-bec6-4ca5-a02c-565725a51597","resolution":{"observed_at":"2026-08-14T12:25:53.562228Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.537107Z","title":"Mem- net: A persistent memory network for image restoration","venue":null,"work_id":"e661fae5-ffa4-4ea6-81a0-efe2e490645c","year":2017},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.836208Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:e43b0cc59fb1fd9c3204c11abd52a7eca3b19c880b0a5053ad2cced82d7c35d4","observation_id":"88c5dc85-6082-4987-88ca-2c44cc97b58c","resolution":{"observed_at":"2026-08-14T12:25:53.543253Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.516585Z","title":"Seman- tic super-resolution: When and where it is useful? Computer Vision and Image Understanding, September 2015","venue":null,"work_id":"80d5e8c9-da2e-41f8-a7b7-67c69275f117","year":2015},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.841931Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:3d64cf526d9ddd54f1b73d46a0ca3ae9b9b5728a735f16c5a2aaa3e159eb8789","observation_id":"f3e3f375-9b6c-4e93-93b4-29d5ff0addd3","resolution":{"observed_at":"2026-08-14T12:25:53.523181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.493720Z","title":"Tsai and T","venue":null,"work_id":"6f982ffb-ea00-4532-a9f2-a287feb8c5c1","year":1984},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.847180Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:270a1a4e5ee81d1381c2e61a46a335d542ec73524c89617cd2184dd4a9846406","observation_id":"5dccb262-bf32-46c5-8a70-4d2d6d30b6bc","resolution":{"observed_at":"2026-08-14T12:25:53.501512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.469047Z","title":null,"venue":null,"work_id":"ac57566b-2e63-4e51-894f-695d079a11aa","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.854334Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:bfe61fac1c2f53408dc398bc7b18c77a5a173aa89aac0cdcb96532ad301e8014","observation_id":"fa5dd8cc-dc52-4d6d-896d-83eed834bdb7","resolution":{"observed_at":"2026-08-14T12:25:53.479055Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.441184Z","title":"Recovering realistic texture in image super-resolution by deep spatial feature transform","venue":null,"work_id":"6a786519-857f-42e4-837f-5991b4614488","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.860613Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:12ae71179448fbdc9939fbe49c0b074b1e5c6014311444c10f4cef929c36a62d","observation_id":"2b5dc6f0-009c-47b8-a135-3b2c012f80f6","resolution":{"observed_at":"2026-08-14T12:25:53.447262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.415708Z","title":"Esrgan: En- hanced super-resolution generative adversarial networks","venue":null,"work_id":"447cdfb4-36c3-4087-bd4b-2ac6bba84398","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.865967Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:be23d3633fe355f627dc154da14c765715278a4661753aa2c947882fd05cc31e","observation_id":"be1e1750-36b6-418d-8398-dab7431c0197","resolution":{"observed_at":"2026-08-14T12:25:53.424264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.389695Z","title":null,"venue":null,"work_id":"ea4c417d-02b1-474c-bc5c-f23f8b81b080","year":2004},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.872311Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:656dfb86957ac12375b872c085765f277f31ff7b25759eb4cd9388a26ec767c8","observation_id":"9a8a751a-7146-4476-9f62-094e6d557892","resolution":{"observed_at":"2026-08-14T12:25:53.398045Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1506.06579","last_updated":"2015-06-22T12:57:15Z","snapshot_observed_at":"2026-08-16T04:36:06.256807Z","submitted_at":"2015-06-22T12:57:15Z","title":"Understanding Neural Networks Through Deep Visualization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1506.06579","snapshot_observed_at":"2026-08-14T12:25:52.878053Z","title":"Fuchs, and Hod Lipson","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.878053Z"},"links":{"cited_paper":"/paper/1506.06579","citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:c2f0a869a11c7a85c9f22a19141c926dfdb5fe84db5b362bc31d679c8f4bc0ca","observation_id":"66cc182a-5d5d-4310-8a84-453b905f5954","resolution":{"observed_at":"2026-08-14T12:25:52.878053Z","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":"2026-08-14T12:25:53.360568Z","title":"Craft- ing a toolchain for image restoration by deep reinforcement learning","venue":null,"work_id":"f47f163c-4319-4418-a0a0-f35e88329d19","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.883233Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:707a7a3a9d3fe6f1a7754beafa43c41135ef23cceb8f904a6f68effe8a288e74","observation_id":"a63d245e-db4c-465d-a7fb-c67b279adc1f","resolution":{"observed_at":"2026-08-14T12:25:53.366368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.328505Z","title":"Visualizing and comparing convolutional neural net- works, 2014","venue":null,"work_id":"a02a2e18-cd9e-4d88-9e99-c1eea7bc2bd3","year":2014},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.889525Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:c7735662027c6b13fc2c6f78faebbe16c0ca016d4cda2feb62a5af1cf332d527","observation_id":"2f33f325-e55d-473b-88b2-6283a5dca2e9","resolution":{"observed_at":"2026-08-14T12:25:53.336642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.303438Z","title":"Unsupervised image super- resolution using cycle-in-cycle generative adversarial net- works","venue":null,"work_id":"7005396d-2679-4c50-ae0f-413ef41fc924","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.895978Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:63b95b02eac1f7a937b5b87ce987550e38abbcc7392e3c2bc82a4b83ee7e7ac8","observation_id":"22274766-c896-46b9-8d5a-207c57069299","resolution":{"observed_at":"2026-08-14T12:25:53.310621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.279299Z","title":"On single image scale-up using sparse-representations","venue":null,"work_id":"8b7afd8d-d6ea-4b92-8037-de2b9df94848","year":2012},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.901391Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:ff906c1f16b7b5f4f4a332fdfac9ae061cd8b75262480e743675cc1b91ce0195","observation_id":"5edcf251-1d6a-4ee8-b40d-8b9983145cef","resolution":{"observed_at":"2026-08-14T12:25:53.286716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.256850Z","title":"Efros, Eli Shecht- man, and Oliver Wang","venue":null,"work_id":"b897d243-6b82-4cc1-8bee-41aa9bd3c921","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.907437Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:363b507c92f6869ba2e143672c0b1ab345f581d556df77042aa4bbb13f5eb593","observation_id":"d64ba79d-0978-4e61-b80f-b12214e01751","resolution":{"observed_at":"2026-08-14T12:25:53.264168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:52.916789Z","title":"Image super-resolution using very deep residual channel attention networks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.916789Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:b17ac16371cb59369fd16787ca7226f7ef8bbd7b72003e1e13635275e3160867","observation_id":"74a98583-e1dc-42e4-87c0-9ef59a2bdfa9","resolution":{"observed_at":"2026-08-14T12:25:52.916789Z","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":"2026-08-14T12:25:53.204475Z","title":"Residual dense network for image super-resolution","venue":null,"work_id":"68d1da12-d729-416b-8a71-964b59a0980d","year":2018},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.924330Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:f19f6361ea9010bce2680c14ed60afebc8ac02609bc4fdd4d2e71871b1061c2e","observation_id":"49463827-9c22-4a9b-8f38-332a79d56f54","resolution":{"observed_at":"2026-08-14T12:25:53.211860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:53.182384Z","title":"Scene parsing through ade20k dataset","venue":null,"work_id":"100880c8-b794-48b1-982f-4c29d3a59208","year":2017},"citing_paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:52.929725Z"},"links":{"citing_paper":"/paper/1908.07222"},"observation_digest":"sha256:03d9c383e4558256107c884476949ae1a628e255366c73491c84fe918bbe4b96","observation_id":"1fffabaf-3db4-4024-b1ea-d374ea88730d","resolution":{"observed_at":"2026-08-14T12:25:53.188609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}}],"paper":{"arxiv_id":"1908.07222","last_updated":"2019-08-20T08:39:48Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T06:07:19.467985Z","submitted_at":"2019-08-20T08:39:48Z","title":"SROBB: Targeted Perceptual Loss for Single Image Super-Resolution"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":2,"verified_fuzzy":27},"total_outbound_references":46},"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 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:1908.07222."}