{"as_of":"2026-08-08T22:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2251148d4782f2ac97227998c90870a2d9a6acaad8a64ac540cecd17be836051","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":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":13,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:04:05.687347Z","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":"2026-07-04T11:39:47.595411Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"1906.11148","last_updated":"2019-06-26T15:05:24Z","snapshot_observed_at":"2026-08-06T23:37:49.061993Z","submitted_at":"2019-06-26T15:05:24Z","title":"Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-25T15:45:38.743857Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/1906.11148"},"observation_digest":"sha256:73e72103027de708ce15ebd93b0454c294d621781147bcf58a2265fa8d7f5484","observation_id":"ed5b3057-d0a8-43d3-8669-3da52c20eac2","resolution":{"observed_at":"2026-05-25T15:45:59.257683Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"2202.05568","last_updated":"2026-05-14T15:08:56Z","snapshot_observed_at":"2026-07-06T12:36:45.308097Z","submitted_at":"2022-02-11T11:53:28Z","title":"Change of measure through the Legendre transform","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-24T12:23:57.747016Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2202.05568"},"observation_digest":"sha256:5bd1cf78c8208292a4eb8cdb62429de52ebae1842bed448006beb99d27ee513b","observation_id":"dddfdfe5-4963-49f0-a190-31e7c453e989","resolution":{"observed_at":"2026-05-24T12:24:27.416889Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-08-07T11:04:05.687347Z","title":"A primer on pac-bayesian learning","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.03670","last_updated":"2025-06-04T08:01:06Z","snapshot_observed_at":"2026-08-07T10:55:28.191660Z","submitted_at":"2025-06-04T08:01:06Z","title":"Position: There Is No Free Bayesian Uncertainty Quantification","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T11:04:05.687347Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2506.03670"},"observation_digest":"sha256:1d9c2d1065dcd5e8f8b2f711a741ef3443eb64dbd168a62fd1eb004463727374","observation_id":"a6f51306-3555-4802-9bde-1eebbae4bd7f","resolution":{"observed_at":"2026-08-07T11:04:05.687347Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-08-04T10:24:35.954858Z","title":"A Primer on PAC-Bayesian Learning , 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2510.10544","last_updated":"2026-05-28T18:38:46Z","snapshot_observed_at":"2026-08-06T12:08:51.428259Z","submitted_at":"2025-10-12T11:02:18Z","title":"PAC-Bayesian Reinforcement Learning Trains Generalizable Policies","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-04T10:24:35.954858Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2510.10544"},"observation_digest":"sha256:677d6c740a837867350304b0bcfbf318cfd46d59b74800e4c373d77a73e1b82a","observation_id":"4c4710fc-98df-4820-ad94-6d45e68c11ed","resolution":{"observed_at":"2026-08-04T10:24:35.954858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"2602.07999","last_updated":"2026-05-26T23:40:51Z","snapshot_observed_at":"2026-08-03T03:31:47.277340Z","submitted_at":"2026-02-08T14:53:14Z","title":"Tighter Information-Theoretic Generalization Bounds via a Novel Class of Change of Measure Inequalities","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T06:09:32.629347Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2602.07999"},"observation_digest":"sha256:821e125f2b4489951b593ff500240f681e990dd41d421203073f2e0f227644ab","observation_id":"bb56178f-c40d-4c6d-ab23-de0cd8963a82","resolution":{"observed_at":"2026-05-16T06:10:40.737768Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-08-03T03:31:48.786676Z","title":"A primer on PAC-Bayesian learning,","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2602.07999","last_updated":"2026-05-26T23:40:51Z","snapshot_observed_at":"2026-08-03T03:31:47.277340Z","submitted_at":"2026-02-08T14:53:14Z","title":"Tighter Information-Theoretic Generalization Bounds via a Novel Class of Change of Measure Inequalities","version":4},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T03:31:48.786676Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2602.07999"},"observation_digest":"sha256:0386972e17a0e0cb6681f59b3f5458957608c7b2fdfc62af26e349f5b28a2b1f","observation_id":"881512df-aa9c-4054-bbf3-ed4edc6fe56a","resolution":{"observed_at":"2026-08-03T03:31:48.786676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"2605.14746","last_updated":"2026-07-12T07:31:17Z","snapshot_observed_at":"2026-07-29T20:44:23.574180Z","submitted_at":"2026-05-14T12:13:08Z","title":"Selective Safety Steering via Value-Filtered Decoding","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-30T21:03:28.381687Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2605.14746"},"observation_digest":"sha256:f16da4d4f0f988355a4fde39ef43ff8ff516b18d9f1ea18fb64a1d6a5a908e70","observation_id":"6674cb79-f9d2-4a79-97a0-4b0a44eea570","resolution":{"observed_at":"2026-06-30T21:05:03.900618Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-14T18:59:01.049397Z","title":"value head","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2605.14746","last_updated":"2026-07-12T07:31:17Z","snapshot_observed_at":"2026-07-29T20:44:23.574180Z","submitted_at":"2026-05-14T12:13:08Z","title":"Selective Safety Steering via Value-Filtered Decoding","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-14T18:59:01.049397Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2605.14746"},"observation_digest":"sha256:45f68b0274a727ddd70737fcb2a2d9af1d179deee24e3f36d59a16cf3418f323","observation_id":"9f7bb6c8-0fbf-49bf-9b9f-6115a3f23fbc","resolution":{"observed_at":"2026-07-14T18:59:01.049397Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"2606.02589","last_updated":"2026-05-21T05:01:39Z","snapshot_observed_at":"2026-07-06T23:42:58.036516Z","submitted_at":"2026-05-21T05:01:39Z","title":"Rashomon-Seeded Annealing for Robust Bayesian Inference in Factorial Designs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-30T16:33:08.558052Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2606.02589"},"observation_digest":"sha256:d46fa9b6e8cf3275f15f8c0a76716fdac96e8faa0a5ceaf71b9957d6bc85f9a7","observation_id":"e2448836-10ba-4d09-ba70-5341039315d3","resolution":{"observed_at":"2026-06-30T16:35:12.392649Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"2606.23009","last_updated":"2026-06-22T08:22:13Z","snapshot_observed_at":"2026-08-06T19:54:12.989083Z","submitted_at":"2026-06-22T08:22:13Z","title":"Hierarchical Bayes meets hierarchical forecasting: A flexible framework for level-focused forecasts","version":1},"reference_index":114,"source":"arxiv_source","source_observed_at":"2026-06-26T07:45:30.493501Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2606.23009"},"observation_digest":"sha256:bb2f37c268512956cd7d0d363307867ca5f25b6d6865de46d574eabd1a4cff97","observation_id":"7215e7a9-c195-455e-b686-d343f0e03189","resolution":{"observed_at":"2026-07-04T11:39:47.596765Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"2606.28281","last_updated":"2026-06-26T17:24:21Z","snapshot_observed_at":"2026-08-07T05:23:28.873814Z","submitted_at":"2026-06-26T17:24:21Z","title":"PAC-Bayesian Certificates for Quadratic Closed-Loop Control","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-29T02:48:00.937356Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2606.28281"},"observation_digest":"sha256:b220f051204ac53ef1113bc61302838f7fb1bd721614c2542333dce04cb62b2d","observation_id":"f56d1d67-4a95-46f5-9912-2f66356eceef","resolution":{"observed_at":"2026-07-01T17:55:52.500823Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":"1901.05353","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-07-04T11:39:47.595411Z","title":"A primer on PAC-bayesian learning","venue":null,"work_id":"c313bfb9-ed08-4643-84e2-f10f357caa94","year":1901},"citing_paper":{"arxiv_id":"2606.29043","last_updated":"2026-06-27T18:39:21Z","snapshot_observed_at":"2026-08-02T02:25:37.244962Z","submitted_at":"2026-06-27T18:39:21Z","title":"How Far Can Sharpness and Complexity Jointly Explain Generalization?","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-30T09:27:42.998341Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2606.29043"},"observation_digest":"sha256:e3416403ad56a87009080a6e9ce6fb45eae1c5934328fdaffd32ca864a74df80","observation_id":"66ca337f-c30f-4c86-ad52-ddc6ca1d9d89","resolution":{"observed_at":"2026-06-30T09:34:34.764035Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.05353","snapshot_observed_at":"2026-08-03T14:08:19.176866Z","title":"arXiv preprint arXiv:1901.05353 , year=","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2607.29077","last_updated":"2026-07-31T06:56:22Z","snapshot_observed_at":"2026-08-05T23:12:30.958755Z","submitted_at":"2026-07-31T06:56:22Z","title":"A Generalized-Bayes Perspective on Counterfactual Explanations: Posterior-Based Decision-Making and Evaluation","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-03T14:08:19.176866Z"},"links":{"cited_paper":"/paper/1901.05353","citing_paper":"/paper/2607.29077"},"observation_digest":"sha256:66dd5a071631457dc4f7974727369c8c82949d6975e206dad372bacd00e66d67","observation_id":"683a5935-9ebb-4dde-aabc-2256ca11d372","resolution":{"observed_at":"2026-08-03T14:08:19.176866Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1901.05353/citation-record","integrity":"/paper/1901.05353/integrity","json":"/paper/1901.05353/citation-record.json","paper":"/paper/1901.05353"},"outbound":[],"paper":{"arxiv_id":"1901.05353","last_updated":"2019-05-07T21:11:16Z","latest_version":3,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-08T11:44:39.947522Z","submitted_at":"2019-01-16T15:47:51Z","title":"A Primer on PAC-Bayesian Learning"},"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":"2026-08-08T06:32:00.761636+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 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:1901.05353."}