{"as_of":"2026-08-15T09:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:83227dc72490955b3377296d26cfa098f8d54dce9600e766524065682936d065","coverage":[{"denominator":8,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:19:29.529771Z","state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T05:35:04.251947Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-14T05:35:04.585293Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"cited_work":{"arxiv_id":"2608.06337","doi":null,"metadata_source":"pith","pith_arxiv_id":"2608.06337","snapshot_observed_at":"2026-08-14T05:35:04.585293Z","title":"Optimal Rates for Learning with Monotone Adversaries","venue":"stat.ML","work_id":"dc5a2417-f1b2-427b-bf8a-3d569118e10b","year":2026},"citing_paper":{"arxiv_id":"2608.13514","last_updated":"2026-08-13T17:36:49Z","snapshot_observed_at":"2026-08-15T09:16:39.097226Z","submitted_at":"2026-08-13T17:36:49Z","title":"Bagging Robustly Learns VC Classes with Linear Sample Complexity","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-14T05:35:04.251947Z"},"links":{"cited_paper":"/paper/2608.06337","citing_paper":"/paper/2608.13514"},"observation_digest":"sha256:e9bdfbf7f2bc5a91ac8cd8a1f435e915299b2480f9905ed4d7862b69033a07ed","observation_id":"0e0fcc7d-6ac6-44cc-beed-a60ad7cfa42d","resolution":{"observed_at":"2026-08-14T05:35:04.589905Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2608.06337/citation-record","integrity":"/paper/2608.06337/integrity","json":"/paper/2608.06337/citation-record.json","paper":"/paper/2608.06337"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:19:29.608808Z","title":"The Optimal Sample Complexity of PAC Learning","venue":null,"work_id":"4bd9a58e-333a-4f67-a08c-cde89da021d9","year":2016},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.519223Z"},"links":{"citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:73c76a023a1016151accba5bb82a2b4e68cc6bc0dab333a4733e3d51a98bad41","observation_id":"6ad3787b-d047-4dc3-af77-ee66bc75e4bd","resolution":{"observed_at":"2026-08-07T05:19:29.613862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T05:19:29.658335Z","title":"PMLR, 2016, pp","venue":null,"work_id":"598c70f0-31ba-4e06-b02a-9cee86b88e33","year":2016},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.497159Z"},"links":{"citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:c660ac91c82b13785a402c0e1af64ea514f40347b46b5b6486a34afe39f23e83","observation_id":"f75b6f96-40c9-405c-af93-d452147323e7","resolution":{"observed_at":"2026-08-07T05:19:29.663462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T05:19:29.624701Z","title":"Learning in an Echo Chamber: Online Learning with Replay Adversary","venue":null,"work_id":"21c2ac52-c5ca-4cf2-9a29-664a1bff9bef","year":1989},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":134,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.514012Z"},"links":{"citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:642f6ace109e10c0a4b0bddff23e7448fc5bf0a351567676fa2c0cf365ac3588","observation_id":"6fe64d4b-f767-4177-a57f-2a6e96e0b195","resolution":{"observed_at":"2026-08-07T05:19:29.630293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T05:19:29.592495Z","title":"Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm","venue":null,"work_id":"d71eddc9-4280-4bd5-aaea-219efcf5ed1c","year":1988},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":195,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.525009Z"},"links":{"citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:0c065ef2f2637442fd0b17a6783746a523aff81545b4a5f5578de94ed3e94bcc","observation_id":"1d21716a-a9b4-4c49-8b95-27d56abb97e8","resolution":{"observed_at":"2026-08-07T05:19:29.597317Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T05:19:29.674445Z","title":"Partitioning and Geometric Embedding of Range Spaces of Finite Vapnik–Chervonenkis Dimension","venue":null,"work_id":"00d45c23-205c-4e79-8942-2985f435a056","year":2024},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":247,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.491769Z"},"links":{"citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:f3d23e5b47282f53e571af559c407c59e71c655655d726b377e577a56bbe1598","observation_id":"c1572a63-0cb6-401a-a379-fe236ebb01c9","resolution":{"observed_at":"2026-08-07T05:19:29.680082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T05:19:29.574431Z","title":"How Robust are Reconstruction Thresholds for Community Detection?","venue":null,"work_id":"95d9afab-202b-4582-b092-f348a97f2156","year":2015},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":313,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.529771Z"},"links":{"citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:65e1e2352653e700239343419cd688f26b11d2469cfc6ca3d36c6e0f8ce7e656","observation_id":"24b4dfd2-5973-415b-a8a2-58240add9b89","resolution":{"observed_at":"2026-08-07T05:19:29.581988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1507.05307","last_updated":"2015-07-19T16:55:08Z","snapshot_observed_at":"2026-08-14T22:39:51.012532Z","submitted_at":"2015-07-19T16:55:08Z","title":"2 Notes on Classes with Vapnik-Chervonenkis Dimension 1","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1507.05307","snapshot_observed_at":"2026-08-07T05:19:29.502696Z","title":"Limitations of Learning Via Embeddings in Euclidean Half Spaces","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.502696Z"},"links":{"cited_paper":"/paper/1507.05307","citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:6f673af044716a904d335b6fbeb25b4449dde44d7261d9ad8c30a4f77d84b26f","observation_id":"b4d8de35-91e8-4a16-8cba-335628a8a664","resolution":{"observed_at":"2026-08-07T05:19:29.502696Z","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":"2026-08-07T05:19:29.641562Z","title":"Robust Learning under Clean-Label Attack","venue":null,"work_id":"759f94ba-3119-4cfd-b834-426f7ef4f3fc","year":2020},"citing_paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-07T05:19:29.507889Z"},"links":{"citing_paper":"/paper/2608.06337"},"observation_digest":"sha256:4c887a7d8c1892f46065dec75c3025415f84b42176cc483a67e5f4aa9f9a30ce","observation_id":"dba2f80c-3526-419b-9731-7b4f94bc39cd","resolution":{"observed_at":"2026-08-07T05:19:29.646555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.06337","last_updated":"2026-08-06T17:45:32Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-13T14:23:32.419080Z","submitted_at":"2026-08-06T17:45:32Z","title":"Optimal Rates for Learning with Monotone Adversaries"},"reference_resolution":{"displayed":8,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":7},"total_outbound_references":8},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 1 inbound Pith citation observation for arXiv:2608.06337."}