{"as_of":"2026-08-13T04:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:db9ace29964658ef4184fa90e158769901fb350d50c191d30f9bb960e23d2e0d","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T14:11:18.565889Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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/2411.16743/citation-record","integrity":"/paper/2411.16743/integrity","json":"/paper/2411.16743/citation-record.json","paper":"/paper/2411.16743"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:19.737559Z","title":"Lectures on convex optimization","venue":null,"work_id":"19394c16-b638-4b72-ac30-fcd00a40297f","year":2018},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.385092Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:0b1f0c86ffbb5d531537716cd65e78df574766b2b3386277fa2d7c9756572ece","observation_id":"80fdcbc5-7d3a-4e0c-9a79-61bc46892cc9","resolution":{"observed_at":"2026-08-12T14:11:19.752417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:19.703983Z","title":"First-Order Methods in Optimization","venue":null,"work_id":"3a996fe9-e11b-4467-8c30-21443c230715","year":2017},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.390743Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:b36ca7aa6503f4cdb7584c067ce1accfb9657b106316e8d1861a266e53f5782d","observation_id":"50af7b2e-10b3-4b69-809f-139fc20de074","resolution":{"observed_at":"2026-08-12T14:11:19.715488Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:19.688716Z","title":"relative continuity for non-lipschitz nonsmooth convex optimization using stochastic (or deterministic) mirror descent","venue":null,"work_id":"30fe737c-de19-43c3-94e0-f261648df533","year":2019},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.395340Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:e0507cd7b04aa4b2c330b41b13526258b4c8c833b6f06837b4094619cdff7890","observation_id":"10435325-cf6a-48e8-8efe-9feddaaa372f","resolution":{"observed_at":"2026-08-12T14:11:19.693559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:18.399909Z","title":"A descent Lemma beyond Lipschitz gradient continuity: first-order method revisited and applications","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.399909Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:bf5baa84c370cf65148d5cb4c82fdf5076cb5ad70f77ea957e1c98e4c0cc1bb4","observation_id":"4d882b52-6550-43af-8097-942c666c11a4","resolution":{"observed_at":"2026-08-12T14:11:18.399909Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.405061Z","title":"Relatively smooth convex optimization by first-order methods, and applications","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.405061Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:13b3805a1eb7d382a9a9ae1cbc9a57b9c76c5a812c998c38331c3ebe33081de2","observation_id":"36f490a3-17f0-467c-8879-a63cfe76c828","resolution":{"observed_at":"2026-08-12T14:11:18.405061Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.409558Z","title":"Accelerated Bregman proximal gradient methods for relatively smooth convex optimization","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.409558Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:b69717778dfd236754fe7636e24e4facaf4b30424f8034945875167680eb00c0","observation_id":"680f357c-be2c-4592-ab44-485a51fc94c0","resolution":{"observed_at":"2026-08-12T14:11:18.409558Z","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":"10.1007/s10107-019-01449-1","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.887397Z","title":"Implementable tensor methods in unconstrained convex optimization","venue":null,"work_id":"b65dfbcd-1c1e-4697-a0ac-f3d3a9ab81a4","year":2021},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.414599Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:a073e43d273713c33a89c1a803a61dfb2d40e1ae056d4d8bbfa7453cba010762","observation_id":"c6fb2efb-58f7-4619-83fd-828385eb55a4","resolution":{"observed_at":"2026-08-12T14:11:18.892407Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10107-021-01727-x","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.865835Z","title":"Inexact accelerated high-order proximal-point methods","venue":null,"work_id":"aa47bc4f-b5bc-4301-bc04-696619d3d05f","year":2023},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.419531Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:da32ad15ecb397cfd2e6b7f9599e55b9cb274498e473c09e902a7d350c37aa3e","observation_id":"4440ee2b-35bb-4f05-b415-44fcbe06e50e","resolution":{"observed_at":"2026-08-12T14:11:18.874152Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:18.424636Z","title":"Optimization methods for large-scale machine learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.424636Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:a814ed2db29d64675291c466a830662b976f80f87c5b876130aa23ac1fa7d7fb","observation_id":"5508a24d-0536-4ae6-aee6-563913a09d36","resolution":{"observed_at":"2026-08-12T14:11:18.424636Z","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":"2026-08-12T14:11:19.669429Z","title":"Random search for hyper-parameter optimization","venue":null,"work_id":"8989974b-3456-4823-bccd-8efde1f728ee","year":2012},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.429905Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:f4cef25944a86fe4f97132be1e5f5480b3e52b39207cd774459baa90bd3edb34","observation_id":"2736045b-3fea-4177-8677-7db7e967adcd","resolution":{"observed_at":"2026-08-12T14:11:19.677542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:18.435793Z","title":"First-order methods of smooth convex optimization with inexact oracle","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.435793Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:36461ee2808817420e2ec15bb6fc4aca4b83327cce776cdf341527a451963dcd","observation_id":"d57253b0-7d51-46fd-a293-e1347cbf4c6f","resolution":{"observed_at":"2026-08-12T14:11:18.435793Z","resolver_source":null,"status":"malformed_identifier"},"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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.442628Z","title":"Inexact model: A framework for optimiza- tion and variational inequalities","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.442628Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:bf1993b47983a4833eae07f62cae448335af823b2c2805c73fad2aeae2aeeb08","observation_id":"47f4f8d4-6ad2-4b2d-8e2d-4b96b8180618","resolution":{"observed_at":"2026-08-12T14:11:18.442628Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.450144Z","title":"Universal intermediate gradient method for convex problems with inexact oracle","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.450144Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:27a73e41bd623dcb2a0f3a587509e09b6832d237af80a2484d83e072126c946d","observation_id":"2eb2ddd2-aa39-40da-9418-4eecea4cb3d2","resolution":{"observed_at":"2026-08-12T14:11:18.450144Z","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":"2026-08-12T14:11:19.648548Z","title":"Intermediate gradient methods for smooth convex problems with inexact oracle","venue":null,"work_id":"63aa4f0a-42d4-417c-a8b0-6a40960ac44d","year":2013},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.455252Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:1444669cef6202722ce4feaf6c246664e9264e9ba3dcd0a9829693e39b2c3885","observation_id":"0e7370ad-0f03-4a80-ad15-7e006fa4a47b","resolution":{"observed_at":"2026-08-12T14:11:19.655027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10957-016-0999-6","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.826090Z","title":"Stochastic intermediate gradient method for convex prob- lems with stochastic inexact oracle","venue":null,"work_id":"1a12e7a4-ef00-4902-bb86-faf5757950cd","year":2016},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.460398Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:12be12973dd76fbabb8b84c65b6843f73f3ada46ba5e6d519057ccbf534ba158","observation_id":"166c903f-4160-4247-a05b-f819debb4869","resolution":{"observed_at":"2026-08-12T14:11:18.830905Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:18.465407Z","title":"A fast iterative shrinkage-thresholding algorithm for linear inverse problems","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.465407Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:7c0b0aba9df16eb5fc521e22ac6f21b87abf7db45e6d3a5c45f6efdb55be164c","observation_id":"a95d649a-3729-49ee-b474-e1e8753f82ee","resolution":{"observed_at":"2026-08-12T14:11:18.465407Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.470398Z","title":"Gradient methods for minimizing composite functions","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.470398Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:1008893e44641b92b60beeac243547d143aae194ffa4424bd4f96bfb35e8ac3b","observation_id":"a805a796-2a5e-4fa2-b369-247c9469fa71","resolution":{"observed_at":"2026-08-12T14:11:18.470398Z","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":"10.1137/s105262340342782","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.756857Z","title":"Interior gradient and proximal methods for convex and conic op- timization","venue":null,"work_id":"ed3f968a-a4fb-49fa-b714-428646bedc26","year":2006},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.475166Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:825f6217ac66e07cde9ed1cf82c43a9382f62a8bd12c1100441b73657e829f0d","observation_id":"8cc954a1-00d7-4aec-8d06-09f4ff106cf6","resolution":{"observed_at":"2026-08-12T14:11:18.768112Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:19.618366Z","title":"Problem Complexity and Method Efficiency in Optimization","venue":null,"work_id":"3ff9ffce-8f46-4c21-9ff6-eb1ae89be647","year":1983},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.480221Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:8f4c9613ff6f5637d062f0a3b494689a2f82372d2cb31f854803405c09e633c8","observation_id":"2bdb9706-b46a-43ef-8ecc-c56d5f0523dc","resolution":{"observed_at":"2026-08-12T14:11:19.623039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1088/0266-5611/25/12/123006","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.737318Z","title":"Image deblurring with Poisson data: from cells to galaxies","venue":null,"work_id":"9a7951db-16ad-4ace-ba4d-bcc93fa02e19","year":2009},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.485631Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:9028b739b30a7bd0d03764da0d820c57542df77eb38bddf69eb46eaaa9e26aa0","observation_id":"be0c606a-47e7-4c32-83b3-d61b0fcfb243","resolution":{"observed_at":"2026-08-12T14:11:18.743355Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:18.492465Z","title":"Why least squares and maximum entropy an axiomatic approach to inference for linear iverse problems","venue":null,"work_id":null,"year":1991},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.492465Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:a441cae2941bf7dc551adc224c21853269f2daebf94c90962a60570960100058","observation_id":"23d36496-27af-43ba-af61-c68be1875124","resolution":{"observed_at":"2026-08-12T14:11:18.492465Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.497546Z","title":"Optimum design in regression problems","venue":null,"work_id":null,"year":1959},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.497546Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:431bbb43908358fee1768dd57ef9a4ee31b76b4eafb7bc160879af9d6f63b004","observation_id":"03a260c8-e857-4dd7-8b95-767cd32285bd","resolution":{"observed_at":"2026-08-12T14:11:18.497546Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.502007Z","title":"Optimal and efficient designs of experiments","venue":null,"work_id":null,"year":1969},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.502007Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:a1a454d9359597c7ff07142990fb6dda36149e6d59cb5919905122aeb8aec1e8","observation_id":"7531ba7e-eb1a-42a3-bcae-f4373de8c959","resolution":{"observed_at":"2026-08-12T14:11:18.502007Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.506983Z","title":"A simple convergence analysis of Bregman proximal gradient algorithm","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.506983Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:f7bff921cdf8156be29a3da5f6668b1b4a7a0d941a7aae1cd2ff597a2dde5033","observation_id":"11b72f38-0b48-44c4-97ef-26564fcd7d4f","resolution":{"observed_at":"2026-08-12T14:11:18.506983Z","resolver_source":null,"status":"malformed_identifier"},"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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.514425Z","title":"Convergence analysis of a proximal-like minimization algorithm us- ing Bregman functions","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.514425Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:d8429d2c104600a5c4bd50635640bd20d57817071c7c296e1b4d7797b05635ab","observation_id":"a74ffa0a-ef7a-4608-abcc-b6b45879065d","resolution":{"observed_at":"2026-08-12T14:11:18.514425Z","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":"2026-08-12T14:11:19.599581Z","title":"Learning supervised pagerank with gradient-based and gradient-free optimization methods","venue":null,"work_id":"b7939281-93e8-4b4e-b74b-727293a4af50","year":2016},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.518982Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:5bd99f10ace3a24ff873ccc6580b3d04aab8e8585cd249bbdc79fb8b718bcec5","observation_id":"e3e170e6-a64f-4a25-84ba-243cea36a5cb","resolution":{"observed_at":"2026-08-12T14:11:19.605618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:18.526073Z","title":"Universal gradient methods for convex optimization problems","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.526073Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:7ae4ad7d5a5f764923ef2660f8494e02a4d4524e4a5c8777f395637941771274","observation_id":"f1eaeb10-08bf-438b-8c53-a93e5e1b2ea3","resolution":{"observed_at":"2026-08-12T14:11:18.526073Z","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":"2026-08-12T14:11:19.581663Z","title":"Adaptive Algorithms for Relatively Lips- chitz Continuous Convex Optimization Problems","venue":null,"work_id":"2218b13c-5ddc-44f3-b7cd-27b8740b6b42","year":2023},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.534183Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:d306d32e08ab1099dcaea54d3c83961b75f2f5101b4586ef235da0483a01a540","observation_id":"e5c8091b-2e3d-402b-9eb6-96d0c7ac9695","resolution":{"observed_at":"2026-08-12T14:11:19.586649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1134/s0361768823060026","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.662930Z","title":"Adaptive Methods or Variational Inequalities with Relatively Smooth and Reletively Strongly Monotone Operators","venue":null,"work_id":"0847d73f-fcdc-4d1f-9be8-a40b20913eb7","year":2023},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.538221Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:6cb9627682d971d5d3fc82968814e8877f97c7176b03e4310fc8ed266801d3d3","observation_id":"562c30e6-43c0-48e5-891c-f02bbffda4ca","resolution":{"observed_at":"2026-08-12T14:11:18.680340Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:19.565208Z","title":"Lectures on modern convex optimization: analysis, algorithms, and engineering applications","venue":null,"work_id":"0acdf3af-723d-43f0-9cd9-4413e372fdb3","year":2001},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.543175Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:6195db8ab2cf1a1119c8c76287d27632a7fb42a532e82fda4d94cac59262ea62","observation_id":"e038a90d-c0ff-444e-b3d0-31c4f5e9759b","resolution":{"observed_at":"2026-08-12T14:11:19.572580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-12T14:11:18.553712Z","title":"A simplified view of first order methods for optimization","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.553712Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:c4a27299ad5fa10b967306a50cb81fd46d499d453b9674ceeb0cae29da015832","observation_id":"7ffe5bef-e43e-4c82-b99a-f72496208212","resolution":{"observed_at":"2026-08-12T14:11:18.553712Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T14:11:18.559945Z","title":"Pegasos: primal estimated sub-gradient solver for SVM","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.559945Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:d1679c15068c821904cddd334b6f0f4ecae99133f96f8cf183c7a45f8ce39d3f","observation_id":"d89f6d48-cc57-4e35-bb03-c7272a4ceb07","resolution":{"observed_at":"2026-08-12T14:11:18.559945Z","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":"2026-08-12T14:11:19.532219Z","title":"Bregman gradient methods for relatively-smooth optimization","venue":null,"work_id":"b339f59e-c469-4e9d-abba-d7c146848ee8","year":2021},"citing_paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T14:11:18.565889Z"},"links":{"citing_paper":"/paper/2411.16743"},"observation_digest":"sha256:9f47fc011ee3b0d9bd056d3b7dfcc9f215cce7b1661e29ab3ffe749ac01273b4","observation_id":"406a59b9-0e7b-4482-abcd-164a206d165c","resolution":{"observed_at":"2026-08-12T14:11:19.538050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.16743","last_updated":"2024-11-23T19:42:23Z","latest_version":1,"primary_category":"math.OC","snapshot_observed_at":"2026-08-12T16:35:41.738423Z","submitted_at":"2024-11-23T19:42:23Z","title":"Accelerated Bregman gradient methods for relatively smooth and relatively Lipschitz continuous minimization problems"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":6,"verified_fuzzy":10},"total_outbound_references":33},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2411.16743."}