{"as_of":"2026-08-09T00:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8a6432f4a0c2d96d2222a6c2146496c3bc012532404be497bc79927eb22682ae","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:23:35.361555Z","state":"measured"},{"denominator":24,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":24,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2505.22075/citation-record","integrity":"/paper/2505.22075/integrity","json":"/paper/2505.22075/citation-record.json","paper":"/paper/2505.22075"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:39.487534Z","title":"Robust optimization–a comprehensive survey,","venue":null,"work_id":"f992ce47-9717-48e0-a349-0208f6ae7e98","year":2007},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:33.329511Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:d5e00f06ba350b170f0d17f3f2a6d2b6a96c83c7f1e59b15bd8b359867f4345f","observation_id":"d6582170-4d4e-497f-a8de-997e75b1b045","resolution":{"observed_at":"2026-08-07T13:23:39.574194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:39.206790Z","title":"Theory and applica- tions of robust optimization,","venue":null,"work_id":"ecc64232-addd-4b34-bc89-0cd535808626","year":2011},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:33.393726Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:b87216792a0467422b7d3d47dc0126d3d262aa18b725cdacbf0f6406bbeb5a24","observation_id":"041212fb-b625-4d1c-b44b-657b32509576","resolution":{"observed_at":"2026-08-07T13:23:39.309282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:38.999069Z","title":"An outlook on robust model predictive control algorithms: Reflections on performance and computational aspects,","venue":null,"work_id":"5e33d3be-d7d4-4972-b418-65afe0ac321f","year":2018},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:33.536366Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:38763dac0386585c97bd80ba2400fc6e562dbdc837862cacf8444400ceb233f8","observation_id":"a80c2ff2-a91a-4e58-9cb3-455a25414c51","resolution":{"observed_at":"2026-08-07T13:23:39.098920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:38.752130Z","title":"Robust optimization in power systems: a tutorial overview,","venue":null,"work_id":"32dc5921-8bec-491b-b2b7-0c7fbc9a5b20","year":2022},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:33.643020Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:cfae767a51c6fc793d962ae8eb0d5fdeb4f523d95de66d900147fd27adb31bc5","observation_id":"310d4b2e-2fa3-41a0-bab4-6772705fda02","resolution":{"observed_at":"2026-08-07T13:23:38.860586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:38.547118Z","title":"Optimization under uncertainty in the era of big data and deep learning: When machine learning meets mathemat- ical programming,","venue":null,"work_id":"7991b71b-34d3-4454-b58a-9541caf91a13","year":2019},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:33.702669Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:b973d0be7ea01b94c882a789f28beef9663bc0e0a0a33a0267220fb4ad38e86e","observation_id":"88df798e-7bcc-44a9-88e0-0bb0d6062d89","resolution":{"observed_at":"2026-08-07T13:23:38.651863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:38.366196Z","title":"From data to decisions: Distributionally robust optimization is optimal,","venue":null,"work_id":"26d72410-4f80-44d7-9b18-e76a55160bcc","year":2021},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:33.790347Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:947ac67acad2c9ca10b2e5f7e926673f8a16c2c4f8878cd1973b0499cbf4c32f","observation_id":"77af18a0-b0a6-4d15-a77b-51e4f5a922a4","resolution":{"observed_at":"2026-08-07T13:23:38.468105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:38.094624Z","title":"Distributionally favorable optimization: A framework for data-driven decision-making with endogenous outliers,","venue":null,"work_id":"1fac6107-98a3-49a3-8eac-53987c95edf1","year":2024},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:33.931607Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:f91467aaa598a514a43cad2c1d4ffdff2d209c0a2a8d8d6ca006433c25c36329","observation_id":"193eabf0-ad24-4045-810a-d250979a7d4a","resolution":{"observed_at":"2026-08-07T13:23:38.224355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:37.826610Z","title":"Large-scale methods for distributionally robust optimization,","venue":null,"work_id":"923f02ab-6b51-464f-ac59-60d0b26198ec","year":2020},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.047849Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:c6a052ab813a6805eb410dd29a3f48afb649bf0da331e9f9572a29ed2632ec7f","observation_id":"34cdf552-4ea9-47a8-be7c-4283f740d325","resolution":{"observed_at":"2026-08-07T13:23:37.966527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:37.577611Z","title":"Distributionally robust optimization: A review on theory and applications,","venue":null,"work_id":"28868c3f-0eae-4b01-a930-e76d959aaf93","year":2022},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.158623Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:bd7d3c9b9351206909de3951f95858bd7ab613dac24ec8871c7191556bed704c","observation_id":"ce03fd84-13ec-4328-bc55-e18b81e9653b","resolution":{"observed_at":"2026-08-07T13:23:37.707999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:34.228312Z","title":"On the road between robust optimization and the scenario approach for chance constrained optimization problems,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.228312Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:90180d9277582ffb301e3f6cbf3a68fa22a014364b8dabc81beb8962fccc83b7","observation_id":"1f6c9cd8-46f3-42af-8bb3-da1a75932137","resolution":{"observed_at":"2026-08-07T13:23:34.228312Z","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":"2026-08-07T13:23:37.313274Z","title":"Data-driven robust optimiza- tion,","venue":null,"work_id":"2f2faaf8-d754-4b1b-83a9-f1b3a5718040","year":2018},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.333186Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:65c01430f23c3643bedc6f1073bfd31115897d723c6b7ef269b3628987fdfd2c","observation_id":"1aaa773e-6d13-4fd9-8a61-9f238cd2e6c5","resolution":{"observed_at":"2026-08-07T13:23:37.443881Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:37.060393Z","title":"Wasserstein distributionally robust optimization: Theory and appli- cations in machine learning,","venue":null,"work_id":"f7c6ad11-5943-40ba-a2f3-b26345aa66ae","year":2019},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.442692Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:4cb35470b131bffe3e62ed4ae0fcaf5d95cf6960474a0bd2f310322ca35270f0","observation_id":"a933ca4a-3634-42a4-adc6-5fa3bd111562","resolution":{"observed_at":"2026-08-07T13:23:37.181499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:36.786190Z","title":"Nonparametric estimation of uncertainty sets for robust optimization,","venue":null,"work_id":"cc9d1bf4-9e84-44a0-b15d-a82e550f6c88","year":2020},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.499515Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:cb76e2f9b4f47683d5a9cc2384e0e44e976a9738be7ba8b6f7222e18a81c0a94","observation_id":"769ae2ec-4b68-40f0-a0d4-e92c8c24453d","resolution":{"observed_at":"2026-08-07T13:23:36.953920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:36.525068Z","title":"Satisficing models under uncertainty,","venue":null,"work_id":"40343ec5-7cf2-47e9-8ff5-00dd1b29003b","year":2022},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.555829Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:ad5a69bb82da25ead419432635ad8ccc821e0dc6ab47fcdd488112438511856d","observation_id":"91c781b2-1c02-41df-9331-4079b9e1e314","resolution":{"observed_at":"2026-08-07T13:23:36.633836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:36.377144Z","title":"Robust optimal control with adjustable uncertainty sets,","venue":null,"work_id":"3ea6ff46-e4f6-4721-8658-ae9f6565d5cb","year":2017},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.656768Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:784b88d09806800db304f435f6dd365a0e88e388cce48ce186f273c85954bd0a","observation_id":"792942e7-ce95-4358-8e66-b1f5b447fd7b","resolution":{"observed_at":"2026-08-07T13:23:36.463918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:36.216250Z","title":"Robust risk-aware model predictive control of linear systems with bounded disturbances,","venue":null,"work_id":"53f1a123-98f4-4344-b6a0-f5646e9776e8","year":2022},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.734350Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:3bf5bf0b078918fa70abcd9533dfa74bf98b589a26d37fd19d5539791f0fcacd","observation_id":"ebee690b-14d6-4bf4-b290-857df8759819","resolution":{"observed_at":"2026-08-07T13:23:36.316982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:36.081199Z","title":"Opportunistic safety outside the maximal controlled invariant set,","venue":null,"work_id":"0666aa1e-6e85-4f2f-af34-ae4cea8214d0","year":2023},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.855232Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:7765d734152d02d8748201cafb66fddade098c390e831b2c3dbd8630494bad8d","observation_id":"12403eae-f1a9-4e5d-b014-525dedb23386","resolution":{"observed_at":"2026-08-07T13:23:36.133938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:35.959452Z","title":"Learning-based rigid tube model predictive control,","venue":null,"work_id":"fee0b002-2415-4cf9-9dde-a1e1414b556a","year":2024},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.926686Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:d1a1b46255e50fb57e34ac943e12c61529eb926eaadfd730556bffd3285d36f1","observation_id":"b3711230-f93d-4f54-bceb-c7c237c69a27","resolution":{"observed_at":"2026-08-07T13:23:36.023239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:35.828940Z","title":"Robust optimization,","venue":null,"work_id":"49456c30-9cc8-47db-aa99-9077c8c091e9","year":2009},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:34.995280Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:f8f4ddfa98fe38ade51f17a5b375ff15386afd83962747ecd1b134e9c80c2ef3","observation_id":"54114ad1-8dff-40ab-b7da-d602178d83c0","resolution":{"observed_at":"2026-08-07T13:23:35.894283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:35.712431Z","title":"Deriving robust counter- parts of nonlinear uncertain inequalities,","venue":null,"work_id":"f71a1f07-34cb-419d-952d-7f9c343f23fa","year":2015},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:35.080089Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:1abfa4aa8b279c909d506e22a9034c63f69905a9464221553dcc44d5b5119fdf","observation_id":"17737dd8-a404-46a9-853c-0e6d44a7c257","resolution":{"observed_at":"2026-08-07T13:23:35.767129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:35.168973Z","title":"Data-driven distributionally robust optimization using the wasserstein metric: Performance guar- antees and tractable reformulations,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:35.168973Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:be9ec9e70b1f06abd7dda070d68dabe724bbd06db940e97ee61d6c7c021fa155","observation_id":"36bb0d01-0c8a-4930-9591-f64f53e9bc22","resolution":{"observed_at":"2026-08-07T13:23:35.168973Z","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":"2026-08-07T13:23:35.222921Z","title":"On the implementation of an interior- point filter line-search algorithm for large-scale nonlinear program- ming,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:35.222921Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:61726937a053e65efe816b6e03f1242cc7ae0aad2c976eaa36dbf94a18a7af8f","observation_id":"1f4b7f39-acbb-45b8-8680-fa3f21ca3a1c","resolution":{"observed_at":"2026-08-07T13:23:35.222921Z","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":"2026-08-07T13:23:35.552558Z","title":"Power systems test case archive","venue":null,"work_id":"c1d038b5-5bf3-41b3-82bd-176ead2a5872","year":1993},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:35.285943Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:0ceff71bf404a5347b3635bc24bfc0720ffef46b01ed6de98fab8f9e981a505f","observation_id":"f40fc9c6-58aa-45a3-a4c3-d1dda74a0aa4","resolution":{"observed_at":"2026-08-07T13:23:35.606091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:23:35.443338Z","title":"Matpower 5.0 documentation","venue":null,"work_id":"1427b466-e05b-46e4-af1a-7f6e24afe95d","year":2020},"citing_paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:23:35.361555Z"},"links":{"citing_paper":"/paper/2505.22075"},"observation_digest":"sha256:c16ca5017e32a17079d89463c113e344c9fe4b7927cdc2ee833218004facf606","observation_id":"50016b7d-3fd9-4424-b088-9fb75cdc4ae7","resolution":{"observed_at":"2026-08-07T13:23:35.481563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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"}}],"paper":{"arxiv_id":"2505.22075","last_updated":"2025-05-28T07:56:08Z","latest_version":1,"primary_category":"math.OC","snapshot_observed_at":"2026-08-07T13:13:17.768623Z","submitted_at":"2025-05-28T07:56:08Z","title":"Data-Driven Adjustable Robust Optimization"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":21},"total_outbound_references":24},"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 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2505.22075."}