{"as_of":"2026-08-09T22:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:84f3218984106d2bedffdbba74c6a7f12ce186e8e869147bbe14fb7c5073bd34","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:54:11.213481Z","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":"2026-06-29T10:33:18.772880Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":"2209.10579","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-06-29T10:33:18.772880Z","title":"First-Order Policy Optimization for Robust Markov Decision Process","venue":null,"work_id":"90c3f7d8-1341-4353-8d55-2e93c8a02318","year":2022},"citing_paper":{"arxiv_id":"2408.16286","last_updated":"2026-04-24T03:11:36Z","snapshot_observed_at":"2026-08-03T07:01:54.251485Z","submitted_at":"2024-08-29T06:37:16Z","title":"Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form","version":5},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-05-23T21:58:56.180393Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2408.16286"},"observation_digest":"sha256:68a6d3b645e93c9c636bb1a3ba6ee9b6164b17d2db8c9d0acf04c2df016b225b","observation_id":"ad6ae68f-dc42-47b6-84b5-6ddabd41e6d9","resolution":{"observed_at":"2026-05-23T22:03:30.920726Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-08-07T05:54:11.213481Z","title":"First-order policy optimization for robust markov decision process","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07040","last_updated":"2026-07-13T02:54:44Z","snapshot_observed_at":"2026-08-08T08:44:26.506196Z","submitted_at":"2025-06-08T08:26:27Z","title":"Efficient Q-Learning and Actor-Critic Methods for Robust Average-Reward Reinforcement Learning","version":4},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T05:54:11.213481Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2506.07040"},"observation_digest":"sha256:b0ff400f297c2bbc517abb13e00f639afc618490df75500ce8de67252ab3463e","observation_id":"6b2800b2-64ec-4e46-b8c4-4e056478a7aa","resolution":{"observed_at":"2026-08-07T05:54:11.213481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":"2209.10579","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-06-29T10:33:18.772880Z","title":"First-Order Policy Optimization for Robust Markov Decision Process","venue":null,"work_id":"90c3f7d8-1341-4353-8d55-2e93c8a02318","year":2022},"citing_paper":{"arxiv_id":"2604.04795","last_updated":"2026-07-07T17:01:01Z","snapshot_observed_at":"2026-07-13T09:40:41.819534Z","submitted_at":"2026-04-06T16:01:59Z","title":"Sample Complexity for Markov Decision Processes and Stochastic Optimal Control with Static Risk Measures","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T19:31:33.732451Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2604.04795"},"observation_digest":"sha256:3ae5a69f6173ab33a0da79eaa29d7bcabe4c4113b29b13a86587bf1f0ff75e23","observation_id":"02e14e7c-de26-479c-bdd9-1439190d22ba","resolution":{"observed_at":"2026-05-10T22:50:51.101008Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":"2209.10579","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-06-29T10:33:18.772880Z","title":"First-Order Policy Optimization for Robust Markov Decision Process","venue":null,"work_id":"90c3f7d8-1341-4353-8d55-2e93c8a02318","year":2022},"citing_paper":{"arxiv_id":"2604.06039","last_updated":"2026-04-07T16:34:16Z","snapshot_observed_at":"2026-07-06T22:54:34.877944Z","submitted_at":"2026-04-07T16:34:16Z","title":"Value Mirror Descent for Reinforcement Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-10T19:07:41.863349Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2604.06039"},"observation_digest":"sha256:29e7b611248e452cb8f4326c5704f6b0b12523754f0bdb97590d528f4f200083","observation_id":"ca97eebf-6bc5-4ee6-9fb9-206d4d7de8ec","resolution":{"observed_at":"2026-05-10T23:30:49.576825Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":"2209.10579","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-06-29T10:33:18.772880Z","title":"First-Order Policy Optimization for Robust Markov Decision Process","venue":null,"work_id":"90c3f7d8-1341-4353-8d55-2e93c8a02318","year":2022},"citing_paper":{"arxiv_id":"2604.21177","last_updated":"2026-04-23T00:49:34Z","snapshot_observed_at":"2026-07-06T23:07:47.244208Z","submitted_at":"2026-04-23T00:49:34Z","title":"Revisiting Subgradient Dominance in Robust MDPs: Counterexamples, Hardness, and Sufficient Conditions","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-05-09T22:01:46.060931Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2604.21177"},"observation_digest":"sha256:8af990bb95e19e0d5b1bceb00799c2b730352eae5c31fb9a954fabc327df27a3","observation_id":"6f144f27-1a45-4766-a00a-be694147343a","resolution":{"observed_at":"2026-05-11T14:21:05.312687Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":"2209.10579","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-06-29T10:33:18.772880Z","title":"First-Order Policy Optimization for Robust Markov Decision Process","venue":null,"work_id":"90c3f7d8-1341-4353-8d55-2e93c8a02318","year":2022},"citing_paper":{"arxiv_id":"2605.10671","last_updated":"2026-05-11T14:53:03Z","snapshot_observed_at":"2026-07-06T23:22:37.355450Z","submitted_at":"2026-05-11T14:53:03Z","title":"Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Bellman-Operator Framework","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-12T04:01:07.589351Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2605.10671"},"observation_digest":"sha256:88eb93250bf9c40226bab2929297655c8898adf4dca71e34f3ae8baf9d25e261","observation_id":"748102b9-a20c-4ab4-8810-057dbc871299","resolution":{"observed_at":"2026-05-12T06:46:29.369993Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":"2209.10579","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-06-29T10:33:18.772880Z","title":"First-Order Policy Optimization for Robust Markov Decision Process","venue":null,"work_id":"90c3f7d8-1341-4353-8d55-2e93c8a02318","year":2022},"citing_paper":{"arxiv_id":"2605.28706","last_updated":"2026-05-27T16:32:02Z","snapshot_observed_at":"2026-07-06T23:38:14.056361Z","submitted_at":"2026-05-27T16:32:02Z","title":"Robust Markov Decision Processes on Continuous State Spaces","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-29T10:31:29.175140Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2605.28706"},"observation_digest":"sha256:f512be090864917de487f6c4a932db56124ecbbc12c5da5c20d24ea1058ce383","observation_id":"c6747c55-653f-44c3-8ec3-2862ce2e3095","resolution":{"observed_at":"2026-06-29T10:33:18.774758Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process","version":2},"cited_work":{"arxiv_id":"2209.10579","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.10579","snapshot_observed_at":"2026-06-29T10:33:18.772880Z","title":"First-Order Policy Optimization for Robust Markov Decision Process","venue":null,"work_id":"90c3f7d8-1341-4353-8d55-2e93c8a02318","year":2022},"citing_paper":{"arxiv_id":"2605.31309","last_updated":"2026-05-29T13:41:01Z","snapshot_observed_at":"2026-08-02T14:22:06.907671Z","submitted_at":"2026-05-29T13:41:01Z","title":"Non-Asymptotic Convergence of Stochastic Iterative Algorithms: A Lyapunov Framework","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-06-28T23:11:02.699220Z"},"links":{"cited_paper":"/paper/2209.10579","citing_paper":"/paper/2605.31309"},"observation_digest":"sha256:b224eec2d19ea4958e2dc4756f82c60efaabf3144581d90e8d33429c85a6e872","observation_id":"9e666d68-b161-47fe-8196-cd229dfebfd1","resolution":{"observed_at":"2026-06-28T23:12:46.683876Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2209.10579/citation-record","integrity":"/paper/2209.10579/integrity","json":"/paper/2209.10579/citation-record.json","paper":"/paper/2209.10579"},"outbound":[],"paper":{"arxiv_id":"2209.10579","last_updated":"2023-06-10T21:34:45Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T13:54:53.084096Z","submitted_at":"2022-09-21T18:10:28Z","title":"First-order Policy Optimization for Robust Markov Decision Process"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2209.10579."}