{"as_of":"2026-08-16T20:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:84fff8d40a19724a46a9cc7e9066a286898e4af0840485b18eb5882362c628d7","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T15:20:56.526507Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-01T12:55:44.110449Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2209.08025","last_updated":"2022-09-16T16:10:08Z","snapshot_observed_at":"2026-08-16T16:31:57.975577Z","submitted_at":"2022-09-16T16:10:08Z","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.08025","snapshot_observed_at":"2026-08-11T15:20:56.526507Z","title":"Trustworthy reinforcement learning against intrinsic vulnerabilities: Robustness, safety, and generalizability","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.11138","last_updated":"2024-12-15T10:05:23Z","snapshot_observed_at":"2026-08-16T07:30:02.387836Z","submitted_at":"2024-12-15T10:05:23Z","title":"Safe Reinforcement Learning using Finite-Horizon Gradient-based Estimation","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-11T15:20:56.526507Z"},"links":{"cited_paper":"/paper/2209.08025","citing_paper":"/paper/2412.11138"},"observation_digest":"sha256:2840f3d86ee0471bdd27f5481f02b63ebc70316adc2cedc85b8ea7bf04ccf76f","observation_id":"9f83f98c-d743-4be3-8402-224876a928a8","resolution":{"observed_at":"2026-08-11T15:20:56.526507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.08025","last_updated":"2022-09-16T16:10:08Z","snapshot_observed_at":"2026-08-16T16:31:57.975577Z","submitted_at":"2022-09-16T16:10:08Z","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability","version":1},"cited_work":{"arxiv_id":"2209.08025","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.08025","snapshot_observed_at":"2026-07-01T12:55:44.110449Z","title":"Trustworthy reinforcement learning against intrinsic vulnerabilities: Robustness, safety, and generalizability","venue":null,"work_id":"3dc96f10-b0e0-4eb5-9b57-851e4f3e48c6","year":2022},"citing_paper":{"arxiv_id":"2605.06992","last_updated":"2026-05-07T22:16:03Z","snapshot_observed_at":"2026-08-16T19:07:24.079514Z","submitted_at":"2026-05-07T22:16:03Z","title":"Why Does Agentic Safety Fail to Generalize Across Tasks?","version":1},"reference_index":116,"source":"pdf_text","source_observed_at":"2026-05-11T01:55:38.554161Z"},"links":{"cited_paper":"/paper/2209.08025","citing_paper":"/paper/2605.06992"},"observation_digest":"sha256:28bf3df3da62189a99f6c6993671beb2bda2c9047dcb6d3437bd1bcb285eb082","observation_id":"026b617e-16f4-4599-80e3-7b958c772e0c","resolution":{"observed_at":"2026-05-11T04:06:00.233188Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.08025","last_updated":"2022-09-16T16:10:08Z","snapshot_observed_at":"2026-08-16T16:31:57.975577Z","submitted_at":"2022-09-16T16:10:08Z","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability","version":1},"cited_work":{"arxiv_id":"2209.08025","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2209.08025","snapshot_observed_at":"2026-07-01T12:55:44.110449Z","title":"Trustworthy reinforcement learning against intrinsic vulnerabilities: Robustness, safety, and generalizability","venue":null,"work_id":"3dc96f10-b0e0-4eb5-9b57-851e4f3e48c6","year":2022},"citing_paper":{"arxiv_id":"2606.30829","last_updated":"2026-06-29T19:00:01Z","snapshot_observed_at":"2026-08-09T01:11:24.442182Z","submitted_at":"2026-06-29T19:00:01Z","title":"Joint Chance Constrained Safe-Optimal Control","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-01T01:40:08.230114Z"},"links":{"cited_paper":"/paper/2209.08025","citing_paper":"/paper/2606.30829"},"observation_digest":"sha256:5053eeada8c39f434ea1d1cb431ebaa6453ff3ad913d602a1f2a37bfc508ae0d","observation_id":"5d1f60f7-36fa-46bd-97fd-124b188280f0","resolution":{"observed_at":"2026-07-01T12:55:44.112066Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2209.08025/citation-record","integrity":"/paper/2209.08025/integrity","json":"/paper/2209.08025/citation-record.json","paper":"/paper/2209.08025"},"outbound":[],"paper":{"arxiv_id":"2209.08025","last_updated":"2022-09-16T16:10:08Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T16:31:57.975577Z","submitted_at":"2022-09-16T16:10:08Z","title":"Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2209.08025."}