{"as_of":"2026-08-16T14:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f37c1ca03d03476b00f2275dcf80a98f6f992f6574ede7fcbd7321da7ea9b8dd","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T15:10:47.130797Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-10T15:10:47.293677Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2006.16958","last_updated":"2020-08-13T16:05:28Z","snapshot_observed_at":"2026-08-16T08:22:59.633656Z","submitted_at":"2020-06-30T16:52:23Z","title":"Evaluating the Performance of Reinforcement Learning Algorithms","version":2},"cited_work":{"arxiv_id":"2006.16958","doi":null,"metadata_source":"pith","pith_arxiv_id":"2006.16958","snapshot_observed_at":"2026-08-10T15:10:47.293677Z","title":"Evaluating the Performance of Reinforcement Learning Algorithms","venue":"cs.LG","work_id":"7e318c6d-62aa-4122-857e-1860ee1ab93d","year":2020},"citing_paper":{"arxiv_id":"2501.14443","last_updated":"2025-01-24T12:23:12Z","snapshot_observed_at":"2026-08-14T11:54:43.271872Z","submitted_at":"2025-01-24T12:23:12Z","title":"Learning more with the same effort: how randomization improves the robustness of a robotic deep reinforcement learning agent","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T15:10:47.130797Z"},"links":{"cited_paper":"/paper/2006.16958","citing_paper":"/paper/2501.14443"},"observation_digest":"sha256:bd6321e9c2abc84a2d8de6d86ee02bc02fd5c47590b4b7dfb0b511a344dffc54","observation_id":"b428c9ce-ee13-4da5-bc0b-f8df9bf36cb3","resolution":{"observed_at":"2026-08-10T15:10:47.298842Z","resolver_source":"local_arxiv","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/2006.16958/citation-record","integrity":"/paper/2006.16958/integrity","json":"/paper/2006.16958/citation-record.json","paper":"/paper/2006.16958"},"outbound":[],"paper":{"arxiv_id":"2006.16958","last_updated":"2020-08-13T16:05:28Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T08:22:59.633656Z","submitted_at":"2020-06-30T16:52:23Z","title":"Evaluating the Performance of Reinforcement Learning Algorithms"},"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 1 inbound Pith citation observation for arXiv:2006.16958."}