{"as_of":"2026-08-11T14:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e79e1c9e1de441080f28827186591bc9726ab1b0eab3debabd8084375d902af0","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T04:56:22.453068Z","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":"2026-06-29T08:23:15.210988Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03372","snapshot_observed_at":"2026-08-11T04:56:22.453068Z","title":"Elementary analysis of policy gradient methods.arxiv:2404.03372, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18279","last_updated":"2024-12-24T08:39:35Z","snapshot_observed_at":"2026-08-11T04:48:34.949240Z","submitted_at":"2024-12-24T08:39:35Z","title":"Improving Multi-Step Reasoning Abilities of Large Language Models with Direct Advantage Policy Optimization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T04:56:22.453068Z"},"links":{"cited_paper":"/paper/2404.03372","citing_paper":"/paper/2412.18279"},"observation_digest":"sha256:c9cd4f2a05242aaa54188f8fd617e1d2bcc0a3ad9865591d320a9dd83dae24b8","observation_id":"53de0872-a891-4fab-9ada-976fdf1488b8","resolution":{"observed_at":"2026-08-11T04:56:22.453068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods","version":2},"cited_work":{"arxiv_id":"2404.03372","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03372","snapshot_observed_at":"2026-06-29T08:23:15.210988Z","title":"Elementary analysis of policy gradient methods","venue":null,"work_id":"c2bfbf70-d7d9-42cb-94b1-bd65181249bd","year":2016},"citing_paper":{"arxiv_id":"2509.09838","last_updated":"2026-05-11T21:29:26Z","snapshot_observed_at":"2026-07-06T22:29:01.585836Z","submitted_at":"2025-09-11T20:34:08Z","title":"Dissecting Discrete Soft Actor-Critic: Limitations and Principled Alternatives","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-05-18T17:05:36.100114Z"},"links":{"cited_paper":"/paper/2404.03372","citing_paper":"/paper/2509.09838"},"observation_digest":"sha256:42075bdf5ee8f7149e4dd89c075511bb6eb301b1a791d6d95dd45504c0ac8a66","observation_id":"63fd8aad-413b-403f-9e3f-ae8aa635afec","resolution":{"observed_at":"2026-05-18T17:06:39.778309Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods","version":2},"cited_work":{"arxiv_id":"2404.03372","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03372","snapshot_observed_at":"2026-06-29T08:23:15.210988Z","title":"Elementary analysis of policy gradient methods","venue":null,"work_id":"c2bfbf70-d7d9-42cb-94b1-bd65181249bd","year":2016},"citing_paper":{"arxiv_id":"2602.01505","last_updated":"2026-05-06T16:04:38Z","snapshot_observed_at":"2026-08-11T05:16:16.621039Z","submitted_at":"2026-02-02T00:35:42Z","title":"Optimal Sample Complexity for Single Time-Scale Actor-Critic with Momentum","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-16T08:12:57.430291Z"},"links":{"cited_paper":"/paper/2404.03372","citing_paper":"/paper/2602.01505"},"observation_digest":"sha256:5ba69ac92d0fe1b98b197c4b5f770f09106e4a49eff8f11a5758ee446f7ba481","observation_id":"b09d0da5-99b1-4cb7-a56b-ed62587608c8","resolution":{"observed_at":"2026-05-16T08:17:36.505694Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods","version":2},"cited_work":{"arxiv_id":"2404.03372","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03372","snapshot_observed_at":"2026-06-29T08:23:15.210988Z","title":"Elementary analysis of policy gradient methods","venue":null,"work_id":"c2bfbf70-d7d9-42cb-94b1-bd65181249bd","year":2016},"citing_paper":{"arxiv_id":"2604.25872","last_updated":"2026-04-28T17:10:15Z","snapshot_observed_at":"2026-07-06T23:11:39.318906Z","submitted_at":"2026-04-28T17:10:15Z","title":"When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-07T16:24:43.688967Z"},"links":{"cited_paper":"/paper/2404.03372","citing_paper":"/paper/2604.25872"},"observation_digest":"sha256:cac02912909132b46c70a429063e972593d5d3d7ab63faeb63091a9f550e47f3","observation_id":"78f1a5c5-0921-403e-ae92-c241984b705b","resolution":{"observed_at":"2026-05-11T23:41:19.581704Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods","version":2},"cited_work":{"arxiv_id":"2404.03372","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.03372","snapshot_observed_at":"2026-06-29T08:23:15.210988Z","title":"Elementary analysis of policy gradient methods","venue":null,"work_id":"c2bfbf70-d7d9-42cb-94b1-bd65181249bd","year":2016},"citing_paper":{"arxiv_id":"2605.30648","last_updated":"2026-05-28T23:05:45Z","snapshot_observed_at":"2026-07-06T23:39:53.132531Z","submitted_at":"2026-05-28T23:05:45Z","title":"Convergence of Steepest Descent and Adam under Non-Uniform Smoothness","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-29T08:19:12.076347Z"},"links":{"cited_paper":"/paper/2404.03372","citing_paper":"/paper/2605.30648"},"observation_digest":"sha256:d46e4035a1e34dd0c049b40485db3a1bcfee3ed71f100c4abb89e809ca102a38","observation_id":"d2d089cb-e58d-4fa2-8d19-30d3af83bed7","resolution":{"observed_at":"2026-06-29T08:23:15.212279Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03372","snapshot_observed_at":"2026-07-14T04:17:12.534820Z","title":"arxiv:2404.03372 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11626","last_updated":"2026-07-13T14:45:07Z","snapshot_observed_at":"2026-07-16T23:19:55.768663Z","submitted_at":"2026-07-13T14:45:07Z","title":"On the Policy Convergence of Policy Mirror Descent Methods","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-14T04:17:12.534820Z"},"links":{"cited_paper":"/paper/2404.03372","citing_paper":"/paper/2607.11626"},"observation_digest":"sha256:7f1fa493f01c226bebfcd4e7f4b996963f74269d20fe02bd34e9959d8146406c","observation_id":"6193d972-ea4e-4cff-b657-5a0c79578cce","resolution":{"observed_at":"2026-07-14T04:17:12.534820Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.03372","snapshot_observed_at":"2026-08-01T04:04:00.536160Z","title":"arXiv preprint arXiv:2404.03372 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22982","last_updated":"2026-07-25T01:37:26Z","snapshot_observed_at":"2026-08-05T03:41:36.284702Z","submitted_at":"2026-07-25T01:37:26Z","title":"Finite-Time Analysis of the Natural Policy Gradient in Finite-Horizon Markov Decision Processes","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-01T04:04:00.536160Z"},"links":{"cited_paper":"/paper/2404.03372","citing_paper":"/paper/2607.22982"},"observation_digest":"sha256:52d2bd03c9f13f0f6b8ee464f8c04d41b16bfa8931a96f81c727ed4d370cf294","observation_id":"030f074d-1a7c-4837-b5c5-ef81206316d4","resolution":{"observed_at":"2026-08-01T04:04:00.536160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.03372/citation-record","integrity":"/paper/2404.03372/integrity","json":"/paper/2404.03372/citation-record.json","paper":"/paper/2404.03372"},"outbound":[],"paper":{"arxiv_id":"2404.03372","last_updated":"2024-04-11T02:59:07Z","latest_version":2,"primary_category":"math.OC","snapshot_observed_at":"2026-08-05T09:15:12.934589Z","submitted_at":"2024-04-04T11:16:16Z","title":"Elementary Analysis of Policy Gradient Methods"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2404.03372."}