{"as_of":"2026-08-14T01:23:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:64860a3e495c12fe8afb15af44b929863919554bbfd59397885b4d3722692b5d","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":"2026-08-13T06:32:02.005865+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":"2026-08-10T17:01:13.785256Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.07082","last_updated":"2025-04-15T15:07:30Z","snapshot_observed_at":"2026-08-12T23:25:36.245619Z","submitted_at":"2024-07-09T17:55:23Z","title":"Can Learned Optimization Make Reinforcement Learning Less Difficult?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.07082","snapshot_observed_at":"2026-08-10T17:01:13.785256Z","title":"Can learned optimization make reinforcement learning less difficult? arXiv preprint arXiv:2407.07082, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12670","last_updated":"2025-06-19T15:01:04Z","snapshot_observed_at":"2026-08-13T17:49:02.176276Z","submitted_at":"2025-01-22T06:10:27Z","title":"Celo: Training Versatile Learned Optimizers on a Compute Diet","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T17:01:13.785256Z"},"links":{"cited_paper":"/paper/2407.07082","citing_paper":"/paper/2501.12670"},"observation_digest":"sha256:dadc2125c2e9ec7d563942b348c8375be5ca2a08d5fc9f95e0835a7833c7d1ac","observation_id":"2b79ed6f-1eb3-4c4a-8054-13d8babdbe4b","resolution":{"observed_at":"2026-08-10T17:01:13.785256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07082","last_updated":"2025-04-15T15:07:30Z","snapshot_observed_at":"2026-08-12T23:25:36.245619Z","submitted_at":"2024-07-09T17:55:23Z","title":"Can Learned Optimization Make Reinforcement Learning Less Difficult?","version":3},"cited_work":{"arxiv_id":"2407.07082","doi":"10.48550/arxiv.2407.07082","metadata_source":"pith","pith_arxiv_id":"2407.07082","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Can Learned Optimization Make Reinforcement Learning Less Difficult?","venue":"cs.LG","work_id":"2573e96d-2995-4762-ac7d-9e8459e181e6","year":2024},"citing_paper":{"arxiv_id":"2607.29559","last_updated":"2026-07-31T15:50:29Z","snapshot_observed_at":"2026-08-07T18:56:05.725689Z","submitted_at":"2026-07-31T15:50:29Z","title":"LEMUR: Learning to Align with Multi-Objective Reinforcement Learning from Preference Feedback","version":1},"reference_index":265,"source":"arxiv_source","source_observed_at":"2026-08-03T04:39:32.184113Z"},"links":{"cited_paper":"/paper/2407.07082","citing_paper":"/paper/2607.29559"},"observation_digest":"sha256:32048be5bda81cf130e8a0c3514277ceb72bb2cf6789f8832822456e00ef4810","observation_id":"fccf9ced-5d15-4f59-a74e-442bc1bb0471","resolution":{"observed_at":"2026-08-03T04:44:18.380119Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-10T21:38:18.334799+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-10T21:38:18.334799+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07082","last_updated":"2025-04-15T15:07:30Z","snapshot_observed_at":"2026-08-12T23:25:36.245619Z","submitted_at":"2024-07-09T17:55:23Z","title":"Can Learned Optimization Make Reinforcement Learning Less Difficult?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.07082","snapshot_observed_at":"2026-08-05T15:25:40.590903Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.03644","last_updated":"2026-08-04T13:29:00Z","snapshot_observed_at":"2026-08-11T03:36:19.110855Z","submitted_at":"2026-08-04T13:29:00Z","title":"Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details","version":1},"reference_index":264,"source":"arxiv_source","source_observed_at":"2026-08-05T15:25:40.590903Z"},"links":{"cited_paper":"/paper/2407.07082","citing_paper":"/paper/2608.03644"},"observation_digest":"sha256:d0e96fc2673c6a470f89fb7238c54ed21cc9085f3047c6543af0dd7dbfc12851","observation_id":"aebf1e82-e7d4-420b-b10e-aacea1cd344b","resolution":{"observed_at":"2026-08-05T15:25:40.590903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2407.07082/citation-record","integrity":"/paper/2407.07082/integrity","json":"/paper/2407.07082/citation-record.json","paper":"/paper/2407.07082"},"outbound":[],"paper":{"arxiv_id":"2407.07082","last_updated":"2025-04-15T15:07:30Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T23:25:36.245619Z","submitted_at":"2024-07-09T17:55:23Z","title":"Can Learned Optimization Make Reinforcement Learning Less Difficult?"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.07082."}