{"as_of":"2026-08-07T15:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3ce15286f8727a6fb0683fdc9c828dde4dc50b0205ea9d14bdfb98e46ed4e483","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":"2026-08-07T06:34:17.273281+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":"2026-08-04T12:38:57.947144Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.03105","last_updated":"2026-07-30T05:46:37Z","snapshot_observed_at":"2026-08-07T07:00:35.214074Z","submitted_at":"2025-08-05T05:32:36Z","title":"Accelerating SGDM via Learning Rate and Batch Size Schedules: A Lyapunov-Based Analysis","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.03105","snapshot_observed_at":"2026-08-04T12:38:57.947144Z","title":"Accelerating sgdm via learning rate and batch size schedules: A lyapunov-based analysis","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.03164","last_updated":"2026-06-28T16:14:54Z","snapshot_observed_at":"2026-08-04T12:38:48.240318Z","submitted_at":"2025-10-03T16:35:56Z","title":"Why Do We Need Warm-up? A Theoretical Perspective","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-04T12:38:57.947144Z"},"links":{"cited_paper":"/paper/2508.03105","citing_paper":"/paper/2510.03164"},"observation_digest":"sha256:cfc98722e396ff4b4805022f3c750812af3012ac2919137dbd4105160712b642","observation_id":"b1228a4f-78df-4eb7-9f23-4784716f46cf","resolution":{"observed_at":"2026-08-04T12:38:57.947144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2508.03105/citation-record","integrity":"/paper/2508.03105/integrity","json":"/paper/2508.03105/citation-record.json","paper":"/paper/2508.03105"},"outbound":[],"paper":{"arxiv_id":"2508.03105","last_updated":"2026-07-30T05:46:37Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T07:00:35.214074Z","submitted_at":"2025-08-05T05:32:36Z","title":"Accelerating SGDM via Learning Rate and Batch Size Schedules: A Lyapunov-Based Analysis"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2508.03105."}