{"as_of":"2026-08-11T13:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2b14d772ae4b5592e74754f3224d662f303d02eae32644a3c89b7a04c578bd3d","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:39:19.389478Z","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":"2026-05-11T03:20:56.549164Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.01870","last_updated":"2024-06-04T00:45:37Z","snapshot_observed_at":"2026-08-07T17:01:22.032110Z","submitted_at":"2024-06-04T00:45:37Z","title":"Understanding Stochastic Natural Gradient Variational Inference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01870","snapshot_observed_at":"2026-08-06T18:39:19.389478Z","title":"Understanding stochastic natural gradient variational inference","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07853","last_updated":"2025-07-10T15:33:28Z","snapshot_observed_at":"2026-08-09T08:20:44.598736Z","submitted_at":"2025-07-10T15:33:28Z","title":"Optimization Guarantees for Square-Root Natural-Gradient Variational Inference","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-06T18:39:19.389478Z"},"links":{"cited_paper":"/paper/2406.01870","citing_paper":"/paper/2507.07853"},"observation_digest":"sha256:7c8ae8fca3dcb43aee6722643704dc9a2eafd4fc73904f58660e93fcf7eb3a49","observation_id":"dac3c5d5-b618-41f4-b1d3-08492394a615","resolution":{"observed_at":"2026-08-06T18:39:19.389478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01870","last_updated":"2024-06-04T00:45:37Z","snapshot_observed_at":"2026-08-07T17:01:22.032110Z","submitted_at":"2024-06-04T00:45:37Z","title":"Understanding Stochastic Natural Gradient Variational Inference","version":1},"cited_work":{"arxiv_id":"2406.01870","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.01870","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Wu and J","venue":null,"work_id":"bbf181bf-c0ea-45c6-99c7-6c2977773f0d","year":2024},"citing_paper":{"arxiv_id":"2605.07531","last_updated":"2026-05-08T10:02:51Z","snapshot_observed_at":"2026-08-11T02:38:57.179402Z","submitted_at":"2026-05-08T10:02:51Z","title":"SGD for Variational Inference: Tackling Unbounded Variance via Preconditioning and Dynamic Batching","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-11T02:30:54.859754Z"},"links":{"cited_paper":"/paper/2406.01870","citing_paper":"/paper/2605.07531"},"observation_digest":"sha256:ef0359241ef476008dc6cb13acfd9ab1afaf2aa04ac7faa23159e8679dcc2b29","observation_id":"21eba610-d924-4c6a-9170-74c29c2311d9","resolution":{"observed_at":"2026-05-11T03:20:56.551542Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2406.01870/citation-record","integrity":"/paper/2406.01870/integrity","json":"/paper/2406.01870/citation-record.json","paper":"/paper/2406.01870"},"outbound":[],"paper":{"arxiv_id":"2406.01870","last_updated":"2024-06-04T00:45:37Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T17:01:22.032110Z","submitted_at":"2024-06-04T00:45:37Z","title":"Understanding Stochastic Natural Gradient Variational Inference"},"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 2 inbound Pith citation observations for arXiv:2406.01870."}