{"as_of":"2026-08-07T20:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0f1d1ad1740f16cd062c30929ec8b4ba6f985fbd222849e06afdf3e5aeb30d03","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":"2026-08-07T06:34:17.273281+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":"2026-08-06T18:39:18.391365Z","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":"2026-07-04T20:40:08.506330Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.17641","last_updated":"2024-06-06T04:31:43Z","snapshot_observed_at":"2026-07-06T17:36:20.138864Z","submitted_at":"2024-02-27T16:11:05Z","title":"Variational Learning is Effective for Large Deep Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17641","snapshot_observed_at":"2026-08-06T18:39:18.391365Z","title":"Variational learning is effective for large deep networks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.07853","last_updated":"2025-07-10T15:33:28Z","snapshot_observed_at":"2026-08-07T09:32:16.763214Z","submitted_at":"2025-07-10T15:33:28Z","title":"Optimization Guarantees for Square-Root Natural-Gradient Variational Inference","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-06T18:39:18.391365Z"},"links":{"cited_paper":"/paper/2402.17641","citing_paper":"/paper/2507.07853"},"observation_digest":"sha256:1a18e116a712690760ce1b2b91710a5ff7cbefd15b21be33821413b4436e0b33","observation_id":"7d189caa-36d8-40a1-b892-3bf352f1fcca","resolution":{"observed_at":"2026-08-06T18:39:18.391365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17641","last_updated":"2024-06-06T04:31:43Z","snapshot_observed_at":"2026-07-06T17:36:20.138864Z","submitted_at":"2024-02-27T16:11:05Z","title":"Variational Learning is Effective for Large Deep Networks","version":2},"cited_work":{"arxiv_id":"2402.17641","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.17641","snapshot_observed_at":"2026-07-04T20:40:08.506330Z","title":"Variati onal Learning is Effective for Large Deep Networks","venue":null,"work_id":"6bd1968f-6b1b-4565-9331-e82c2eb42087","year":2024},"citing_paper":{"arxiv_id":"2510.03046","last_updated":"2026-04-08T14:57:20Z","snapshot_observed_at":"2026-07-06T22:31:40.462674Z","submitted_at":"2025-10-03T14:28:10Z","title":"Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-18T10:01:16.498310Z"},"links":{"cited_paper":"/paper/2402.17641","citing_paper":"/paper/2510.03046"},"observation_digest":"sha256:38c52aec1c416c1a8a83db21457c65baf4e5af22df3cd8bbe5cfc720ce503a46","observation_id":"e298c473-0caa-4aa3-9d62-4bc69c10f1c1","resolution":{"observed_at":"2026-05-18T10:02:31.767495Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17641","last_updated":"2024-06-06T04:31:43Z","snapshot_observed_at":"2026-07-06T17:36:20.138864Z","submitted_at":"2024-02-27T16:11:05Z","title":"Variational Learning is Effective for Large Deep Networks","version":2},"cited_work":{"arxiv_id":"2402.17641","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.17641","snapshot_observed_at":"2026-07-04T20:40:08.506330Z","title":"Variati onal Learning is Effective for Large Deep Networks","venue":null,"work_id":"6bd1968f-6b1b-4565-9331-e82c2eb42087","year":2024},"citing_paper":{"arxiv_id":"2606.25745","last_updated":"2026-06-24T12:15:23Z","snapshot_observed_at":"2026-07-07T00:00:12.737052Z","submitted_at":"2026-06-24T12:15:23Z","title":"Gaussian Mean Field Variational Inference can Overestimate Predictive Variance","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-06-25T19:48:28.532570Z"},"links":{"cited_paper":"/paper/2402.17641","citing_paper":"/paper/2606.25745"},"observation_digest":"sha256:83e902cbc6296a76c690cf65668eefa4bf2c92fc0915ded4d5bdaac12755cbbe","observation_id":"de62a576-759e-4e53-928a-17820d8b22d2","resolution":{"observed_at":"2026-07-04T20:40:08.507744Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.17641/citation-record","integrity":"/paper/2402.17641/integrity","json":"/paper/2402.17641/citation-record.json","paper":"/paper/2402.17641"},"outbound":[],"paper":{"arxiv_id":"2402.17641","last_updated":"2024-06-06T04:31:43Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T17:36:20.138864Z","submitted_at":"2024-02-27T16:11:05Z","title":"Variational Learning is Effective for Large Deep Networks"},"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 3 inbound Pith citation observations for arXiv:2402.17641."}