{"as_of":"2026-08-08T23:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dda0305b324fd78ea372d0d4dd59b5b23bbfeafd5e5e220d7c0e9f34c799471e","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":"2026-08-08T06:32:00.761636+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":"2026-08-06T18:07:15.991152Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T18:07:21.117509Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2310.12688","last_updated":"2023-10-19T12:35:30Z","snapshot_observed_at":"2026-07-06T16:35:35.755643Z","submitted_at":"2023-10-19T12:35:30Z","title":"Compression of Recurrent Neural Networks using Matrix Factorization","version":1},"cited_work":{"arxiv_id":"2310.12688","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.12688","snapshot_observed_at":"2026-08-06T18:07:21.117509Z","title":"Compression of Recurrent Neural Networks using Matrix Factorization","venue":"cs.LG","work_id":"0db1b7c0-c41a-48dc-8fff-78cd3dbf12f4","year":2023},"citing_paper":{"arxiv_id":"2507.09428","last_updated":"2025-07-12T23:39:14Z","snapshot_observed_at":"2026-08-07T02:29:11.658442Z","submitted_at":"2025-07-12T23:39:14Z","title":"On Information Geometry and Iterative Optimization in Model Compression: Operator Factorization","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T18:07:15.991152Z"},"links":{"cited_paper":"/paper/2310.12688","citing_paper":"/paper/2507.09428"},"observation_digest":"sha256:9fee468af0f0ae122ce5521bd91bc7f4200a8b64635f12ad12f33020d3d1d82a","observation_id":"a082847a-7549-4cff-952d-55dc2887f0e4","resolution":{"observed_at":"2026-08-06T18:07:21.178066Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2310.12688/citation-record","integrity":"/paper/2310.12688/integrity","json":"/paper/2310.12688/citation-record.json","paper":"/paper/2310.12688"},"outbound":[],"paper":{"arxiv_id":"2310.12688","last_updated":"2023-10-19T12:35:30Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T16:35:35.755643Z","submitted_at":"2023-10-19T12:35:30Z","title":"Compression of Recurrent Neural Networks using Matrix Factorization"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2310.12688."}