Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Large Scale Private Learning via Low-rank Reparametrization
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2106.09352.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-24T04:21:49.775278Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T04:23:52.774563Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 1431930a-9364-4aad-946b-9b8b5bab14f4 · inbound
Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions cites this paper.
Industry Practitioners Perspectives on AI Model Quality: Perceptions, Challenges, and Solutions Large Scale Private Learning via Low-rank Reparametrization
Reference 140
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T04:23:52.776326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.