Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the quantization of recurrent neural networks
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2101.05453.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T15:48:57.310365Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-09T15:48:58.003342Z
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 5ae69329-8856-4ca2-9149-a467e4040d1e · inbound
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity cites this paper.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity On the quantization of recurrent neural networks
Reference 28
- Resolution
- verified exact
- local_arxiv, observed 2026-08-09T15:48:58.007442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.