Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Adam-family Methods with Decoupled Weight Decay in Deep Learning
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2310.08858.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:10:55.144839Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T20:45:48.880338Z
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 99dd7265-15b3-4db5-bc31-bd10b8b39e89 · inbound
Optimization Hyper-parameter Laws for Large Language Models cites this paper.
Optimization Hyper-parameter Laws for Large Language Models Adam-family Methods with Decoupled Weight Decay in Deep Learning
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T20:45:48.883210Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8a76bc57-5b4e-49be-acea-7ad9090d1fc4 · inbound
Mathematical analysis of the gradients in deep learning cites this paper.
Mathematical analysis of the gradients in deep learning Adam-family Methods with Decoupled Weight Decay in Deep Learning
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:10:55.144839Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 95cd25a5-35f1-4c4a-b5f1-288513702a52 · inbound
On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem cites this paper.
On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem Adam-family Methods with Decoupled Weight Decay in Deep Learning
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:48:25.612913Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.