Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.12965.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:51:27.023834Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T07:32:00.240307Z
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 17b6aebc-d6bb-4c76-96cb-2602c2fd3c56 · inbound
Unwrapping photonic reservoirs: enhanced expressivity via random Fourier encoding over stretched domains cites this paper.
Unwrapping photonic reservoirs: enhanced expressivity via random Fourier encoding over stretched domains Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:27.023834Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eae65544-8502-4737-b6ab-36733302fb90 · inbound
Fully analog end-to-end online training with real-time adaptibility on integrated photonic platform cites this paper.
Fully analog end-to-end online training with real-time adaptibility on integrated photonic platform Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:27:45.826181Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aac095b4-22d0-440d-8ac4-823f1d4843e7 · inbound
TRON: Trainable, architecture-reconfigurable random optical neural networks cites this paper.
TRON: Trainable, architecture-reconfigurable random optical neural networks Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T07:32:00.241545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.