Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Cascaded Forward Algorithm for Neural Network Training
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.09728.
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 2026-08-06T19:14:00.471509Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T06:29:37.193382Z
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 c91c3250-efd5-449d-9bf5-93ce9b29fe64 · inbound
Energy-Efficient Supervised Learning with a Binary Stochastic Forward-Forward Algorithm cites this paper.
Energy-Efficient Supervised Learning with a Binary Stochastic Forward-Forward Algorithm The Cascaded Forward Algorithm for Neural Network Training
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:14:00.471509Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f04a1405-1615-4baa-b157-b12c8ecc8e5f · inbound
Breaking chains with trees: Deep learning with $\mathcal{O}(\log N)$ parallel time complexity cites this paper.
Breaking chains with trees: Deep learning with $\mathcal{O}(\log N)$ parallel time complexity The Cascaded Forward Algorithm for Neural Network Training
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T06:29:37.195310Z
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.
Observation 10f6d6da-d757-40b9-9acc-a677c60adebb · inbound
What Does Goodness Measure? A Likelihood-Ratio Account of Forward-Forward Learning cites this paper.
What Does Goodness Measure? A Likelihood-Ratio Account of Forward-Forward Learning The Cascaded Forward Algorithm for Neural Network Training
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T06:35:59.565515Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.