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Paper Citation Record · LEDGER

Novel Saliency Analysis for the Forward Forward Algorithm

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.15365.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.15365 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:00:08.259021Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-11T19:59:06.806431Z

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 edff9064-2b66-4127-994b-8251ef7ddfdd · inbound

Quantized and Interpretable Learning Scheme for Deep Neural Networks in Classification Task cites this paper.

Quantized and Interpretable Learning Scheme for Deep Neural Networks in Classification Task Novel Saliency Analysis for the Forward Forward Algorithm

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T22:00:08.259021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:00:08.259021Z digest=sha256:c012e00ca36bc56ed5045cf610cdecf8a515db50ad13bbf28e0d6b03912f814d

Observation b34e6d2e-1820-497a-ad37-f9a2012df229 · inbound

Applying Machine Learning Tools for Urban Resilience Against Floods cites this paper.

Applying Machine Learning Tools for Urban Resilience Against Floods Novel Saliency Analysis for the Forward Forward Algorithm

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-11T19:59:06.813650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T19:59:06.763246Z digest=sha256:a591c180e87ec16483972105ca2562df489afd0ea0dc05cb662d0d5af31cefb6