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Paper Citation Record · LEDGER

Coding schemes in neural networks learning classification tasks

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.16689.

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

pith.paper-citation-record.v1
2406.16689 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T23:13:38.928818Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T11:19:07.241392Z

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 a14938c3-eea0-43ab-bb14-0d2f1ff937f8 · inbound

Optimal generalisation and learning transition in extensive-width shallow neural networks near interpolation cites this paper.

Optimal generalisation and learning transition in extensive-width shallow neural networks near interpolation Coding schemes in neural networks learning classification tasks

Reference 2025

Resolution
malformed identifier
no resolver link, observed 2026-08-09T23:13:38.928818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T23:13:38.928818Z digest=sha256:1041f1fb80c22870b9d2b0248aeb225d5a58e88205ed1706d9d2f27fed4e03c0

Observation e4e4a116-4ea4-49f1-9615-9bee9b1828a7 · inbound

From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning cites this paper.

From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning Coding schemes in neural networks learning classification tasks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T05:36:55.533302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:36:55.533302Z digest=sha256:5ddb48305fa413db1da83e0384eac0e58fd0201e7a02ad8f182ac567425809e2

Observation a7e5d306-4a5b-4d61-ac6a-89532adfd56a · inbound

Adaptive kernel predictors from feature-learning infinite limits of neural networks cites this paper.

Adaptive kernel predictors from feature-learning infinite limits of neural networks Coding schemes in neural networks learning classification tasks

Reference 56

Resolution
verified exact
local_arxiv, observed 2026-08-08T11:19:07.245475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-08T11:19:07.018072Z digest=sha256:f61a97ae913ad91626a70f352c804195c20b73a8a3650628dc1afc75309a6ae4