Pith. sign in

Paper Citation Record · LEDGER

Higher-Order Transformer Derivative Estimates for Explicit Pathwise Learning Guarantees

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.16563.

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

pith.paper-citation-record.v1
2405.16563 v2

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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:12:59.161173Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T04:45:56.947659Z

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 7c873cfe-aec8-48eb-9b9e-cbf4a8df8148 · inbound

Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data cites this paper.

Beyond Universal Approximation Theorems: Algorithmic Uniform Approximation by Neural Networks Trained with Noisy Data Higher-Order Transformer Derivative Estimates for Explicit Pathwise Learning Guarantees

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-05T13:12:59.161173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:12:59.161173Z digest=sha256:4a07d9096a6870b74d3e995b8cad1401845ea265a8f9354821609ce254ddf68d

Observation 0d37e30a-784a-4bf3-ad10-abc312806eec · inbound

Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity cites this paper.

Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity Higher-Order Transformer Derivative Estimates for Explicit Pathwise Learning Guarantees

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:45:56.954407Z

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.

source=pdf_text observed=2026-05-11T01:06:48.313418Z digest=sha256:92822c1e569b0320ba1244e1877aab89d5ae8ce73180b8206a4f8a5557b0adb8