Paper Citation Record · LEDGER

LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study

As of 12 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 2 inbound Pith citation observations for arXiv:2605.30385.

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

pith.paper-citation-record.v1
2605.30385 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T08:57:37.922572Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T08:47:18.055950Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

5 of 5 outbound references displayed

verified exact2
verified fuzzy0
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 437c946c-c19b-4cd9-8504-058c945d6b86 · outbound

This paper cites Concept control for LLM safety using radial basis function representations.ACM Digital Library, pages 220–232, 2025.

LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study Concept control for LLM safety using radial basis function representations.ACM Digital Library, pages 220–232, 2025

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-29T08:57:37.922572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcf9268f-9e5a-4a9b-9da2-db47826e5478 · outbound

This paper cites MLT, 2026.

LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study MLT, 2026

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-29T08:57:37.922572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc6a90cf-21a8-4c88-90ee-536778feccc7 · outbound

This paper cites A comprehensive survey on Kolmogorov Arnold networks (KAN).Preprint, pages 1–16, 2025.

LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study A comprehensive survey on Kolmogorov Arnold networks (KAN).Preprint, pages 1–16, 2025

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-29T09:03:15.985655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4250f239-017c-46c3-9205-0f7eecf1745b · outbound

This paper cites arXiv:2510:06660v1 [Link].

LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study arXiv:2510:06660v1 [Link]

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T08:57:37.922572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f3001e0-c199-4c7d-9d4b-376f0da1b862 · outbound

This paper cites Nonlinearity as rank: Generative low-rank adapter with radial basis functions.Preprint, pages 1–31, 2026.

LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study Nonlinearity as rank: Generative low-rank adapter with radial basis functions.Preprint, pages 1–31, 2026

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T09:03:15.988875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation 9da7235c-a838-410f-aa3e-ea66dfc2e654 · inbound

Piercing Gilbreath's Conjecture: From Deep Number Theory Insights to Fintech and Cybersecurity cites this paper.

Piercing Gilbreath's Conjecture: From Deep Number Theory Insights to Fintech and Cybersecurity LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-11T21:14:13.772368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e49f98c5-ef99-4026-badc-8e629989419b · inbound

Piercing Gilbreath's Conjecture: From Deep Number Theory Insights to Fintech and Cybersecurity cites this paper.

Piercing Gilbreath's Conjecture: From Deep Number Theory Insights to Fintech and Cybersecurity LLMs Without Deep Neural Networks: New Architecture, Benefits and Case Study

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T08:47:18.055950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.