Paper Citation Record · LEDGER

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture

As of 19 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2501.14000.

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

pith.paper-citation-record.v1
2501.14000 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:52:17.699064Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact2
verified fuzzy7
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7d77585c-878d-4d0e-8def-14662a92dabc · outbound

This paper cites Understanding deep neural networks with rectified linear units.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Understanding deep neural networks with rectified linear units

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:52:18.143420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ac04f5c6-6cc2-4bfc-80d4-f028e8322b1b · outbound

This paper cites Reconciling modern machine-learning practice and the classical bias–variance trade-off.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Reconciling modern machine-learning practice and the classical bias–variance trade-off

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.593587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d165bcc7-1173-4b45-b208-d3392fb3ea06 · outbound

This paper cites The Consciousness Prior.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture The Consciousness Prior

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.598976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b90924a-308f-4e97-912c-81d361bef9b7 · outbound

This paper cites Learning activation functions in deep (spline) neural networks.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Learning activation functions in deep (spline) neural networks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:52:18.128132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1d68010e-f66d-4336-8d4e-b2958b9b056a · outbound

This paper cites A practical guide to splines.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture A practical guide to splines

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:52:18.113081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68d77798-7e16-4eec-90e2-187cd86ce5db · outbound

This paper cites Activation functions in deep learning: A comprehensive survey and benchmark.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Activation functions in deep learning: A comprehensive survey and benchmark

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:52:18.098201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 230e5096-51ea-4949-a616-24578ab084a6 · outbound

This paper cites Adaptive activation functions for deep networks.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Adaptive activation functions for deep networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:52:18.083332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76077e6a-daae-41f1-8624-85b7639b26d0 · outbound

This paper cites Exsplinet: An interpretable and expressive spline-based neural network.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Exsplinet: An interpretable and expressive spline-based neural network

Reference 8

Resolution: verified exact; doi, observed 2026-08-10T15:52:17.759739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 03a863f1-fc72-4930-ac66-22142b39d59f · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.630387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae3e16ff-d894-4ba1-b36b-e7b4f8231d8a · outbound

This paper cites Evolving parsimonious networks by mixing activation functions.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Evolving parsimonious networks by mixing activation functions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.634838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9518bb58-bc0f-40c2-b455-79e03d3e9a8f · outbound

This paper cites Deep linear networks with arbitrary loss: All local minima are global.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Deep linear networks with arbitrary loss: All local minima are global

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:52:18.060881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 81184d8f-fde6-4ab7-af80-dad7b7e05f60 · outbound

This paper cites Measuring the intrinsic dimension of objective landscapes.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Measuring the intrinsic dimension of objective landscapes

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:52:18.046008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dbbb1027-1727-48d9-a6d5-9bf376832351 · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture KAN: Kolmogorov-Arnold Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.648295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ffba83f-7c25-4da2-90eb-fe837b93987d · outbound

This paper cites Foundations of Spline Theory: B-Splines, Spline Approximation, and Hierarchical Refinement, pp.\ 1--76.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Foundations of Spline Theory: B-Splines, Spline Approximation, and Hierarchical Refinement, pp.\ 1--76

Reference 14

Resolution: verified exact; doi, observed 2026-08-10T15:52:17.746244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1f3f4444-892e-4ca8-91e1-949e6653f562 · outbound

This paper cites Mish: A Self Regularized Non-Monotonic Activation Function.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Mish: A Self Regularized Non-Monotonic Activation Function

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.656980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b11b28a8-e9e8-4ea1-b118-5784c5cd0202 · outbound

This paper cites Optimal approximation of piecewise smooth functions using deep relu neural networks.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Optimal approximation of piecewise smooth functions using deep relu neural networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.661492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af131933-6a58-4dba-8773-340455ce23b7 · outbound

This paper cites Searching for Activation Functions.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Searching for Activation Functions

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.665690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6f07088-81a2-497f-bbbb-b3ab34ea7d14 · outbound

This paper cites The kolmogorov–arnold representation theorem revisited.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture The kolmogorov–arnold representation theorem revisited

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.670197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b7788ef-30ba-4cd9-9b2b-a138b8ceca6d · outbound

This paper cites KAN or MLP: A Fairer Comparison.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture KAN or MLP: A Fairer Comparison

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.674611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 696e314d-a274-4da3-9aca-330093173fb7 · outbound

This paper cites Understanding deep learning requires rethinking generalization.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Understanding deep learning requires rethinking generalization

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.679085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2ece4f7-191d-438a-9621-094c0fd39a12 · outbound

This paper cites write newline.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture write newline

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.683684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaeac119-978d-40ac-928f-d6d47a3cd473 · outbound

This paper cites @esa (Ref.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture @esa (Ref

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.689421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 987ccc20-6282-42d3-80cd-74875ef51744 · outbound

This paper cites an unresolved cited work.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.694404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caa4626c-f65b-40bc-8024-c6d360062bcd · outbound

This paper cites an unresolved cited work.

Local Control Networks (LCNs): Optimizing Flexibility in Neural Network Data Pattern Capture Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T15:52:17.699064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.