Paper Citation Record · LEDGER

FlexAct: Why Learn when you can Pick?

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2601.06441.

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

pith.paper-citation-record.v1
2601.06441 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:27:30.228258Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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 exact0
verified fuzzy0
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 31bc019f-874f-4f38-92ba-b3084291b05a · outbound

This paper cites Learning Activation Functions: A new paradigm for understanding Neural Networks.

FlexAct: Why Learn when you can Pick? Learning Activation Functions: A new paradigm for understanding Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.167054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a7ff5f7-cd19-4c9e-892c-8df1fcbe4199 · outbound

This paper cites Adaptively Customizing Activation Functions for Various Layers.

FlexAct: Why Learn when you can Pick? Adaptively Customizing Activation Functions for Various Layers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.171106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 804835c1-5396-41a8-9569-97599cacca8f · outbound

This paper cites Scaling Laws for Neural Language Models.

FlexAct: Why Learn when you can Pick? Scaling Laws for Neural Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.179400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 411bd474-9487-43a1-8a0d-907d378db3ab · outbound

This paper cites GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution.

FlexAct: Why Learn when you can Pick? GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.183067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5773cbfc-c11d-4e0b-aacc-7f11b2f4dcb3 · outbound

This paper cites URLhttp://dx.doi.org/10.1109/ICPR.2018.8545362.

FlexAct: Why Learn when you can Pick? URLhttp://dx.doi.org/10.1109/ICPR.2018.8545362

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.190248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27eb89ec-f8d6-4bcd-b166-1a6d95b2fdcf · outbound

This paper cites Comparison of non-linear activation functions for deep neural networks on MNIST classification task.

FlexAct: Why Learn when you can Pick? Comparison of non-linear activation functions for deep neural networks on MNIST classification task

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.197705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0f83012-1c77-4bc8-8f05-cd85d83b87da · outbound

This paper cites Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice.

FlexAct: Why Learn when you can Pick? Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.201770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 829f2f89-e2c3-423b-bbc2-53d17c190b2a · outbound

This paper cites Searching for Activation Functions.

FlexAct: Why Learn when you can Pick? Searching for Activation Functions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.205378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e6da1b0-e4a2-4e1f-b82e-6bc16fcb37e9 · outbound

This paper cites URLhttps://dx.doi.org/10.1088/1741-2552/ac115d.

FlexAct: Why Learn when you can Pick? URLhttps://dx.doi.org/10.1088/1741-2552/ac115d

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.213045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4500b0dd-dd32-4a99-9830-571f0828e659 · outbound

This paper cites Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning.

FlexAct: Why Learn when you can Pick? Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.216522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81128ec8-2239-4a77-9ecb-c77236ec93d7 · outbound

This paper cites SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness.

FlexAct: Why Learn when you can Pick? SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.220341Z

Source-reported events for the cited work

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Observation f90fdc79-5489-44cf-aa10-79076bd78829 · outbound

This paper cites Understanding deep learning requires rethinking generalization.

FlexAct: Why Learn when you can Pick? Understanding deep learning requires rethinking generalization

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.224570Z

Source-reported events for the cited work

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Observation 157be54b-1a20-4dff-be23-9fbc6d4480ea · outbound

This paper cites Fixup Initialization: Residual Learning Without Normalization.

FlexAct: Why Learn when you can Pick? Fixup Initialization: Residual Learning Without Normalization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.228258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caf43ddc-5852-4a3a-90a4-9fa420d7d244 · outbound

This paper cites Activation Functions: Comparison of trends in Practice and Research for Deep Learning.

FlexAct: Why Learn when you can Pick? Activation Functions: Comparison of trends in Practice and Research for Deep Learning

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.193902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6944238d-3b8c-44ee-b444-9658e2d2471d · outbound

This paper cites Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.

FlexAct: Why Learn when you can Pick? Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.209291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74a6d9cc-ca55-42f0-b99a-51e3b3118e04 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

FlexAct: Why Learn when you can Pick? BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.155044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c8dec2a-3c0e-4da4-8c8a-892208fe8eec · outbound

This paper cites Layer Normalization.

FlexAct: Why Learn when you can Pick? Layer Normalization

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.142393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11c33fd4-3c5b-42d8-bcbc-a27ce772912c · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

FlexAct: Why Learn when you can Pick? Categorical Reparameterization with Gumbel-Softmax

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.175509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67f8ebf0-2c21-4eb7-852c-8173c0f75cc5 · outbound

This paper cites The Shattered Gradients Problem: If resnets are the answer, then what is the question?.

FlexAct: Why Learn when you can Pick? The Shattered Gradients Problem: If resnets are the answer, then what is the question?

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.146537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 112f9c90-be7b-4ec1-b0de-d52d22eb9acf · outbound

This paper cites Deep Learning using Rectified Linear Units (ReLU).

FlexAct: Why Learn when you can Pick? Deep Learning using Rectified Linear Units (ReLU)

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.137358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4495f8c4-bb49-4f87-a265-d3d498e51634 · outbound

This paper cites Rational neural networks.

FlexAct: Why Learn when you can Pick? Rational neural networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.150931Z

Source-reported events for the cited work

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Observation 140026bb-0753-455e-bf1d-7e326a5f90da · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

FlexAct: Why Learn when you can Pick? An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.159102Z

Source-reported events for the cited work

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Observation 40cf83a4-dcc1-4add-af58-ce5831ba0ba9 · outbound

This paper cites Activation Functions in Deep Learning: A Comprehensive Survey and Benchmark.

FlexAct: Why Learn when you can Pick? Activation Functions in Deep Learning: A Comprehensive Survey and Benchmark

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.163142Z

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Observation 00013af1-7ebd-4cd4-bff4-04003a97ab8b · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

FlexAct: Why Learn when you can Pick? KAN: Kolmogorov-Arnold Networks

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:30.186715Z

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Pith citing papers

No inbound Pith citation observations are available.