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Paper Citation Record · LEDGER

Rethinking Neural Nonlinearity as Gating

As of 7 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.03148.

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

pith.paper-citation-record.v1
2607.03148 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T04:33:35.163697Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

25 of 25 outbound references displayed

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  • verified fuzzy0
  • unresolved19
  • parse uncertain0
  • malformed identifier5
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External citation measurements

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Outbound references

Observation 5b5436f0-8d91-4eb7-b691-8803cce259d2 · outbound

This paper cites Learning Activation Functions to Improve Deep Neural Networks.

Rethinking Neural Nonlinearity as Gating Learning Activation Functions to Improve Deep Neural Networks

Reference 1

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Observation 781d29f4-3b1d-475d-80c9-47ee7df91e61 · outbound

This paper cites Training Stochastic Model Recognition Algorithms as Networks can Lead to Maximum Mutual Information Estimation of Parameters.

Rethinking Neural Nonlinearity as Gating Training Stochastic Model Recognition Algorithms as Networks can Lead to Maximum Mutual Information Estimation of Parameters

Reference 2

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Observation 04da861e-8ff4-477a-ba3a-19d7be97c880 · outbound

This paper cites PRIME: A Novel Processing-in-Memory Architecture for Neural Network Computation in ReRAM-Based Main Memory.

Rethinking Neural Nonlinearity as Gating PRIME: A Novel Processing-in-Memory Architecture for Neural Network Computation in ReRAM-Based Main Memory

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 57122c4a-4ccf-4948-92c0-7ffda737ac00 · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Rethinking Neural Nonlinearity as Gating Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 4

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Observation 20d8910d-b851-43f5-b1ad-6ded3fd0b200 · outbound

This paper cites Maxout Networks.

Rethinking Neural Nonlinearity as Gating Maxout Networks

Reference 5

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Observation 2e3963c0-e020-422b-a9ca-6b0ccc2742ff · outbound

This paper cites On the Impact of the Activation func- tion on Deep Neural Networks Training.

Rethinking Neural Nonlinearity as Gating On the Impact of the Activation func- tion on Deep Neural Networks Training

Reference 6

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Observation 4d03bc0f-44e0-41fb-8d64-e7644109af5d · outbound

This paper cites Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification.

Rethinking Neural Nonlinearity as Gating Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Reference 7

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Observation 972e1884-2f19-4e46-aa20-08b9045aeb10 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Rethinking Neural Nonlinearity as Gating Gaussian Error Linear Units (GELUs)

Reference 8

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Observation da280fd5-a8c6-4acb-a55a-950b1edce5a8 · outbound

This paper cites Curvature Tuning: Provable Training- free Model Steering From a Single Parameter.

Rethinking Neural Nonlinearity as Gating Curvature Tuning: Provable Training- free Model Steering From a Single Parameter

Reference 9

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Observation 6a3bcf62-47d3-4677-a52c-b519eff7ec65 · outbound

This paper cites In-Memory Computing with Resistive Switching Devices.

Rethinking Neural Nonlinearity as Gating In-Memory Computing with Resistive Switching Devices

Reference 10

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Observation 1246c2e0-cc30-4ad5-ac37-4de875c9962a · outbound

This paper cites an unresolved cited work.

Rethinking Neural Nonlinearity as Gating Unresolved cited work

Reference 11

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Observation bf2f3223-a83d-4d95-a426-1de956a38019 · outbound

This paper cites Analog In-Memory Computing Attention Mechanism for Fast and Energy-Efficient Large Language Models.

Rethinking Neural Nonlinearity as Gating Analog In-Memory Computing Attention Mechanism for Fast and Energy-Efficient Large Language Models

Reference 12

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Observation f3411697-8fe9-474c-92b7-72ece09ce67d · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Rethinking Neural Nonlinearity as Gating KAN: Kolmogorov-Arnold Networks

Reference 13

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Observation 9b529d5b-6147-4381-b6b0-492a4eee5144 · outbound

This paper cites Rectifier Nonlinearities Improve Neural Network Acoustic Models.

Rethinking Neural Nonlinearity as Gating Rectifier Nonlinearities Improve Neural Network Acoustic Models

Reference 14

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Observation c52b5bbe-8036-4dd4-b1b0-3117424f4b0e · outbound

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

Rethinking Neural Nonlinearity as Gating Mish: A Self Regularized Non-Monotonic Activation Function

Reference 15

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Observation 45791a63-a9b6-45bb-a29e-1301714dfc7d · outbound

This paper cites Padé Activation Units: End- to-end Learning of Flexible Activation Functions in Deep Networks.

Rethinking Neural Nonlinearity as Gating Padé Activation Units: End- to-end Learning of Flexible Activation Functions in Deep Networks

Reference 16

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Observation f216dc78-e164-4437-8fe5-c63bb8c8f616 · outbound

This paper cites Rectified Linear Units Improve Restricted Boltzmann Machines.

Rethinking Neural Nonlinearity as Gating Rectified Linear Units Improve Restricted Boltzmann Machines

Reference 17

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Observation b868710e-78c6-4397-921e-5785eb20a59c · outbound

This paper cites Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors.

Rethinking Neural Nonlinearity as Gating Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors

Reference 18

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Observation c8996269-1715-46e2-a363-fc684b96d751 · outbound

This paper cites Searching for Activation Functions.

Rethinking Neural Nonlinearity as Gating Searching for Activation Functions

Reference 19

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Observation 40a1d3ad-2002-4a24-98a0-9cfbea1fd29a · outbound

This paper cites ImageNet Large Scale Visual Recognition Challenge.

Rethinking Neural Nonlinearity as Gating ImageNet Large Scale Visual Recognition Challenge

Reference 20

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Observation 3de00180-1532-4e79-8434-35482e2c269f · outbound

This paper cites Memory Devices and Applications for In-Memory Computing.

Rethinking Neural Nonlinearity as Gating Memory Devices and Applications for In-Memory Computing

Reference 21

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Observation 397c1aef-cd72-451e-b718-371f5b176886 · outbound

This paper cites ISAAC: A Convolutional Neural Network Accelerator with In-Situ Ana- log Arithmetic in Crossbars.

Rethinking Neural Nonlinearity as Gating ISAAC: A Convolutional Neural Network Accelerator with In-Situ Ana- log Arithmetic in Crossbars

Reference 22

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Observation 22c1e60f-0a01-475b-934d-6345d37c5bbb · outbound

This paper cites GLU Variants Improve Transformer.

Rethinking Neural Nonlinearity as Gating GLU Variants Improve Transformer

Reference 23

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Observation 90f272d1-b3be-424f-91fe-722c74c2988c · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture- of-Experts Layer.

Rethinking Neural Nonlinearity as Gating Outrageously Large Neural Networks: The Sparsely-Gated Mixture- of-Experts Layer

Reference 24

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Observation 5d43d356-2425-4eec-ac55-fc56c7ec4d1f · outbound

This paper cites Training Very Deep Net- works.

Rethinking Neural Nonlinearity as Gating Training Very Deep Net- works

Reference 25

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Pith citing papers

No inbound Pith citation observations are available.