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Paper Citation Record · LEDGER

Revisiting Glorot Initialization for Long-Range Linear Recurrences

As of 19 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2505.19827.

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

pith.paper-citation-record.v1
2505.19827 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:14:10.285013Z

measured 23 of 23 standing notices

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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.

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Source: cited_works

Reference resolution

23 of 23 outbound references displayed

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Outbound references

Observation 28b0d441-1fe1-43d0-98bd-0036051113d9 · outbound

This paper cites Plugging this back in: E[|λi|2k] = 1 nk+1 n−1X s=0 (k + s)! s! = 1 nk · 1 k + 1 · (k + n)! n!.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Plugging this back in: E[|λi|2k] = 1 nk+1 n−1X s=0 (k + s)! s! = 1 nk · 1 k + 1 · (k + n)! n!

Reference 1

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Observation a413ca8c-898a-42f0-a704-d82b43b42f99 · outbound

This paper cites an unresolved cited work.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Unresolved cited work

Reference 2

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Observation 5c957724-a709-45af-8f5a-d5d267addb7c · outbound

This paper cites Finite Depth and Width Corrections to the Neural Tangent Kernel.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Finite Depth and Width Corrections to the Neural Tangent Kernel

Reference 10

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Observation 9d32d309-9ab7-4dc3-9a8f-9c75042aba15 · outbound

This paper cites A Simple Way to Initialize Recurrent Networks of Rectified Linear Units.

Revisiting Glorot Initialization for Long-Range Linear Recurrences A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

Reference 13

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Observation bd0de1ba-056f-4e46-885f-bdb1688e6da2 · outbound

This paper cites Learning Longer Memory in Recurrent Neural Networks.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Learning Longer Memory in Recurrent Neural Networks

Reference 14

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This paper cites Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States

Reference 15

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Observation bc322ffe-e707-481a-9f24-a35bb12b1988 · outbound

This paper cites Deep Information Propagation.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Deep Information Propagation

Reference 16

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Observation 06cc42a0-dda5-4f30-810e-c14ac27a2f86 · outbound

This paper cites Why gradient clipping accelerates training: A theoretical justification for adaptivity.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Why gradient clipping accelerates training: A theoretical justification for adaptivity

Reference 19

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Observation bd71dc8d-1a06-4832-91c6-2db8472c225b · outbound

This paper cites Recurrent neural networks: vanishing and exploding gradients are not the end of the story.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Recurrent neural networks: vanishing and exploding gradients are not the end of the story

Reference 20

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Revisiting Glorot Initialization for Long-Range Linear Recurrences Unresolved cited work

Reference 22

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Observation 0c58e3a3-4f5e-474f-af8b-8753ec91f611 · outbound

This paper cites Proposition 11.2 (Complex-eigenvalue density [Edelman, 1997, Thm.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Proposition 11.2 (Complex-eigenvalue density [Edelman, 1997, Thm

Reference 24

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Observation bc32529b-6541-4655-ade9-10d35c404dc1 · outbound

This paper cites RotRNN: Modelling Long Sequences with Rotations.

Revisiting Glorot Initialization for Long-Range Linear Recurrences RotRNN: Modelling Long Sequences with Rotations

Reference 1994

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Observation 1ce58cf0-2b0c-4f24-8382-1bce330f9787 · outbound

This paper cites doi: 10.1006/jmva.1996.1653.

Revisiting Glorot Initialization for Long-Range Linear Recurrences doi: 10.1006/jmva.1996.1653

Reference 1997

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Observation 57bc73b2-90e3-4779-bbee-8ca1a62ef248 · outbound

This paper cites Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs

Reference 2001

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Observation d76924e3-c048-487a-8b59-ca5deff60629 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 2010

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Observation 6e69752c-4362-44d3-abba-04e2c13ff613 · outbound

This paper cites Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2014

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Observation 800c21cb-571a-49a0-ba9a-6d5cc87a852d · outbound

This paper cites Henaff, A.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Henaff, A

Reference 2015

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Observation a733c7b0-9461-4e77-aafa-10a3a0692dcc · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 2018

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Observation 132579d1-f713-4886-8670-231cbb0ae9cf · outbound

This paper cites Long Range Arena: A Benchmark for Efficient Transformers.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Long Range Arena: A Benchmark for Efficient Transformers

Reference 2019

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This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Efficiently Modeling Long Sequences with Structured State Spaces

Reference 2020

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This paper cites Layer Normalization.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Layer Normalization

Reference 2021

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Revisiting Glorot Initialization for Long-Range Linear Recurrences Sundermeyer, R

Reference 2022

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This paper cites Progress on the study of the Ginibre ensembles I: GinUE.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Progress on the study of the Ginibre ensembles I: GinUE

Reference 2024

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