Paper Citation Record · LEDGER

Parallelizable memory recurrent units

As of 30 July 2026, this Paper Citation Record lists 39 of 39 outbound references and 5 inbound Pith citation observations for arXiv:2601.09495.

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

pith.paper-citation-record.v1
2601.09495 v3

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-21T16:04:48.315986Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-30T06:33:22.917629+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T22:21:16.608148Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-01T14:05:46.356220Z

Reference resolution

39 of 39 outbound references displayed

verified exact0
verified fuzzy37
unresolved1
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b980433e-6e52-49dd-b656-3cdf36e903d0 · outbound

This paper cites Long Short-Term Memory.

Parallelizable memory recurrent units Long Short-Term Memory

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.053127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation d49c66c7-e50e-4405-8e28-30054d2c1853 · outbound

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

Parallelizable memory recurrent units Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.028787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 5845ce9c-c38f-4c48-af83-a9599c793bcb · outbound

This paper cites Attention is All you Need.

Parallelizable memory recurrent units Attention is All you Need

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.043962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 2e90516e-207b-4160-b741-da9c7d9b1b7c · outbound

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

Parallelizable memory recurrent units Efficiently Modeling Long Sequences with Structured State Spaces

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.060419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 889a0ce8-2886-4f1e-bbaf-b17d554198f1 · outbound

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

Parallelizable memory recurrent units Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.018889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 1f4428a1-b417-42dc-be11-7e1b266a6412 · outbound

This paper cites Fading memory and the problem of approximating nonlinear operators with Volterra series.

Parallelizable memory recurrent units Fading memory and the problem of approximating nonlinear operators with Volterra series

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.032248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 9f8791f4-2180-47cc-acf5-0844e2c9b034 · outbound

This paper cites The illusion of state in state-space models.

Parallelizable memory recurrent units The illusion of state in state-space models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.035415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 08387196-bf18-4a67-87ed-9bf638f3cc4a · outbound

This paper cites A bio-inspired bistable recurrent cell allows for long-lasting memory.

Parallelizable memory recurrent units A bio-inspired bistable recurrent cell allows for long-lasting memory

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.041287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 3c10904c-6915-4559-ba24-eb576d067cb8 · outbound

This paper cites Warming up recurrent neural networks to maximise reachable multistability greatly improves learning.

Parallelizable memory recurrent units Warming up recurrent neural networks to maximise reachable multistability greatly improves learning

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.046670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 6ee9307c-e63a-4dc2-b8ed-7eeb9ecb01f2 · outbound

This paper cites Simplified State Space Layers for Sequence Model- ing.

Parallelizable memory recurrent units Simplified State Space Layers for Sequence Model- ing

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.063656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation dc170f4d-5966-4d6b-810f-a6f9eb5fb274 · outbound

This paper cites Parallelizing Linear Recurrent Neural Nets Over Sequence Length.

Parallelizable memory recurrent units Parallelizing Linear Recurrent Neural Nets Over Sequence Length

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.049513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 9eb254f5-83cc-4592-a774-54753510b0f7 · outbound

This paper cites Were RNNs All We Needed?.

Parallelizable memory recurrent units Were RNNs All We Needed?

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.056952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 319483f5-099b-483d-a4c5-cd6752a83f45 · outbound

This paper cites Hierarchically Gated Recurrent Neural Network for Sequence Modeling.

Parallelizable memory recurrent units Hierarchically Gated Recurrent Neural Network for Sequence Modeling

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.038581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 68958ce8-25df-44ce-bd48-d5a42a975d5e · outbound

This paper cites Parallelizing non-linear sequential models over the sequence length.

Parallelizable memory recurrent units Parallelizing non-linear sequential models over the sequence length

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.120587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 65fd6516-af6b-40f3-b253-139983650a06 · outbound

This paper cites Towards Scalable and Stable Paral- lelization of Nonlinear RNNs.

Parallelizable memory recurrent units Towards Scalable and Stable Paral- lelization of Nonlinear RNNs

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.113421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 6569090d-6ba5-4833-bc8c-c6fa306dbb68 · outbound

This paper cites ParaRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models.

Parallelizable memory recurrent units ParaRNN: Unlocking Parallel Training of Nonlinear RNNs for Large Language Models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.086813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation b1120779-4d39-4ae8-97a5-227552556421 · outbound

This paper cites Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-Based Optimization to Spiking Neural Networks.

Parallelizable memory recurrent units Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-Based Optimization to Spiking Neural Networks

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.071495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 238c5e74-d9f8-443e-8263-6b92d67a4709 · outbound

This paper cites Training Spiking Neural Networks Using Lessons From Deep Learning.

Parallelizable memory recurrent units Training Spiking Neural Networks Using Lessons From Deep Learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.093293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation bbe42074-302c-48f4-9cd0-cc610fe3372d · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Parallelizable memory recurrent units Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.079778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation a6c68e41-3a9f-442c-8d7b-76893da54fe2 · outbound

This paper cites Resurrecting Recurrent Neural Networks for Long Sequences.

Parallelizable memory recurrent units Resurrecting Recurrent Neural Networks for Long Sequences

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.123140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 7db51ac6-965c-441f-b2e2-94731e6ada0b · outbound

This paper cites Gradient-based learning applied to document recog- nition.

Parallelizable memory recurrent units Gradient-based learning applied to document recog- nition

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.107894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation b32b4fd2-daa0-4236-905c-a3db5a563a29 · outbound

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

Parallelizable memory recurrent units A Simple Way to Initialize Recurrent Networks of Rectified Linear Units

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.077237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 7d2015ec-0f36-4183-8fc4-a780f011e823 · outbound

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

Parallelizable memory recurrent units Long Range Arena: A Benchmark for Efficient Transformers

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.095551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation e256dd4a-0369-4b8d-a9c3-76cdb2389302 · outbound

This paper cites Multistability in Recurrent Neural Networks.

Parallelizable memory recurrent units Multistability in Recurrent Neural Networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.110625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 3cc4b098-39bb-4e3f-9097-d6a60ba8426f · outbound

This paper cites Theory of Gating in Recurrent Neural Networks.

Parallelizable memory recurrent units Theory of Gating in Recurrent Neural Networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.115929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation b8f5b42f-1cb6-406e-b154-9798a7183f5c · outbound

This paper cites Analysis of continuous-time switching networks.

Parallelizable memory recurrent units Analysis of continuous-time switching networks

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.101504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation cb1da6fd-8b4e-4e3d-b763-f83f0f25b5a8 · outbound

This paper cites A Step Towards Uncovering The Structure of Multistable Neural Networks.

Parallelizable memory recurrent units A Step Towards Uncovering The Structure of Multistable Neural Networks

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.118155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 848ad45c-cf79-4f85-8308-478e313ebcdf · outbound

This paper cites Combining Recurrent, Convo- lutional, and Continuous-time Models with Linear State-Space Layers.

Parallelizable memory recurrent units Combining Recurrent, Convo- lutional, and Continuous-time Models with Linear State-Space Layers

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.128608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 610b397c-e9ed-4d3e-88a5-98099c8a5656 · outbound

This paper cites xLSTM: Extended Long Short-Term Memory.

Parallelizable memory recurrent units xLSTM: Extended Long Short-Term Memory

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.105780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation e66aefad-9021-4ca7-9345-4e814253204e · outbound

This paper cites Recurrent neural network from adder’s perspective: Carry-lookahead RNN.

Parallelizable memory recurrent units Recurrent neural network from adder’s perspective: Carry-lookahead RNN

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.126082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 5fa1b9e7-136a-4033-baa8-97a598e129da · outbound

This paper cites An Optimized Parallel Implementation of Non-Iteratively Trained Recurrent Neural Networks.

Parallelizable memory recurrent units An Optimized Parallel Implementation of Non-Iteratively Trained Recurrent Neural Networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.073863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation c6078fcc-cedf-4baa-8bda-4ad51c7f9794 · outbound

This paper cites Training Deep Spiking Neural Networks Using Backpropaga- tion.

Parallelizable memory recurrent units Training Deep Spiking Neural Networks Using Backpropaga- tion

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.084500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation ff3c13b5-787d-405a-8c52-1b110d66d2ec · outbound

This paper cites Sparse Spiking Gradient Descent.

Parallelizable memory recurrent units Sparse Spiking Gradient Descent

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.088964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation a3aa0fbf-273b-4721-b513-cc9bf32cf1c2 · outbound

This paper cites Learning Finite State Machines With Self-Clustering Recurrent Networks.

Parallelizable memory recurrent units Learning Finite State Machines With Self-Clustering Recurrent Networks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.082019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 9047adaa-f745-4f71-9d20-b138c8824634 · outbound

This paper cites A learning algorithm for multi-layer perceptrons with hard-limiting threshold units.

Parallelizable memory recurrent units A learning algorithm for multi-layer perceptrons with hard-limiting threshold units

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.103622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation e028d1df-07ca-4cca-a5bc-9d70d0bb1657 · outbound

This paper cites Deep Equilibrium Models.

Parallelizable memory recurrent units Deep Equilibrium Models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.068778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 622ad845-6191-45ca-841d-473fdf145dd4 · outbound

This paper cites Prefix sums and their applications.

Parallelizable memory recurrent units Prefix sums and their applications

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-21T16:05:20.099055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation efbcdc5c-e31a-44e5-a1cb-4b38f2800458 · outbound

This paper cites an unresolved cited work.

Parallelizable memory recurrent units Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-05-21T16:05:20.066357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 8f9a13db-2dd0-4c72-912b-a1938a3abc05 · outbound

This paper cites cT ]creates the array[s 0.

Parallelizable memory recurrent units cT ]creates the array[s 0

Reference 39

Resolution: malformed identifier; raw_fallback, observed 2026-05-21T16:05:20.091098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Pith citing papers

Observation e56e8401-8437-46a5-a78e-acc1aa789516 · inbound

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology cites this paper.

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology Parallelizable memory recurrent units

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:05:40.495941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 2e3ca40f-dc47-45bd-913b-cc6c8febb5de · inbound

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology cites this paper.

A Fully Tunable Ultra-Low Power Current-Mode Memory Cell in Standard CMOS Technology Parallelizable memory recurrent units

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-20T22:49:10.397824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 00ab07a7-e090-42ff-bf20-bf31f29873bf · inbound

On the Importance of Multistability for Horizon Generalization in Reinforcement Learning cites this paper.

On the Importance of Multistability for Horizon Generalization in Reinforcement Learning Parallelizable memory recurrent units

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-20T00:05:40.495941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation ada12761-8698-4f6f-b2aa-708f9ee46d8d · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Parallelizable memory recurrent units

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-05-20T22:09:07.218953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.

Observation 0d0d1611-62ba-43c3-949d-8587a8a1ebac · inbound

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations cites this paper.

Hardware-Software Co-Design of Scalable, Energy-Efficient Analog Recurrent Computations Parallelizable memory recurrent units

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:05:46.358272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-30T06:33:22.917629+00:00.