Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain | Paper Citation Record

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Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Unresolved cited work

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This paper cites Convolutional neural net- works on graphs with fast localized spectral filtering.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Convolutional neural net- works on graphs with fast localized spectral filtering

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

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Mamba: Linear-Time Sequence Modeling with Selective State Spaces

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

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Efficiently Modeling Long Sequences with Structured State Spaces

Reference 13

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This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 14

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This paper cites Polynomial-based self-attention for table representation learning.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Polynomial-based self-attention for table representation learning

Reference 15

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This paper cites Kipf and Max Welling.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Kipf and Max Welling

Reference 16

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This paper cites Learning multiple layers of features from tiny im- ages.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Learning multiple layers of features from tiny im- ages

Reference 18

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This paper cites En- hancing the locality and breaking the memory bottleneck of transformer on time series forecasting.NeurIPS,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain En- hancing the locality and breaking the memory bottleneck of transformer on time series forecasting.NeurIPS,

Reference 19

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This paper cites Learn- ing long-range spatial dependencies with horizontal gated recurrent units.NeurIPS, 31,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Learn- ing long-range spatial dependencies with horizontal gated recurrent units.NeurIPS, 31,

Reference 20

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This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Swin transformer: Hierarchical vision transformer using shifted windows

Reference 21

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This paper cites Soft: Softmax-free transformer with linear complexity.NeurIPS, 34,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Soft: Softmax-free transformer with linear complexity.NeurIPS, 34,

Reference 22

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This paper cites Learning word vectors for sentiment analysis.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Learning word vectors for sentiment analysis

Reference 23

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This paper cites A fractional graph laplacian approach to oversmoothing.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain A fractional graph laplacian approach to oversmoothing

Reference 25

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This paper cites Generalized legendre polynomials.Journal of mathematical analysis and applications, 177(2),.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Generalized legendre polynomials.Journal of mathematical analysis and applications, 177(2),

Reference 26

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This paper cites Graph neural networks exponentially lose expressive power for node classification.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Graph neural networks exponentially lose expressive power for node classification

Reference 28

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This paper cites Graph signal processing: Overview, challenges, and ap- plications.IEEE, 106(5),.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Graph signal processing: Overview, challenges, and ap- plications.IEEE, 106(5),

Reference 29

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This paper cites SpectFormer: Frequency and Attention is what you need in a Vision Transformer.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain SpectFormer: Frequency and Attention is what you need in a Vision Transformer

Reference 30

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This paper cites cosFormer: Rethinking Softmax in Attention.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain cosFormer: Rethinking Softmax in Attention

Reference 31

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This paper cites Etc: Encoding long and structured inputs in transformers.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Etc: Encoding long and structured inputs in transformers

Reference 34

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This paper cites A Survey on Oversmoothing in Graph Neural Networks.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain A Survey on Oversmoothing in Graph Neural Networks

Reference 35

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This paper cites Imagenet large scale visual recognition challenge.IJCV, 115,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Imagenet large scale visual recognition challenge.IJCV, 115,

Reference 36

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This paper cites Revisiting over-smoothing in bert from the perspective of graph.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Revisiting over-smoothing in bert from the perspective of graph

Reference 38

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

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Long Range Arena: A Benchmark for Efficient Transformers

Reference 39

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This paper cites Attention is all you need.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Attention is all you need

Reference 40

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Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Graph Attention Networks

Reference 41

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This paper cites A tutorial on spectral clustering.Statistics and computing, 17,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain A tutorial on spectral clustering.Statistics and computing, 17,

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This paper cites Anti-oversmoothing in deep vision transformers via the fourier domain analysis: From theory to practice.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Anti-oversmoothing in deep vision transformers via the fourier domain analysis: From theory to practice

Reference 44

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Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Autoformer: Decomposition transform- ers with auto-correlation for long-term series forecasting

Reference 45

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Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Flowformer: Linearizing Transformers with Conservation Flows

Reference 46

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Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Singularformer: Learning to decompose self- attention to linearize the complexity of transformer

Reference 47

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This paper cites Nystr ¨omformer: A nystr ¨om-based algorithm for approximating self-attention.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Nystr ¨omformer: A nystr ¨om-based algorithm for approximating self-attention

Reference 48

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This paper cites Learning flexible body collision dynamics with hierarchical contact mesh transformer.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Learning flexible body collision dynamics with hierarchical contact mesh transformer

Reference 49

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This paper cites Big bird: Transformers for longer se- quences.NeurIPS, 33:17283–17297,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Big bird: Transformers for longer se- quences.NeurIPS, 33:17283–17297,

Reference 50

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This paper cites You only sample (almost) once: Linear cost self-attention via bernoulli sampling.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain You only sample (almost) once: Linear cost self-attention via bernoulli sampling

Reference 51

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This paper cites A transformer-based framework for multivariate time series representation learning.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain A transformer-based framework for multivariate time series representation learning

Reference 52

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Observation 08af783d-08fd-4b9b-8303-4f49c01aeed4 · outbound

This paper cites Informer: Beyond efficient transformer for long se- quence time-series forecasting.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Informer: Beyond efficient transformer for long se- quence time-series forecasting

Reference 53

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This paper cites Importantly, this is in- dependent of the specific configurations of the input matrices Z.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Importantly, this is in- dependent of the specific configurations of the input matrices Z

Reference 54

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Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Unresolved cited work

Reference 55

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This paper cites The UEA multivariate time series classification archive, 2018.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain The UEA multivariate time series classification archive, 2018

Reference 1985

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Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain ListOps: A Diagnostic Dataset for Latent Tree Learning

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This paper cites Linformer: Self-Attention with Linear Complexity.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Linformer: Self-Attention with Linear Complexity

Reference 2007

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This paper cites BERT: Pre-training of deep bidirectional transformers for language understand- ing.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain BERT: Pre-training of deep bidirectional transformers for language understand- ing

Reference 2009

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Observation 2e8e026f-9cfb-49c8-8b4d-6eed759606fa · outbound

This paper cites Signal processing on directed graphs: The role of edge directionality when processing and learning from network data.IEEE Signal Processing Magazine, 37(6),.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Signal processing on directed graphs: The role of edge directionality when processing and learning from network data.IEEE Signal Processing Magazine, 37(6),

Reference 2011

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This paper cites Language models are unsupervised multitask learners.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Language models are unsupervised multitask learners

Reference 2013

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This paper cites Efficient attention: Attention with linear complexities.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Efficient attention: Attention with linear complexities

Reference 2015

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Observation 5adb96c1-77e1-4afa-a945-c3da390543f9 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Imagenet: A large-scale hierarchical image database

Reference 2016

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Observation 4166ad2f-b72b-46a6-b00e-df4ccaa47f28 · outbound

This paper cites Reformer: The Efficient Transformer.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Reformer: The Efficient Transformer

Reference 2017

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This paper cites Longformer: The Long-Document Transformer.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Longformer: The Long-Document Transformer

Reference 2018

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This paper cites Graph convolutions enrich the self- attention in transformers!Advances in Neural Information Processing Systems, 37:52891–52936,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Graph convolutions enrich the self- attention in transformers!Advances in Neural Information Processing Systems, 37:52891–52936,

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:57:18.931728Z

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Observation 271432c3-c57f-4161-a567-3c2122f6c1fc · outbound

This paper cites Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation

Reference 2020

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Observation eafc4907-35d5-41e1-8f82-1504c0bc5829 · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Generating Long Sequences with Sparse Transformers

Reference 2021

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This paper cites The acl anthology network corpus.Language Resources and Eval- uation, 47,.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain The acl anthology network corpus.Language Resources and Eval- uation, 47,

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:57:18.595200Z

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Observation 4ab34d8d-5536-4c88-b730-b5ec93f9b37b · outbound

This paper cites Adaptive universal generalized PageR- ank graph neural network.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Adaptive universal generalized PageR- ank graph neural network

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:57:18.950086Z

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Observation 09c922d4-6f84-4a4e-aa82-9b85a91e96c4 · outbound

This paper cites Rethinking Attention with Performers.

Learning Advanced Self-Attention for Linear Transformers in the Singular Value Domain Rethinking Attention with Performers

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T21:57:17.553443Z

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