Paper Citation Record · LEDGER

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models

As of 20 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2508.19006.

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

pith.paper-citation-record.v1
2508.19006 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:04:58.001132Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation 36ae2295-ff40-4bff-8b12-920311161635 · outbound

This paper cites Multilayer Perceptron Neural Network Models in Asset Pricing: An Empirical Study on Large-Cap US Stocks.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Multilayer Perceptron Neural Network Models in Asset Pricing: An Empirical Study on Large-Cap US Stocks

Reference 1

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This paper cites Review of Financial Studies 33(5), 2223–2273 (2020) https://doi.org/10.1093/ rfs/hhaa009.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Review of Financial Studies 33(5), 2223–2273 (2020) https://doi.org/10.1093/ rfs/hhaa009

Reference 3

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This paper cites CRC Press, Boca Raton, FL (2020).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models CRC Press, Boca Raton, FL (2020)

Reference 4

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This paper cites Centre for Financial Research (CFR), working paper (2020).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Centre for Financial Research (CFR), working paper (2020)

Reference 5

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This paper cites Available at SSRN 4999011 (2024).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Available at SSRN 4999011 (2024)

Reference 6

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Observation b2d63252-7856-4102-994e-2573dcb195ee · outbound

This paper cites Cognitive science 14(2), 179–211 (1990).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Cognitive science 14(2), 179–211 (1990)

Reference 7

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Observation 54e38f62-c5c5-4422-9191-ff5c499dc73d · outbound

This paper cites nature 323(6088), 533–536 (1986).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models nature 323(6088), 533–536 (1986)

Reference 8

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This paper cites Neural computation 9(8), 1735–1780 (1997).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Neural computation 9(8), 1735–1780 (1997)

Reference 9

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This paper cites In: EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, pp.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models In: EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, pp

Reference 10

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This paper cites Advances in neural information processing systems 30 (2017).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Advances in neural information processing systems 30 (2017)

Reference 11

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This paper cites Longformer: The Long-Document Transformer.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Longformer: The Long-Document Transformer

Reference 12

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This paper cites Technical report, National Bureau of Economic Research (2025).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Technical report, National Bureau of Economic Research (2025)

Reference 13

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This paper cites Journal of Financial Economics 33(1), 3–56 (1993) https://doi.org/10.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Journal of Financial Economics 33(1), 3–56 (1993) https://doi.org/10

Reference 14

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This paper cites Journal of Finance 52(1), 57–82 (1997) https://doi.org/10.1111/j.1540-6261.1997.tb03808.x.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Journal of Finance 52(1), 57–82 (1997) https://doi.org/10.1111/j.1540-6261.1997.tb03808.x

Reference 15

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This paper cites Journal of Financial Economics 116(1), 1–22 (2015) https://doi.org/10.1016/j.jfineco.2014.10.010.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Journal of Financial Economics 116(1), 1–22 (2015) https://doi.org/10.1016/j.jfineco.2014.10.010

Reference 16

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This paper cites Review of Financial Studies 28(3), 650–705 (2015) https://doi.org/10.1093/rfs/ hhu068.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Review of Financial Studies 28(3), 650–705 (2015) https://doi.org/10.1093/rfs/ hhu068

Reference 17

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This paper cites Available at SSRN 3341728 (2019).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Available at SSRN 3341728 (2019)

Reference 18

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This paper cites International Journal of Data Science and Analytics 12(2), 175–183 (2021) https://doi.org/10.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models International Journal of Data Science and Analytics 12(2), 175–183 (2021) https://doi.org/10

Reference 19

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This paper cites Journal of Econometrics 222(1), 429–450 (2021).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Journal of Econometrics 222(1), 429–450 (2021)

Reference 20

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This paper cites Available at SSRN 3450322 (2021).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Available at SSRN 3450322 (2021)

Reference 21

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This paper cites Management Science 70(2), 714–750 (2024) https://doi.org/10.1287/mnsc.2023.4695.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Management Science 70(2), 714–750 (2024) https://doi.org/10.1287/mnsc.2023.4695

Reference 22

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This paper cites Journal of Financial Economics 134(3), 501–524 (2019) https: //doi.org/10.1016/j.jfineco.2019.05.001.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Journal of Financial Economics 134(3), 501–524 (2019) https: //doi.org/10.1016/j.jfineco.2019.05.001

Reference 23

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This paper cites Journal of Economic Surveys (2022) https://doi.org/10.1111/joes.12532.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Journal of Economic Surveys (2022) https://doi.org/10.1111/joes.12532

Reference 24

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This paper cites Advances in neural information processing systems 27 (2014).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Advances in neural information processing systems 27 (2014)

Reference 25

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This paper cites International Review of Financial Analysis 90 (2023) https://doi.org/10.1016/j.irfa.2023.102876.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models International Review of Financial Analysis 90 (2023) https://doi.org/10.1016/j.irfa.2023.102876

Reference 26

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This paper cites Asset Pricing and Deep Learning.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Asset Pricing and Deep Learning

Reference 27

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This paper cites Deep Sequence Modeling: Development and Applications in Asset Pricing.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Deep Sequence Modeling: Development and Applications in Asset Pricing

Reference 28

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This paper cites Available at SSRN 3971876 (2021).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Available at SSRN 3971876 (2021)

Reference 29

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models In: 3rd International Conference on Learning Representations, ICLR 2015 - Conference Track Proceedings, pp

Reference 30

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Effective Approaches to Attention-based Neural Machine Translation

Reference 31

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp

Reference 32

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This paper cites Indonesian Journal of Electrical Engineering and Computer Science 24(3), 1759–1771 (2021).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Indonesian Journal of Electrical Engineering and Computer Science 24(3), 1759–1771 (2021)

Reference 33

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models PloS one12(7), 0180944 (2017)

Reference 34

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This paper cites Supervised Autoencoder MLP for Financial Time Series Forecasting.

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Supervised Autoencoder MLP for Financial Time Series Forecasting

Reference 35

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Applied Stochastic Models in Business and Industry 33(1), 3–12 (2017)

Reference 36

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This paper cites IEEE transactions on neural networks 5(2), 157–166 (1994).

Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models IEEE transactions on neural networks 5(2), 157–166 (1994)

Reference 37

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Neural computation 12(10), 2451–2471 (2000)

Reference 38

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models In: International Conference on Machine Learning, pp

Reference 39

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models In: International Conference on Frontiers of Intelligent Computing: Theory and Applications, pp

Reference 40

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models International Scientific and Practical Conference in Control Engineering and Decision Making, pp

Reference 41

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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models Unresolved cited work

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Pith citing papers

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