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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 21 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.

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measured 41 of 41 standing notices

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measured 0 of 0 inbound itemization

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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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Observation 8f2ff1d5-7ce8-41a4-a41b-4a35228564bc · outbound

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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Observation 2f6072eb-7c7c-4722-b442-ea50bdb155b4 · outbound

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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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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Observation fae42adb-6d05-49bf-bb1e-225176aa4b36 · outbound

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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Observation 71faedc9-5c27-40d0-bc26-a80bbb762735 · outbound

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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Observation 2d372edf-85c6-4967-9fa5-b7ce441a703a · outbound

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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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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This paper cites In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp.

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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This paper cites PloS one12(7), 0180944 (2017).

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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raw_fallback, observed 2026-08-05T16:04:59.010827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:57.944490Z digest=sha256:4ddf61380080ad8749d7dc2ae70770edbf6cb8b4b39e7bfa0727b2e6c39c8aa8

Observation 435bc381-d390-417c-8f93-6c9d34856e6c · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-05T16:04:57.953549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:04:57.953549Z digest=sha256:87b1f208ea4f8b87ed11148fdd0a3fcc946a323a470a46ef2f1ff685ccc23b8c

Observation 6c791a03-4c92-4a18-991a-2035acfa9bf1 · outbound

This paper cites Applied Stochastic Models in Business and Industry 33(1), 3–12 (2017).

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:04:58.973050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:57.963126Z digest=sha256:93b9eac3ba71b194643e8045a1a703b98b8ff9bb132ac8eaa493f0e0722bdeb0

Observation d8d34b13-590a-4cd6-bf72-095621715783 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:04:58.928640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:57.969649Z digest=sha256:3d52d54c87df048c3aa5e6d67e8ec943883fe96660cfca47f032da708c6c4dc0

Observation 15ebaf9d-89ed-456e-bc5d-221e3c46850f · outbound

This paper cites Neural computation 12(10), 2451–2471 (2000).

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:04:58.890958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:57.976341Z digest=sha256:35e601d9e554913d0636b19598deb7e4a91970d6fd6f033eb9b46d4d816fc9bd

Observation 9e15962f-0faa-429a-b048-83d55c729b5c · outbound

This paper cites In: International Conference on Machine Learning, pp.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:04:58.860539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:57.981754Z digest=sha256:02c17b837fb419c3b896b8836b3fd4c2769a24c1c98fcfd8d6dacab18ac2c9d7

Observation 60a48d93-0681-4998-be48-336379712194 · outbound

This paper cites In: International Conference on Frontiers of Intelligent Computing: Theory and Applications, pp.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:04:58.827270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:57.988541Z digest=sha256:36f4c6e3b6988073dfe5c898b51c902f9b0459af2dcff332ff3e0c59c2d78f3d

Observation a9aa1463-fe6e-4c13-aea3-f1940ebb416c · outbound

This paper cites International Scientific and Practical Conference in Control Engineering and Decision Making, pp.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T16:04:58.776539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:57.995066Z digest=sha256:7586f4ddd252f73102962a7f3ab533e3552d02e2427054464fcb7b30a4b358f9

Observation 0fc7d7b5-8ea1-4777-b4a1-592efc5f15bc · outbound

This paper cites an unresolved cited work.

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

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-05T16:04:58.739732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T16:04:58.001132Z digest=sha256:dee64f01cee4a6e66eaa24e61d7b0c394aeef186b446ff88e4ccbbe75dbab34e

Pith citing papers

No inbound Pith citation observations are available.