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Paper Citation Record · LEDGER

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity

As of 21 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.15541.

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

pith.paper-citation-record.v1
2506.15541 v1

Coverage vector

measured 39 of 39 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-15T19:38:27.932737Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation c62111ae-4144-4cd9-a0c0-2d6bd0a5669b · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 1

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Observation 0583c5a7-37d5-48bd-b11b-40744fc27297 · outbound

This paper cites Efficient transformers: A survey.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Efficient transformers: A survey

Reference 2

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Observation c4bbcec9-5552-466b-a90d-6440d5035817 · outbound

This paper cites Transformers in vision: A survey.ACM computing surveys (CSUR), 54(10s):1–41, 2022.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Transformers in vision: A survey.ACM computing surveys (CSUR), 54(10s):1–41, 2022

Reference 3

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Observation be6a3423-a360-4c7d-865f-10dfda52c99d · outbound

This paper cites A survey of transformers.AI open, 3:111–132, 2022.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity A survey of transformers.AI open, 3:111–132, 2022

Reference 4

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Observation a014ed9d-1849-4867-a106-b9ff5a13dec0 · outbound

This paper cites Natural language pro- cessing: an introduction.Journal of the American Medical Informatics Association, 18(5):544– 551, 2011.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Natural language pro- cessing: an introduction.Journal of the American Medical Informatics Association, 18(5):544– 551, 2011

Reference 5

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Observation e12fccc8-ac1d-4439-8ef5-e2cbce3841cc · outbound

This paper cites A survey on vision transformer.IEEE transactions on pattern analysis and machine intelligence, 45(1):87–110, 2022.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity A survey on vision transformer.IEEE transactions on pattern analysis and machine intelligence, 45(1):87–110, 2022

Reference 6

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Observation 7d107c9c-e5d6-4b06-b6d7-20ded5a96cef · outbound

This paper cites Transformer interpretability beyond attention visualization.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Transformer interpretability beyond attention visualization

Reference 7

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Observation 8080a56e-c8c8-41ab-8bc6-aa9cea3414ef · outbound

This paper cites Attention-based interpretability with concept transformers.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Attention-based interpretability with concept transformers

Reference 8

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Observation e0004033-1462-46ba-8e7d-674dce5c13f0 · outbound

This paper cites Interpretability-aware redundancy reduction for vision transformers.Advances in neural infor- mation processing systems, 34:24898–24911, 2021.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Interpretability-aware redundancy reduction for vision transformers.Advances in neural infor- mation processing systems, 34:24898–24911, 2021

Reference 9

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Observation defe9de6-530e-4ce4-ae4c-6a86dcb06e0b · outbound

This paper cites Are Transformers universal approximators of sequence-to-sequence functions?.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Are Transformers universal approximators of sequence-to-sequence functions?

Reference 10

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Observation c85ade4d-95ed-479c-9b59-ff9260dd16bd · outbound

This paper cites Attention is turing-complete.Journal of Machine Learning Research, 22(75):1–35, 2021.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Attention is turing-complete.Journal of Machine Learning Research, 22(75):1–35, 2021

Reference 11

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Observation 1429ca7f-cc2b-49d9-bceb-4e86aaafa483 · outbound

This paper cites Transformers learn to imple- ment preconditioned gradient descent for in-context learning.Advances in Neural Information Processing Systems, 36:45614–45650, 2023.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Transformers learn to imple- ment preconditioned gradient descent for in-context learning.Advances in Neural Information Processing Systems, 36:45614–45650, 2023

Reference 12

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Observation 80a6d2b0-0f4a-4d6e-b489-8efa7985ff1a · outbound

This paper cites Transformers Learn Shortcuts to Automata.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Transformers Learn Shortcuts to Automata

Reference 13

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Observation f6ecd523-cbe9-4345-8fa3-0884dff5b556 · outbound

This paper cites Explainability for large language models: A survey.ACM Transactions on Intelligent Systems and Technology, 15(2):1–38, 2024.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Explainability for large language models: A survey.ACM Transactions on Intelligent Systems and Technology, 15(2):1–38, 2024

Reference 14

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Observation 6846b5c7-26c6-42c7-8f2d-5437ffc19d16 · outbound

This paper cites Toward transparent ai: A survey on interpreting the inner structures of deep neural networks.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Toward transparent ai: A survey on interpreting the inner structures of deep neural networks

Reference 15

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Observation 475c7c42-a14b-4b44-b581-e8c8a1d00075 · outbound

This paper cites Quantifying Attention Flow in Transformers.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Quantifying Attention Flow in Transformers

Reference 16

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Observation 2addba71-954a-4648-b2c4-dd8ad497a541 · outbound

This paper cites Rethinking graph transformers with spectral attention.Advances in Neural Information Pro- cessing Systems, 34:21618–21629, 2021.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Rethinking graph transformers with spectral attention.Advances in Neural Information Pro- cessing Systems, 34:21618–21629, 2021

Reference 17

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Observation 07f7590a-0ac4-4043-88cc-832e7efef470 · outbound

This paper cites Calcul symbolique et propagation des singularités pour les équations aux dérivées partielles non linéaires.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Calcul symbolique et propagation des singularités pour les équations aux dérivées partielles non linéaires

Reference 18

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Observation 4d1acaa8-bb8c-4fdd-9fae-0543a14876e8 · outbound

This paper cites Springer, 2011.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Springer, 2011

Reference 19

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Observation f4fe8dfa-e36c-4eab-a301-5ca7d87225ae · outbound

This paper cites Fourier analysis methods for pdes.Lecture notes, 14(1):1–91, 2005.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Fourier analysis methods for pdes.Lecture notes, 14(1):1–91, 2005

Reference 20

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Observation a4977d9e-4376-4732-91eb-1ccce85dcec7 · outbound

This paper cites The nash-moser theorem and paradifferential operators.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity The nash-moser theorem and paradifferential operators

Reference 21

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Observation df170e44-8d80-4464-93f4-4758f8d46794 · outbound

This paper cites Quasilinearization with regularizing tensor paraproducts.arXiv preprint arXiv:2503.12629, 2025.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Quasilinearization with regularizing tensor paraproducts.arXiv preprint arXiv:2503.12629, 2025

Reference 22

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Observation 66fdc40f-c1d8-4ae2-9e82-380918258d92 · outbound

This paper cites Harmonic analysis of digital data bases.Wavelets and Multiscale Analysis: Theory and Applications, pages 161–197, 2011.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Harmonic analysis of digital data bases.Wavelets and Multiscale Analysis: Theory and Applications, pages 161–197, 2011

Reference 23

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Observation b182eb9b-99f9-413b-915d-70c62c4ddebe · outbound

This paper cites Sampling, denoising and compression of matrices by coherent matrix organization.Applied and Computational Harmonic Analysis, 33(3):354–369, 2012.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Sampling, denoising and compression of matrices by coherent matrix organization.Applied and Computational Harmonic Analysis, 33(3):354–369, 2012

Reference 24

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Observation faf9effb-9baf-4b2f-b991-9927dde215ce · outbound

This paper cites Yale University, 2014.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Yale University, 2014

Reference 25

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Source-reported events for the cited work

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Observation 6a8bc919-7057-478f-b750-75f2fb33b7be · outbound

This paper cites Hierarchical coupled-geometry analysis for neuronal structure and activity pattern discovery.IEEE Journal of Selected Topics in Signal Processing, 10(7):1238–1253, 2016.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Hierarchical coupled-geometry analysis for neuronal structure and activity pattern discovery.IEEE Journal of Selected Topics in Signal Processing, 10(7):1238–1253, 2016

Reference 26

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Observation 260cf288-8df2-4b6e-bb4c-6d0e33d4fabf · outbound

This paper cites From clutter to clarity: Emergent neural operators via questionnaire metrics.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity From clutter to clarity: Emergent neural operators via questionnaire metrics

Reference 27

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verified fuzzy
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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.

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Observation 95f7b260-2f6b-4330-9cc7-7303225fdbb0 · outbound

This paper cites From disorganized data to emergent dynamic models: Questionnaires to partial differential equations.PNAS nexus, page pgaf018, 2025.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity From disorganized data to emergent dynamic models: Questionnaires to partial differential equations.PNAS nexus, page pgaf018, 2025

Reference 28

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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.

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Observation 349b8e58-8405-4f7b-80ad-ed91a63cb804 · outbound

This paper cites Multiscale wavelets on trees, graphs and high dimensional data: theory and applications to semi supervised learning.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Multiscale wavelets on trees, graphs and high dimensional data: theory and applications to semi supervised learning

Reference 29

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verified fuzzy
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Observation 5fea09ed-6d95-49d3-849f-6090f7b21d9c · outbound

This paper cites Ondelettes et opérateurs.I: Ondelettes, 1990.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Ondelettes et opérateurs.I: Ondelettes, 1990

Reference 30

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source=pdf_text observed=2026-08-15T19:38:27.840157Z digest=sha256:7f3b3487baee08c92b1556e4a994a486d0035ec5f208f6f4aa06350ba95fbdf7

Observation 4d161fb2-e6b0-4155-a2de-60cdd1946ab4 · outbound

This paper cites A theory for multiresolution signal decomposition: the wavelet repre- sentation.IEEE transactions on pattern analysis and machine intelligence, 11(7):674–693, 1989.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity A theory for multiresolution signal decomposition: the wavelet repre- sentation.IEEE transactions on pattern analysis and machine intelligence, 11(7):674–693, 1989

Reference 31

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Source-reported events for the cited work

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Observation e2208cae-2fb8-420d-bdf9-cd0636afef64 · outbound

This paper cites Wavelets and adapted waveform analysis.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Wavelets and adapted waveform analysis

Reference 32

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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.

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Observation 6f9b5910-9861-4019-9f50-85b40441aa71 · outbound

This paper cites Multiresolution homogenization schemes for differential equations and appli- cations.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Multiresolution homogenization schemes for differential equations and appli- cations

Reference 33

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verified fuzzy
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Source-reported events for the cited work

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Observation 11aa94cb-49c3-4378-b62b-9021f125f1b8 · outbound

This paper cites an unresolved cited work.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Unresolved cited work

Reference 34

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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.

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Observation 0d404f33-aa1e-434b-a136-38e6a7933cb0 · outbound

This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 35

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ad1b50c7-4916-406b-a2d6-536e08ca5adf · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 36

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e5e2d3c4-c2e1-4b9a-9773-9cab6165d004 · outbound

This paper cites Diffusion maps.Applied and computational harmonic analysis, 21(1):5–30, 2006.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Diffusion maps.Applied and computational harmonic analysis, 21(1):5–30, 2006

Reference 37

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8bf8e246-4363-4f95-af0a-3a1e40bc209e · outbound

This paper cites Pointer Sentinel Mixture Models.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Pointer Sentinel Mixture Models

Reference 38

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 02dd11b1-637a-475d-a9ef-b341fc750831 · outbound

This paper cites Learning multiple layers of features from tiny images.

Intrinsic and Extrinsic Organized Attention: Softmax Invariance and Network Sparsity Learning multiple layers of features from tiny images

Reference 39

Resolution
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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.

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Pith citing papers

No inbound Pith citation observations are available.