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Paper Citation Record · LEDGER

Multi-modal transformer for signal classification in nanopore blockade experiments

As of 22 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.20323.

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

pith.paper-citation-record.v1
2607.20323 v1

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measured 38 of 38 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-01T10:13:24.758801Z

measured 38 of 38 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

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38 of 38 outbound references displayed

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Outbound references

Observation 38833894-f5f0-4e67-b9fe-2a14031ec51c · outbound

This paper cites Quantifying Attention Flow in Transformers.

Multi-modal transformer for signal classification in nanopore blockade experiments Quantifying Attention Flow in Transformers

Reference 1

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Observation 980f0d59-4999-401d-816a-a6e82b180983 · outbound

This paper cites Howard, Xander F.

Multi-modal transformer for signal classification in nanopore blockade experiments Howard, Xander F

Reference 2

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Observation 5fa9f6e7-0dbc-41e4-b72e-7c6fe17b3983 · outbound

This paper cites Kasianowicz, Manuela Pastoriza-Gallego, J´ erˆ ome Math´ e, R´ egis Daniel, Fabien Piguet, and Abdelghani Oukhaled.

Multi-modal transformer for signal classification in nanopore blockade experiments Kasianowicz, Manuela Pastoriza-Gallego, J´ erˆ ome Math´ e, R´ egis Daniel, Fabien Piguet, and Abdelghani Oukhaled

Reference 3

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Observation c7b158c9-46be-4e2e-9280-cbd4aa186371 · outbound

This paper cites Behrends and Tobias Ensslen.

Multi-modal transformer for signal classification in nanopore blockade experiments Behrends and Tobias Ensslen

Reference 4

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Observation 19a66064-9001-4782-b718-8d60baf7af95 · outbound

This paper cites PhD thesis, ´Ecole doctorale Sciences et ing´ enierie (Cergy-Pontoise, Val d’Oise), 2018.

Multi-modal transformer for signal classification in nanopore blockade experiments PhD thesis, ´Ecole doctorale Sciences et ing´ enierie (Cergy-Pontoise, Val d’Oise), 2018

Reference 5

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Observation c33357b1-9f93-47f3-9420-f8509dea4baa · outbound

This paper cites CrossViT: Cross-attention multi-scale vision transformer for image classification.

Multi-modal transformer for signal classification in nanopore blockade experiments CrossViT: Cross-attention multi-scale vision transformer for image classification

Reference 6

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Observation f008bb4e-6bdd-4338-9f15-b8ba7e2beb04 · outbound

This paper cites Vision Transformers Need Registers.

Multi-modal transformer for signal classification in nanopore blockade experiments Vision Transformers Need Registers

Reference 7

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Observation b9aa51f3-a603-45d5-bc31-478ff4d8d7b4 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Multi-modal transformer for signal classification in nanopore blockade experiments BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 8

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Observation 90b5fb2c-f846-40c0-9059-746bc58bb398 · outbound

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

Multi-modal transformer for signal classification in nanopore blockade experiments An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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Observation d7d9388c-78ee-4410-b868-8e0a63935b03 · outbound

This paper cites PhD thesis, Albert-Ludwigs-Universit¨ at Freiburg, Freiburg, 2024.

Multi-modal transformer for signal classification in nanopore blockade experiments PhD thesis, Albert-Ludwigs-Universit¨ at Freiburg, Freiburg, 2024

Reference 10

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This paper cites Behrends.

Multi-modal transformer for signal classification in nanopore blockade experiments Behrends

Reference 11

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Observation 18eeba03-0e2b-4b03-8f79-a50f61a0eca0 · outbound

This paper cites Behrends.

Multi-modal transformer for signal classification in nanopore blockade experiments Behrends

Reference 12

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Multi-modal transformer for signal classification in nanopore blockade experiments Unresolved cited work

Reference 13

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Observation b9ba3119-6b14-47b7-af9d-49f991c69ba3 · outbound

This paper cites Fried, Yanfang Wu, Richard D.

Multi-modal transformer for signal classification in nanopore blockade experiments Fried, Yanfang Wu, Richard D

Reference 14

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Observation f5de7798-7453-43b1-a453-adf6530cdca8 · outbound

This paper cites Burman, Javier E.

Multi-modal transformer for signal classification in nanopore blockade experiments Burman, Javier E

Reference 15

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Observation 8d4ba96c-0197-464b-8d78-e58e64f333b0 · outbound

This paper cites Masked Autoencoders Are Scalable Vision Learners.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 15979–15988, June 2022.

Multi-modal transformer for signal classification in nanopore blockade experiments Masked Autoencoders Are Scalable Vision Learners.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 15979–15988, June 2022

Reference 16

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Observation 9316375a-00c3-4dd7-a906-aa701b64bc51 · outbound

This paper cites Behrends, and Christian Holm.

Multi-modal transformer for signal classification in nanopore blockade experiments Behrends, and Christian Holm

Reference 17

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Observation 0fbafe90-bc77-4065-b553-4f7f1e09122f · outbound

This paper cites Finishing the euchromatic se- quence of the human genome.Nature, 431(7011):931–945, October 2004.

Multi-modal transformer for signal classification in nanopore blockade experiments Finishing the euchromatic se- quence of the human genome.Nature, 431(7011):931–945, October 2004

Reference 18

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Observation 6e9d044c-b124-4d24-b741-6996f5bdb55c · outbound

This paper cites SGDR: Stochastic Gradient Descent with Warm Restarts.

Multi-modal transformer for signal classification in nanopore blockade experiments SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 19

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This paper cites catch22: CAnonical Time-series CHaracteristics.

Multi-modal transformer for signal classification in nanopore blockade experiments catch22: CAnonical Time-series CHaracteristics

Reference 20

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Observation e6766774-a4c7-4cb4-be4d-511129c33726 · outbound

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Multi-modal transformer for signal classification in nanopore blockade experiments Unresolved cited work

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This paper cites Fox, Yishu Fang, Melissa Queen, Mattias Tolhurst, Nicolas Cardozo, Miten Jain, and Jeff Nivala.

Multi-modal transformer for signal classification in nanopore blockade experiments Fox, Yishu Fang, Melissa Queen, Mattias Tolhurst, Nicolas Cardozo, Miten Jain, and Jeff Nivala

Reference 22

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This paper cites Ssqueezepy.GitHub.

Multi-modal transformer for signal classification in nanopore blockade experiments Ssqueezepy.GitHub

Reference 23

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This paper cites Behrends, Aleksei Aksimentiev, and Abdelghani Oukhaled.

Multi-modal transformer for signal classification in nanopore blockade experiments Behrends, Aleksei Aksimentiev, and Abdelghani Oukhaled

Reference 24

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Observation 8c1840bd-aaf3-427f-832b-09c51e9518a4 · outbound

This paper cites Nanopore sensing of protein and peptide conformation for point-of-care applications.

Multi-modal transformer for signal classification in nanopore blockade experiments Nanopore sensing of protein and peptide conformation for point-of-care applications

Reference 25

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Observation f4cf6f55-5018-4092-939f-cce44cf96201 · outbound

This paper cites Single-Molecule Fingerprinting of Unlabeled Full-Length Proteins Using an Aerolysin Nanopore.Journal of the American Chemical Society, June 2026.

Multi-modal transformer for signal classification in nanopore blockade experiments Single-Molecule Fingerprinting of Unlabeled Full-Length Proteins Using an Aerolysin Nanopore.Journal of the American Chemical Society, June 2026

Reference 26

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Observation 6120746c-bf1d-4047-891f-b1977d4f634b · outbound

This paper cites Knappe, Mark Bathe, George Barbastathis, and Patrick S.

Multi-modal transformer for signal classification in nanopore blockade experiments Knappe, Mark Bathe, George Barbastathis, and Patrick S

Reference 27

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Observation 1d1d478f-9fbb-4959-9daf-c836a7ac54de · outbound

This paper cites Jayne Wallace, Marjetka Podobnik, and Gregor Anderluh.

Multi-modal transformer for signal classification in nanopore blockade experiments Jayne Wallace, Marjetka Podobnik, and Gregor Anderluh

Reference 28

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Observation 1a212af7-9bdf-4987-b28b-704535d92bb1 · outbound

This paper cites Pre-training of Lightweight Vision Transformers on Small Datasets with Minimally Scaled Images.

Multi-modal transformer for signal classification in nanopore blockade experiments Pre-training of Lightweight Vision Transformers on Small Datasets with Minimally Scaled Images

Reference 29

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Observation 373e1837-9bbc-4b82-9e04-c288aa3475c4 · outbound

This paper cites Behrends, and Christian Holm.

Multi-modal transformer for signal classification in nanopore blockade experiments Behrends, and Christian Holm

Reference 30

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Observation d7b79c60-07bc-491f-9e81-10dc2e9a6b00 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Multi-modal transformer for signal classification in nanopore blockade experiments Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 31

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Observation fe1ba295-6439-4825-a3b1-0c55218880c8 · outbound

This paper cites Dynamic Features Driven by Stochastic Collisions in a Nanopore for Precise Single-Molecule Identification.Journal of the American Chemical Society, 147(2):1781–1791, January 2025.

Multi-modal transformer for signal classification in nanopore blockade experiments Dynamic Features Driven by Stochastic Collisions in a Nanopore for Precise Single-Molecule Identification.Journal of the American Chemical Society, 147(2):1781–1791, January 2025

Reference 32

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This paper cites Reiner, Celeste Kennard, Mark J.

Multi-modal transformer for signal classification in nanopore blockade experiments Reiner, Celeste Kennard, Mark J

Reference 33

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Observation 19c00240-3d39-4374-a95b-661d95baebd1 · outbound

This paper cites LIMU-BERT: Unleashing the Potential of Unlabeled Data for IMU Sensing Applications.

Multi-modal transformer for signal classification in nanopore blockade experiments LIMU-BERT: Unleashing the Potential of Unlabeled Data for IMU Sensing Applications

Reference 34

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Observation ae03bbe3-f11d-4b5e-9ccc-471232d7c774 · outbound

This paper cites Single-Molecule Ionic and Optical Sensing with Nanoapertures.

Multi-modal transformer for signal classification in nanopore blockade experiments Single-Molecule Ionic and Optical Sensing with Nanoapertures

Reference 35

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This paper cites Foster, Aleksei Aksimentiev, Min Chen, and Meni Wanunu.

Multi-modal transformer for signal classification in nanopore blockade experiments Foster, Aleksei Aksimentiev, Min Chen, and Meni Wanunu

Reference 36

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Observation 8c10ad7c-a405-469e-a775-4cb655d9bba0 · outbound

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Multi-modal transformer for signal classification in nanopore blockade experiments Unresolved cited work

Reference 37

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Observation 27b7f99f-479d-4e87-adec-cc38c8ae99d7 · outbound

This paper cites Peptide sequencing based on host–guest interaction-assisted nanopore sensing.Nature Methods, 21(1):102– 109, January 2024.

Multi-modal transformer for signal classification in nanopore blockade experiments Peptide sequencing based on host–guest interaction-assisted nanopore sensing.Nature Methods, 21(1):102– 109, January 2024

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source=pdf_text observed=2026-08-01T10:13:24.758801Z digest=sha256:5d446bc69fa851c04f9c53234ab3eb4e870d9d781d19eab2c1430cd93bd8f0c6

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