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Paper Citation Record · LEDGER

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models

As of 10 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2607.03925.

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

pith.paper-citation-record.v1
2607.03925 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T22:59:23.504518Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

42 of 42 outbound references displayed

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  • verified fuzzy0
  • unresolved32
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

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Outbound references

Observation 86b061e6-6d54-4f49-82fa-0e6005ba8474 · outbound

This paper cites A comprehensive review of eeg-based brain–computer interface paradigms.Journal of neural engineering, 16(1): 011001, 2019.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models A comprehensive review of eeg-based brain–computer interface paradigms.Journal of neural engineering, 16(1): 011001, 2019

Reference 1

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Observation 46ca8f3c-76e5-4231-9c2b-e0ba3402b2c9 · outbound

This paper cites Review of machine learning techniques for eeg based brain computer interface.Archives of Computational Methods in Engineering, 29(5):3001–3020, 2022.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Review of machine learning techniques for eeg based brain computer interface.Archives of Computational Methods in Engineering, 29(5):3001–3020, 2022

Reference 2

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:1775bf05e06baad55a570c383da779c082c1d13e8834a3586edf27bb218915ac

Observation 4bfe6676-e089-4b1a-bb3a-d1784b951064 · outbound

This paper cites A review of classification algorithms for eeg-based brain– computer interfaces: a 10 year update.Journal of neural engineering, 15(3):031005, 2018.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models A review of classification algorithms for eeg-based brain– computer interfaces: a 10 year update.Journal of neural engineering, 15(3):031005, 2018

Reference 3

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Observation 36474223-5a62-4fd9-ac54-339cd10dd002 · outbound

This paper cites Past, present, and future of eeg-based bci applications.Sensors, 22(9):3331, 2022.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Past, present, and future of eeg-based bci applications.Sensors, 22(9):3331, 2022

Reference 4

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:82f15042f156849a15432988e48fbcbb30b4ae5968b691be6b374d3d7cc1c60b

Observation 820cf523-c073-435c-8b98-a8f5308143ed · outbound

This paper cites Recent advances in natural language processing via large pre-trained language models: A survey.ACM Comput.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Recent advances in natural language processing via large pre-trained language models: A survey.ACM Comput

Reference 5

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:c900f71ecbb983b4cd2d9c26a82ca63f7ba1fadc9b285c4d7899871baddcd837

Observation 47f277c0-0c94-45b1-950a-f92f34c12bf2 · outbound

This paper cites Masked autoencoders are scalable vision learners.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Masked autoencoders are scalable vision learners

Reference 6

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:a18a5e86ccf526f84c3e7a2b8002575a94dd53139d3b162048f7d8f7029656f9

Observation 132c7a05-c6fc-4e5f-801c-9e49ec45c903 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models A simple framework for contrastive learning of visual representations

Reference 7

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:19267facaed5a66da7f4a737181b1c3dae2deb986e54a54771dfea65220deb15

Observation e6c729c6-3081-4d39-afa7-79bcf3a86360 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 8

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:c9f07a3b5aee33a60535058bdf30fb9cb8b8d933cbcfbeddc5f4fe06c465d8e2

Observation 0ee74b34-40f0-41ec-9631-408fdfb8626a · outbound

This paper cites Eeg foundation models: a critical review of current progress and future directions.Journal of neural engineering, 23(2):021001, 2026.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Eeg foundation models: a critical review of current progress and future directions.Journal of neural engineering, 23(2):021001, 2026

Reference 9

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:51a01e9b17adfdbb5e2713e515d42517e8e7276305e1b3c10bf9c92428d5e683

Observation ffcb48cc-7bf9-40b7-98c3-6e95ab28ac72 · outbound

This paper cites A simple review of eeg foundation models: Datasets, advancements and future perspectives.arXiv preprint arXiv:2504.20069, 2025.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models A simple review of eeg foundation models: Datasets, advancements and future perspectives.arXiv preprint arXiv:2504.20069, 2025

Reference 10

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:03dfc04765f36c49f327488df1b30d7433a5da0b01159ced705d4d56bb3ff775

Observation f2761343-f185-4f61-9618-c1c9a3c4014f · outbound

This paper cites AdaBrain-Bench: Benchmarking Brain Foundation Models for Brain-Computer Interface Applications.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models AdaBrain-Bench: Benchmarking Brain Foundation Models for Brain-Computer Interface Applications

Reference 11

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:359439ccb0cdf1e1ee522d0c0f43a481818963adc33bf8253e833cb2194c6f9c

Observation 9a24a755-c546-4c35-ae9e-230acc9791ab · outbound

This paper cites Eeg-based emotion recognition: A state-of-the-art review of current trends and opportunities.Computational Intelligence and Neuroscience, 2020(1):8875426, 2020.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Eeg-based emotion recognition: A state-of-the-art review of current trends and opportunities.Computational Intelligence and Neuroscience, 2020(1):8875426, 2020

Reference 12

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:92368ab0491e29da5e1060d5be1410f94be8703b76e05a1d2b68a02d8a3252fd

Observation e4bb1a11-03b6-4fc7-ab3b-b5fdfb09ca13 · outbound

This paper cites A review of feature extraction and performance evaluation in epileptic seizure detection using eeg.Biomedical Signal Processing and Control, 57:101702, 2020.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models A review of feature extraction and performance evaluation in epileptic seizure detection using eeg.Biomedical Signal Processing and Control, 57:101702, 2020

Reference 13

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Observation e258fa76-0631-4f3b-9af0-5b4405fca5d0 · outbound

This paper cites Al-Zoubi, Hossam Faris, and Ibrahim Aljarah.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Al-Zoubi, Hossam Faris, and Ibrahim Aljarah

Reference 14

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:f41dccc62c7a9aaf9ae8d5a74264aa8b7006412138dbfe465a825f1b2ac03140

Observation dca3c274-f9c4-48b8-861a-4b35947a54c0 · outbound

This paper cites Shamim Hossain.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Shamim Hossain

Reference 15

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Observation 01fa85ec-1c54-4803-a390-1a7c5ad1b1b4 · outbound

This paper cites Chrononet: A deep recurrent neural net- work for abnormal eeg identification.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Chrononet: A deep recurrent neural net- work for abnormal eeg identification

Reference 16

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Observation ef6a58e6-1842-4da5-ac1c-60bdd31a0297 · outbound

This paper cites an unresolved cited work.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Unresolved cited work

Reference 17

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Observation bfef776d-6138-4b59-9980-59971ffd1214 · outbound

This paper cites Aboalayon, Miad Faezipour, Wafaa S.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Aboalayon, Miad Faezipour, Wafaa S

Reference 18

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Observation 63c2bca8-ed9c-4ee3-846a-f5647b359a8a · outbound

This paper cites Self-supervised learning: Generative or contrastive.IEEE Transactions on Knowledge and Data Engineering, 35(1):857–876, 2023.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Self-supervised learning: Generative or contrastive.IEEE Transactions on Knowledge and Data Engineering, 35(1):857–876, 2023

Reference 19

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:3857c40adaeeb07123f99f4023ad4bbd9ea606623bee7b0b274208abf4973afb

Observation 516afda5-8bac-421f-8d3e-81dbad99e00e · outbound

This paper cites Cbramod: A criss-cross brain foundation model for eeg decoding.arXiv preprint arXiv:2412.07236, 2024.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Cbramod: A criss-cross brain foundation model for eeg decoding.arXiv preprint arXiv:2412.07236, 2024

Reference 20

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:800671712623cda138d171b5322ef50c9815733ffe5f92f01defff686cb3c596

Observation e1eb3cc6-bc45-4c9a-8d50-26fcdc98fedf · outbound

This paper cites Large brain model for learning generic representations with tremendous eeg data in bci.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Large brain model for learning generic representations with tremendous eeg data in bci

Reference 21

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Observation 4cabc2b7-3fdb-4387-8eb7-d60c585b60e2 · outbound

This paper cites Non- stationarity in brain-computer interfaces: An analytical perspective.arXiv preprint arXiv:2512.15941, 2025.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Non- stationarity in brain-computer interfaces: An analytical perspective.arXiv preprint arXiv:2512.15941, 2025

Reference 22

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Observation 34b1ce31-9895-4743-a727-00aa40b81758 · outbound

This paper cites Challenge for affective brain-computer interfaces: non- stationary spatio-spectral eeg oscillations of emotional responses.Frontiers in human neuro- science, 13:366, 2019.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Challenge for affective brain-computer interfaces: non- stationary spatio-spectral eeg oscillations of emotional responses.Frontiers in human neuro- science, 13:366, 2019

Reference 23

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Observation 8190b25c-0285-47db-9f19-0d79099c9799 · outbound

This paper cites an unresolved cited work.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Unresolved cited work

Reference 24

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Observation 69593ff9-ac03-4cd8-935f-318ebeea0ff4 · outbound

This paper cites Eegpt: Pretrained transformer for universal and reliable representation of eeg signals.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Eegpt: Pretrained transformer for universal and reliable representation of eeg signals

Reference 25

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Observation 5ba48bfb-e4ee-45bc-be5d-86e44ed6e27b · outbound

This paper cites Biot: Biosignal transformer for cross-data learning in the wild.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Biot: Biosignal transformer for cross-data learning in the wild

Reference 26

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Observation 69778eb0-b064-4aac-b59b-8a478e4da4c3 · outbound

This paper cites Hoi, Doyen Sahoo, Jing Lu, and Peilin Zhao.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Hoi, Doyen Sahoo, Jing Lu, and Peilin Zhao

Reference 27

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Observation 4b72de28-261c-4125-95df-e0158f1d5096 · outbound

This paper cites Contrastive test-time adaptation.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Contrastive test-time adaptation

Reference 28

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Observation 102561db-9bd4-4345-9a87-c123ab390b16 · outbound

This paper cites Online video understanding: Ovbench and videochat- online.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Online video understanding: Ovbench and videochat- online

Reference 29

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:157e37ee29fccac8e240e4d721dc06e85bf7fbb2eb872d80855fa80d4f62dfdc

Observation 86ef5332-3ff4-4370-b06d-c7238fca27d2 · outbound

This paper cites Continual learning of large language models: A comprehensive survey.ACM Comput.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Continual learning of large language models: A comprehensive survey.ACM Comput

Reference 30

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Observation 7429204b-938d-4f7a-a0f1-a9f67b3e3d54 · outbound

This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Tent: Fully Test-time Adaptation by Entropy Minimization

Reference 31

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:0da5e0b50472a17184e49a7cefe8b9820298c18012d546495bd1f59794dbac59

Observation 866a4574-0674-4fc5-b6cc-2dd472dc6738 · outbound

This paper cites Mutual information-driven subject- invariant and class-relevant deep representation learning in bci.IEEE Transactions on Neural Networks and Learning Systems, 34(2):739–749, 2023.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Mutual information-driven subject- invariant and class-relevant deep representation learning in bci.IEEE Transactions on Neural Networks and Learning Systems, 34(2):739–749, 2023

Reference 32

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Observation fda89bb8-da8c-45cc-a1f7-c73c9916059c · outbound

This paper cites Eeg temporal–spatial transformer for person identification.Scientific Reports, 12(1):14378, 2022.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Eeg temporal–spatial transformer for person identification.Scientific Reports, 12(1):14378, 2022

Reference 33

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source=pdf_text observed=2026-07-11T22:59:23.504518Z digest=sha256:8a1832fa769d0d725aab3c96d9eca7a02d6a109431902cdbb5f578bbe154669e

Observation 6341a62b-16c4-4197-bc20-49472cf12c92 · outbound

This paper cites Bci competition 2008–graz data set a.Institute for knowledge discovery (laboratory of brain- computer interfaces), Graz University of Technology, 16(1-6):1, 2008.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Bci competition 2008–graz data set a.Institute for knowledge discovery (laboratory of brain- computer interfaces), Graz University of Technology, 16(1-6):1, 2008

Reference 34

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Observation ea07f07a-1583-4485-9f47-01bc11beafcd · outbound

This paper cites an unresolved cited work.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Unresolved cited work

Reference 35

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Observation 09df3e53-05a7-41d6-88ee-49cb2f3048e7 · outbound

This paper cites A large eeg dataset for studying cross-session variability in motor imagery brain-computer interface.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models A large eeg dataset for studying cross-session variability in motor imagery brain-computer interface

Reference 36

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Observation f84ed645-ac95-4e5c-8faf-5b5d2a0b7b28 · outbound

This paper cites Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals.circulation, 101(23):e215–e220, 2000.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals.circulation, 101(23):e215–e220, 2000

Reference 37

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no resolver link, observed 2026-07-11T22:59:23.504518Z

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Observation d3df3231-d2ff-4e91-a358-3cb0a9f91fa7 · outbound

This paper cites Bci2000: a general-purpose brain-computer interface (bci) system.IEEE Transactions on biomedical engineering, 51(6):1034–1043, 2004.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Bci2000: a general-purpose brain-computer interface (bci) system.IEEE Transactions on biomedical engineering, 51(6):1034–1043, 2004

Reference 38

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Observation f4b59ae1-47bb-464e-9781-676df526b33f · outbound

This paper cites A large finer-grained affective computing eeg dataset.Scientific Data, 10(1):740, 2023.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models A large finer-grained affective computing eeg dataset.Scientific Data, 10(1):740, 2023

Reference 39

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Observation f4acfb29-6f1b-4d6a-99f3-03bdf18355ef · outbound

This paper cites an unresolved cited work.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Unresolved cited work

Reference 40

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Observation 08ba9f07-936e-4eba-8018-b2a5c6455fdb · outbound

This paper cites Limitations.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Limitations

Reference 41

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no resolver link, observed 2026-07-11T22:59:23.504518Z

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Observation 755d677d-548a-4702-9377-afbcf033174e · outbound

This paper cites Guidelines: • The answer [N/A] means that the paper does not involve crowdsourcing nor research with human subjects.

NeuroOnline: Bridging Pretraining and Online Adaptation for EEG Foundation Models Guidelines: • The answer [N/A] means that the paper does not involve crowdsourcing nor research with human subjects

Reference 42

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no resolver link, observed 2026-07-11T22:59:23.504518Z

Source-reported events for the cited work

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Pith citing papers

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