Paper Citation Record · LEDGER

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization

As of 21 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2602.01728.

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pith.paper-citation-record.v1
2602.01728 v2

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measured 40 of 40 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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40 of 40 outbound references displayed

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Outbound references

Observation d5f5221c-2c53-41f1-990b-8f7cdec9aa39 · outbound

This paper cites Aasm scoring manual updates for 2017,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Aasm scoring manual updates for 2017,

Reference 1

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Observation b91599b6-57f7-4f92-b894-2c5567997597 · outbound

This paper cites The effect of head-related fil- tering and ear-specific decoding bias on auditory attention detection.Journal of Neural Engineering, 13(5):056014,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization The effect of head-related fil- tering and ear-specific decoding bias on auditory attention detection.Journal of Neural Engineering, 13(5):056014,

Reference 6

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Observation 861d0918-74bd-4687-9aee-64c5845d0bdf · outbound

This paper cites Noise-robust cortical tracking of at- tended speech in real-world acoustic scenes.NeuroImage, 156:435–444,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Noise-robust cortical tracking of at- tended speech in real-world acoustic scenes.NeuroImage, 156:435–444,

Reference 9

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Observation b23ecbf5-10a2-4bc7-8738-96070c19a1c9 · outbound

This paper cites Physiobank, physiotoolkit, and physionet: components of a new re- search resource for complex physiologic signals.Circu- lation, 101(23):e215–e220,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Physiobank, physiotoolkit, and physionet: components of a new re- search resource for complex physiologic signals.Circu- lation, 101(23):e215–e220,

Reference 10

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Observation 97b51c00-a6de-4074-aefe-39e03c0b1efa · outbound

This paper cites SalientSleepNet: Multimodal salient wave detection network for sleep stag- ing.IJCAI,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization SalientSleepNet: Multimodal salient wave detection network for sleep stag- ing.IJCAI,

Reference 12

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Observation ebe295aa-2867-4691-a159-758108a44f49 · outbound

This paper cites De- tecting the locus of auditory attention based on the spectro- spatial-temporal analysis of EEG.Journal of Neural En- gineering, 19(5):056035,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization De- tecting the locus of auditory attention based on the spectro- spatial-temporal analysis of EEG.Journal of Neural En- gineering, 19(5):056035,

Reference 13

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Observation d250393e-02f4-41b9-b55c-ac55345ee51e · outbound

This paper cites How EEG preprocessing shapes de- coding performance.Nature Communications Biology, 8(1):1039,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization How EEG preprocessing shapes de- coding performance.Nature Communications Biology, 8(1):1039,

Reference 15

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Observation a1068107-3ce9-4efc-8248-3857e06f717b · outbound

This paper cites ISRUC-Sleep: A comprehensive public dataset for sleep researchers.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization ISRUC-Sleep: A comprehensive public dataset for sleep researchers

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Observation b36aed04-f93b-48a7-94f8-32f1979c3176 · outbound

This paper cites EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces

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Resolution: unresolved; no resolver link, observed 2026-08-03T05:39:52.466118Z

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Observation b3170c5f-ed8c-47ad-be72-d5b6b9c61db7 · outbound

This paper cites Sparse mixture-of-experts are domain generalizable learn- ers.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Sparse mixture-of-experts are domain generalizable learn- ers

Reference 20

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Observation 920e65c2-462b-41af-9482-cf750a5d23e0 · outbound

This paper cites DBPNet: Dual- branch parallel network with temporal-frequency fusion for auditory attention detection.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization DBPNet: Dual- branch parallel network with temporal-frequency fusion for auditory attention detection

Reference 23

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Observation dd7d2a22-afb6-4f4c-97d0-d46d24992b4c · outbound

This paper cites U-time: A fully convolutional network for time series segmentation applied to sleep staging.NeurIPS, 32,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization U-time: A fully convolutional network for time series segmentation applied to sleep staging.NeurIPS, 32,

Reference 24

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Observation c12fb14e-3cff-484a-9673-c7262d0f703d · outbound

This paper cites Ensemble deep learning and machine learn- ing: applications, opportunities, challenges, and future di- rections.Studies in Medical and Health Sciences, 1(2):18– 41,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Ensemble deep learning and machine learn- ing: applications, opportunities, challenges, and future di- rections.Studies in Medical and Health Sciences, 1(2):18– 41,

Reference 25

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This paper cites BCI2000: a general-purpose brain-computer inter- face (BCI) system.Transactions on Biomedical Engineer- ing, 51(6):1034–1043,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization BCI2000: a general-purpose brain-computer inter- face (BCI) system.Transactions on Biomedical Engineer- ing, 51(6):1034–1043,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T05:39:53.167368Z

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Observation 296b2b5b-5ea0-48ef-ac0a-9cee18661a22 · outbound

This paper cites Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition.Transactions on Affective Comput- ing, 14(3):2496–2511,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Contrastive learning of subject-invariant EEG representations for cross-subject emotion recognition.Transactions on Affective Comput- ing, 14(3):2496–2511,

Reference 28

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Observation e4d29d52-f247-47ad-a336-c3e50fafff2d · outbound

This paper cites EEG conformer: Convolutional transformer for EEG decoding and visualization.Transactions on Neural Systems and Rehabilitation Engineering, 31:710–719,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization EEG conformer: Convolutional transformer for EEG decoding and visualization.Transactions on Neural Systems and Rehabilitation Engineering, 31:710–719,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T05:39:53.409773Z

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Observation 3af8a882-92f2-4d13-ab63-2c8a54f652f9 · outbound

This paper cites Towards recognizing spatial-temporal collaboration of EEG phase brain networks for emotion understanding.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Towards recognizing spatial-temporal collaboration of EEG phase brain networks for emotion understanding

Reference 30

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Observation 407f951b-1372-4ad1-bbfa-b1a67a9a6f39 · outbound

This paper cites TinySleepNet: An efficient deep learning model for sleep stage scoring based on raw single-channel EEG.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization TinySleepNet: An efficient deep learning model for sleep stage scoring based on raw single-channel EEG

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This paper cites Review of the BCI competition IV.Frontiers in Neuroscience, 6:55,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Review of the BCI competition IV.Frontiers in Neuroscience, 6:55,

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Observation d09834b7-3d5d-4acf-a2d8-271aaf36a286 · outbound

This paper cites CBraMod: A criss-cross brain foundation model for EEG decoding.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization CBraMod: A criss-cross brain foundation model for EEG decoding

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Observation ca6677f9-b8f3-4f7b-8d36-5dca09ec70a7 · outbound

This paper cites What can neural networks reason about? InICLR,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization What can neural networks reason about? InICLR,

Reference 36

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Observation c3f215c1-9427-4fa5-b6fc-849d072ff713 · outbound

This paper cites DARNet: Dual attention refinement network with spatiotemporal construction for auditory attention detection.NeurIPS, 37:31688–31707,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization DARNet: Dual attention refinement network with spatiotemporal construction for auditory attention detection.NeurIPS, 37:31688–31707,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T05:39:53.936512Z

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This paper cites Rotboost: A technique for combining rota- tion forest and adaboost.Pattern Recognition Letters, 29(10):1524–1536,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Rotboost: A technique for combining rota- tion forest and adaboost.Pattern Recognition Letters, 29(10):1524–1536,

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Observation 914e857c-2652-411e-bc5d-ff5f95e1045b · outbound

This paper cites CSBrain: A cross-scale spatiotemporal brain foundation model for EEG decoding.NeurIPS, 2025.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization CSBrain: A cross-scale spatiotemporal brain foundation model for EEG decoding.NeurIPS, 2025

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Observation 5bc2b66a-2941-4c0b-81c5-91a4c3bf9d0c · outbound

This paper cites Low-latency auditory spatial attention detection based on spectro-spatial features from eeg.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Low-latency auditory spatial attention detection based on spectro-spatial features from eeg

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Observation c868e1f5-eb2f-4707-afa0-f814eed602a3 · outbound

This paper cites Optimized bi-objective EEG chan- nel selection and cross-subject generalization with brain– computer interfaces.Transactions on Human-Machine Systems, 46(6):777–786,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Optimized bi-objective EEG chan- nel selection and cross-subject generalization with brain– computer interfaces.Transactions on Human-Machine Systems, 46(6):777–786,

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Observation d7217807-f7e0-422c-8ec3-f2a60931dc56 · outbound

This paper cites Deep learning with convolutional neural networks for EEG decoding and visualization.Human Brain Mapping, 38(11):5391–5420,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Deep learning with convolutional neural networks for EEG decoding and visualization.Human Brain Mapping, 38(11):5391–5420,

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Observation 2e8e3dbd-090a-4d69-857e-3eb970c087cc · outbound

This paper cites Cross-subject emotion recognition using deep adaptation networks.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Cross-subject emotion recognition using deep adaptation networks

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This paper cites Evolutionary ensem- ble learning for eeg-based cross-subject emotion recog- nition.Journal of Biomedical and Health Informatics, 28(7):3872–3881,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Evolutionary ensem- ble learning for eeg-based cross-subject emotion recog- nition.Journal of Biomedical and Health Informatics, 28(7):3872–3881,

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization EEG-based detection of the locus of auditory attention with convolutional neural net- works.Elife, 10:e56481,

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This paper cites MSFNet: Multi-scale fusion network for brain-controlled speaker extraction.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization MSFNet: Multi-scale fusion network for brain-controlled speaker extraction

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Is limited participant diversity impeding EEG- based machine learning?NeurIPS,

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Brain–computer communication: motiva- tion, aim, and impact of exploring a virtual apartment

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This paper cites Ensemble large language models: A sur- vey.Information, 16(8):688,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Ensemble large language models: A sur- vey.Information, 16(8):688,

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This paper cites DeepSleepNet: A model for au- tomatic sleep stage scoring based on raw single-channel EEG.Transactions on Neural Systems and Rehabilitation Engineering, 25(11):1998–2008,.

Aligning Shared and Routed Experts for Cross-Subject EEG Generalization DeepSleepNet: A model for au- tomatic sleep stage scoring based on raw single-channel EEG.Transactions on Neural Systems and Rehabilitation Engineering, 25(11):1998–2008,

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Neuromorphic sequential arena: A benchmark for neuromorphic temporal process- ing.IJCAI,

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Observation 6914a817-0e4d-4896-96a1-072d17d6df37 · outbound

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Large brain model for learning generic repre- sentations with tremendous EEG data in BCI

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Reducing the subject variability of EEG signals with adversarial domain generalization

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Listen- Net: A lightweight spatio-temporal enhancement nested network for auditory attention detection.IJCAI,

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Aligning Shared and Routed Experts for Cross-Subject EEG Generalization Bagging predictors.Machine Learning, 24(2):123–140,

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