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Paper Citation Record · LEDGER

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding

As of 20 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.03094.

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

pith.paper-citation-record.v1
2607.03094 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T04:57:58.988483Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

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

26 of 26 outbound references displayed

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  • unresolved25
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External citation measurements

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Outbound references

Observation b29e7784-5153-4eb7-bc3c-89b4256a2b31 · outbound

This paper cites and Valdes-Sosa, P.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding and Valdes-Sosa, P

Reference 1

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Observation 06bab2b2-3e84-460a-b199-10c0945dd1ac · outbound

This paper cites Topological superconductivity in tripartite superconductor-ferromagnet-semiconductor nanowires.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Topological superconductivity in tripartite superconductor-ferromagnet-semiconductor nanowires

Reference 2

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Observation 40fca344-8cc5-42b6-a432-2b8fa1f2b075 · outbound

This paper cites Frontiers in Human Neuroscience14, 37 (2020).https://doi.org/10.3389/fnhum.2020.00037.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Frontiers in Human Neuroscience14, 37 (2020).https://doi.org/10.3389/fnhum.2020.00037

Reference 3

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Observation 89d09487-0ddb-4560-b89b-c3ceed39a5cc · outbound

This paper cites IEEE Trans- actions on Biomedical Engineering51(6), 1034–1043 (2004).https://doi.org/ 10.1109/TBME.2004.827072.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding IEEE Trans- actions on Biomedical Engineering51(6), 1034–1043 (2004).https://doi.org/ 10.1109/TBME.2004.827072

Reference 4

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Observation 6d788541-8797-4277-99a7-97b2c94dc12a · outbound

This paper cites an unresolved cited work.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Unresolved cited work

Reference 5

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Observation 6f9289b7-ddfe-44c9-910d-afa56e986f66 · outbound

This paper cites and Wu, D.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding and Wu, D

Reference 6

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Observation 3cd25dca-6972-48dc-bc96-710b2e261faa · outbound

This paper cites 16000–16009.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding 16000–16009

Reference 7

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Observation 96e2b2c3-b8cf-4d4f-9666-913de833c177 · outbound

This paper cites Curran Associates, Red Hook (2025).https://arxiv.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Curran Associates, Red Hook (2025).https://arxiv

Reference 8

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Observation db07a472-0c41-474c-9583-cc7c81cc2cf3 · outbound

This paper cites NeuralBench: A Unifying Framework to Benchmark NeuroAI Models.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding NeuralBench: A Unifying Framework to Benchmark NeuroAI Models

Reference 9

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Observation 8734e2ab-11cd-4a94-b72e-99c6085c92d2 · outbound

This paper cites In: International Confer- ence on Learning Representations (ICLR).

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: International Confer- ence on Learning Representations (ICLR)

Reference 10

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Observation af421b70-ee48-4b1f-b563-1e896da26576 · outbound

This paper cites In: NeurIPS 2025 Workshop: Foun- dation Models for the Brain and Body (2025).

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: NeurIPS 2025 Workshop: Foun- dation Models for the Brain and Body (2025)

Reference 11

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Observation 6396321a-28ee-4516-8ca2-345df87783e0 · outbound

This paper cites Mtlora: A low-rank adaptation approach for efficient multi-task learning,.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Mtlora: A low-rank adaptation approach for efficient multi-task learning,

Reference 12

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Observation c7647850-1f39-4662-a9de-66a2af925453 · outbound

This paper cites Fine-tuning with reserved majority for noise reduction,.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Fine-tuning with reserved majority for noise reduction,

Reference 13

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Observation 167086f2-19cd-4201-9b39-02797dbf90bf · outbound

This paper cites In: 34th European Signal Processing Conference (EUSIPCO).

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: 34th European Signal Processing Conference (EUSIPCO)

Reference 14

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Observation 0128cdfb-ff94-46dd-a3d2-0ca3e7058377 · outbound

This paper cites Institute for Knowledge Discovery (Laboratory of Brain-Computer Interfaces), Graz University of Technology (2008).

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Institute for Knowledge Discovery (Laboratory of Brain-Computer Interfaces), Graz University of Technology (2008)

Reference 15

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Observation 833c7c2b-c527-415f-8264-e109564da440 · outbound

This paper cites In: Advances in Neural Information Processing Systems, vol.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: Advances in Neural Information Processing Systems, vol

Reference 16

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Observation 64053c5b-8172-4aea-955a-354290177065 · outbound

This paper cites In: Advances in Neural Information Processing Systems, vol.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: Advances in Neural Information Processing Systems, vol

Reference 17

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Observation 0b6f6b6f-65ba-46ce-a12a-965f7cc298d2 · outbound

This paper cites GLU Variants Improve Transformer.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding GLU Variants Improve Transformer

Reference 18

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Observation 9d63ef09-59a3-40a2-aba4-bc23053eb822 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 19

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Observation cffd64f3-1c9e-4cdc-aa95-732353e43f4b · outbound

This paper cites Journal of Neural Engineering15(6), 066011 (2018).https://doi.org/10.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Journal of Neural Engineering15(6), 066011 (2018).https://doi.org/10

Reference 20

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Observation d8b2d27f-c5f5-4798-8314-9da500a46f92 · outbound

This paper cites The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark

Reference 21

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Observation f070d0dd-9c0f-43e9-9c12-4833fd7ee45a · outbound

This paper cites Circulation101(23), e215–e220 (2000).https://doi.org/10.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Circulation101(23), e215–e220 (2000).https://doi.org/10

Reference 22

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Observation 7ccd30d8-b1c4-455c-b2a6-1f2c359f3beb · outbound

This paper cites Scientific Data12, 1451 (2025).https: //doi.org/10.1038/s41597-025-05767-2.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding Scientific Data12, 1451 (2025).https: //doi.org/10.1038/s41597-025-05767-2

Reference 23

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Observation 9e96771e-106d-40d3-80f5-d763c5a41f71 · outbound

This paper cites In: International Conference on Learning Rep- resentations (ICLR) (2024).

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: International Conference on Learning Rep- resentations (ICLR) (2024)

Reference 24

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Observation 5e97156f-e070-445d-b057-41357e518a4a · outbound

This paper cites In: Advances in Neural Infor- mation Processing Systems (NeurIPS) (2025).

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: Advances in Neural Infor- mation Processing Systems (NeurIPS) (2025)

Reference 25

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Observation ad042819-25c0-42e5-8f33-dc31f66cdfad · outbound

This paper cites In: International Conferenceon LearningRepresentations(2019).https://openreview.net/forum? id=Bkg6RiCqY7.

Stacked LoRA for Subject-Adaptive EEG Foundation Models in Motor Imagery Decoding In: International Conferenceon LearningRepresentations(2019).https://openreview.net/forum? id=Bkg6RiCqY7

Reference 26

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Pith citing papers

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