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20242026
most citedChannel Reflection: Knowledge-Driven Data Augmentation for EEG-Based Brain-Computer Interfaces

27 citations · 95 across the 17 of their papers we have counts for

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6 papers · 1 filter

cs.LG2026

SCORE: Subject Coordinate Recovery for Label-Free Cross-Subject EEG-to-Image Retrieval

Zhenyao Cui, Siyuan Kan, Siyang Li +2

Accurate visual decoding can reveal how the brain represents visual information and recover perceived content from neural signals such as electroencephalography (EEG), with potenti…

cs.HC2026

Temporal Out-of-Distribution Detection for Asynchronous Motor Imagery Brain-Computer Interfaces

Chenhao Liu, Siyang Li, Luofei Tan +1

Real online brain--computer interfaces operate on continuous electroencephalography (EEG) streams, where users are usually at rest and enter motor-imagery task states only intermit…

eess.SP2026

TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning

Siyang Li, Yize Chen, Zijie Zhu +4

Time Series Foundation Models (TSFMs) have demonstrated strong generalization capability and data efficiency in time series forecasting through large-scale pretraining. However, ad…

cs.LG2026

Synthetic Data Generation for Brain-Computer Interfaces: Overview, Benchmarking, and Future Directions

Ziwei Wang, Zhentao He, Xingyi He +6

Deep learning has achieved transformative performance across diverse domains, largely driven by large-scale and high-quality training data. In contrast, the development of brain-co…

cs.HC2026

RAICL: Retrieval-Augmented In-Context Learning for Vision-Language-Model Based EEG Seizure Detection

Siyang Li, Zhuoya Wang, Xiyan Gui +4

Electroencephalogram (EEG) decoding is a critical component of medical diagnostics, rehabilitation engineering, and brain-computer interfaces. However, contemporary decoding method…

cs.HC2026

Backpropagation-Free Test-Time Adaptation for Lightweight EEG-Based Brain-Computer Interfaces

Siyang Li, Jiayi Ouyang, Zhenyao Cui +4

Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) face significant deployment challenges due to inter-subject variability, signal non-stationarity, and computationa…