collaborators

15 papers

cs.AI2026

CogniFold: Always-On Proactive Memory via Cognitive Folding

Suli Wang, Yiqun Duan, Yu Deng +6

Existing agent memory remains predominantly reactive and retrieval-based, lacking the capacity to autonomously organize experience into persistent cognitive structure. Toward genui…

cs.LG2026

BrainPro: Towards Large-scale Brain State-aware EEG Representation Learning

Yi Ding, Muyun Jiang, Weibang Jiang +6

Electroencephalography (EEG) reflects underlying brain states, whose activities are distributed across brain regions and manifest as spatial patterns on the scalp. Learning these s…

cs.AI2026

InA-Probe: Instruction-Aware Active Probing for Time Series Forecasting with LLMs

Peiliang Gong, Emadeldeen Eldele, Chenyu Liu +8

Large Language Models (LLMs) have recently demonstrated impressive potential for time series forecasting. However, existing methods predominantly rely on passive modality alignment…

cs.LG2026

EEG-Based Multimodal Learning via Hyperbolic Mixture-of-Curvature Experts

Runhe Zhou, Shanglin Li, Guanxiang Huang +5

Electroencephalography (EEG)-based multimodal learning integrates brain signals with complementary modalities to improve mental state assessment, providing great clinical potential…

cs.LG2026

DLink: Distilling Layer-wise and Dominant Knowledge from EEG Foundation Models

Jingyuan Wang, Zhihao Jia, Chenyu Liu +7

EEG foundation models (EFMs) achieve strong cross-subject and cross-task generalization through large-scale pretraining and downstream fine-tuning. Through empirical analysis, we o…

eess.SP2026

Foundation Model Guided Dual-Branch Co-Adaptation for Source-Free EEG Decoding

Peiliang Gong, Han Zhang, Zhen Jiang +5

Source-free domain adaptation (SFDA) provides a practical solution to cross-subject EEG decoding by adapting source-pretrained models to unlabeled target domains without accessing…