23 papers
NeuroCogMap Reveals Cognitive Organization of Large Language Models
Zhongxiang Sun, Haolang Lu, Qiang Ma +11
Understanding how complex cognitive functions are organized within artificial systems is central to interpreting large language models (LLMs) and relating them to biological cognit…
ACPSL: Adaptive Communication-Computation Pipeline Parallel Split Learning over Edge Networks
Chenyu Liu, Zhaoyang Zhang, Zirui Chen +3
In wireless edge networks, split learning (SL) enables base station (BS) to utilize the distributed data and computing power across user equipments (UEs) to achieve collaborative m…
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…
NüshuVoice: Reviving the Voice of Endangered Nüshu with Pitch-Aware Text-to-Speech
Hongkun Yang, Xinhui Yi, Xiyan Zhao +13
Nüshu is an endangered phonetic script historically used by women in Jiangyong County, southern Hunan, China. While existing computational studies of Nüshu mainly focus on textua…
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…
SCOPE: Structured Prototype-Guided Adaptation for EEG Foundation Models with Limited Labels
Jingying Ma, Feng Wu, Yucheng Xing +5
Electroencephalography (EEG) foundation models (EFMs) have shown strong potential for transferable representation learning, yet their adaptation in realistic settings remains chall…