4 papers
Scaling Multi-Agent Systems with Prospect-State Propagation
Zhimei Chen, Mu Chen, Fakhri Karray
Current LLM-based multi-agent systems (MAS) periodically compress intermediate states to reduce inference-time token consumption, thereby attempting to incorporate more agents. How…
Empowering Economic Simulation Through Situation-Aware Llm-Driven Generative System
Zhimei Chen, Mu Chen
Traditional economic modeling typically follows a TOP-DOWN paradigm, neglecting individual diversity and the complexity of social interactions. To better capture the complexity of…
CG-MambaNet: A spatiotemporal framework for cross-patient epileptic seizure prediction using CNN-GCN-Mamba-BiLSTM with event-level clinical evaluation
Mufeng Chen, Qi Wu, Bingchao Huang +6
Epileptic seizure prediction from scalp EEG is critical for closed-loop neurostimulation therapy. Existing deep-learning methods share two architectural limitations: they model EEG…
CLSP-REQA: A Real-Time Quality-Aware Closed-Loop Seizure Prediction Framework with Mamba-BiLSTM and Confidence-Gated Intervention
Mufeng Chen, Qi Wu, Bingchao Huang +4
Reliable seizure prediction is a prerequisite for closed-loop neurostimulation therapy, yet existing methods rarely account for the variability in EEG signal quality encountered in…