16 citations · 21 across the 13 of their papers we have counts for
14 papers
BrainStack: Neuro-MoE with Functionally Guided Expert Routing for EEG-Based Language Decoding
Ziyi Zhao, Jinzhao Zhou, Xiaowei Jiang +6
Decoding linguistic information from electroencephalography (EEG) remains challenging due to the brain's distributed and nonlinear organization. We present BrainStack, a functional…
HuMam: Humanoid Motion Control via End-to-End Deep Reinforcement Learning with Mamba
Yinuo Wang, Yuanyang Qi, Jinzhao Zhou +2
End-to-end reinforcement learning (RL) for humanoid locomotion is appealing for its compact perception-action mapping, yet practical policies often suffer from training instability…
Survival Games: Human-LLM Strategic Showdowns under Severe Resource Scarcity
Zhihong Chen, Yiqian Yang, Jinzhao Zhou +3
The rapid advancement of large language models (LLMs) raises critical concerns about their ethical alignment, particularly in scenarios where human and AI co-exist under the confli…
Pretraining Large Brain Language Model for Active BCI: Silent Speech
Jinzhao Zhou, Zehong Cao, Yiqun Duan +9
This paper explores silent speech decoding in active brain-computer interface (BCI) systems, which offer more natural and flexible communication than traditional BCI applications.…
E2H: A Two-Stage Non-Invasive Neural Signal Driven Humanoid Robotic Whole-Body Control Framework
Yiqun Duan, Qiang Zhang, Jinzhao Zhou +9
Recent advancements in humanoid robotics, including the integration of hierarchical reinforcement learning-based control and the utilization of LLM planning, have significantly enh…
BELT-2: Bootstrapping EEG-to-Language representation alignment for multi-task brain decoding
Jinzhao Zhou, Yiqun Duan, Fred Chang +3
The remarkable success of large language models (LLMs) across various multi-modality applications is well established. However, integrating large language models with humans, or br…
Enhancing End-to-End Autonomous Driving Systems Through Synchronized Human Behavior Data
Yiqun Duan, Zhuoli Zhuang, Jinzhao Zhou +3
This paper presents a pioneering exploration into the integration of fine-grained human supervision within the autonomous driving domain to enhance system performance. The current…
Masked EEG Modeling for Driving Intention Prediction
Jinzhao Zhou, Justin Sia, Yiqun Duan +3
Driving under drowsy conditions significantly escalates the risk of vehicular accidents. Although recent efforts have focused on using electroencephalography to detect drowsiness,…
Towards Linguistic Neural Representation Learning and Sentence Retrieval from Electroencephalogram Recordings
Jinzhao Zhou, Yiqun Duan, Ziyi Zhao +4
Decoding linguistic information from non-invasive brain signals using EEG has gained increasing research attention due to its vast applicational potential. Recently, a number of wo…
DeWave: Discrete EEG Waves Encoding for Brain Dynamics to Text Translation
Yiqun Duan, Jinzhao Zhou, Zhen Wang +2
The translation of brain dynamics into natural language is pivotal for brain-computer interfaces (BCIs). With the swift advancement of large language models, such as ChatGPT, the n…
BELT:Bootstrapping Electroencephalography-to-Language Decoding and Zero-Shot Sentiment Classification by Natural Language Supervision
Jinzhao Zhou, Yiqun Duan, Yu-Cheng Chang +2
This paper presents BELT, a novel model and learning framework for the pivotal topic of brain-to-language translation research. The translation from noninvasive brain signals into…
Domain-Specific Denoising Diffusion Probabilistic Models for Brain Dynamics
Yiqun Duan, Jinzhao Zhou, Zhen Wang +3
The differences in brain dynamics across human subjects, commonly referred to as human artifacts, have long been a challenge in the field, severely limiting the generalizability of…
Generalizing Multimodal Variational Methods to Sets
Jinzhao Zhou, Yiqun Duan, Zhihong Chen +2
Making sense of multiple modalities can yield a more comprehensive description of real-world phenomena. However, learning the co-representation of diverse modalities is still a lon…
Graph-based Facial Affect Analysis: A Review
Yang Liu, Xingming Zhang, Yante Li +3
As one of the most important affective signals, facial affect analysis (FAA) is essential for developing human-computer interaction systems. Early methods focus on extracting appea…