Dongrui Wu
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View article: Discovery of the reward function for embodied reinforcement learning agents
Discovery of the reward function for embodied reinforcement learning agents Open
Reward maximization is a fundamental principle in both the survival and evolution of biological organisms. In particular, in the contexts of cognitive science and embodied agents, reward-driven behavior has been widely regarded as importan…
View article: How does physical distance from the epicenter influence misinformation sharing? The roles of negative affect and social media engagement
How does physical distance from the epicenter influence misinformation sharing? The roles of negative affect and social media engagement Open
This study examines the relationship between physical distance from the epicenter and online misinformation sharing behavior, along with the underlying mechanisms involving emotions and social media usage. A cross-sectional survey of 1094 …
View article: Design and Implementation of a Medical Question Answering System Based on Retrieval-Augmented Generation
Design and Implementation of a Medical Question Answering System Based on Retrieval-Augmented Generation Open
With the rapid growth of medical information demand, providing accurate and reliable medical question-answering services has become a pressing challenge. Traditional generative Q&A models are prone to hallucinations, frequently generating …
View article: The 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real): Methods and Results
The 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real): Methods and Results Open
This paper reviews the 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real), held in conjunction with ICCV 2025. The workshop aimed to bridge the gap between the theoretical promise of D…
View article: MIRepNet: A Pipeline and Foundation Model for EEG-Based Motor Imagery Classification
MIRepNet: A Pipeline and Foundation Model for EEG-Based Motor Imagery Classification Open
Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices. Recent EEG foundation models aim to learn generalized representations across diverse BCI paradigms. However, these approaches overlook fun…
View article: AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding
AFPM: Alignment-based Frame Patch Modeling for Cross-Dataset EEG Decoding Open
Electroencephalogram (EEG) decoding models for brain-computer interfaces (BCIs) struggle with cross-dataset learning and generalization due to channel layout inconsistencies, non-stationary signal distributions, and limited neurophysiologi…
View article: Modeling spatial and temporal urban environmental noise using street view imagery and machine learning
Modeling spatial and temporal urban environmental noise using street view imagery and machine learning Open
View article: DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding
DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding Open
Electroencephalography (EEG)-based brain-computer interfaces (BCIs) transform spontaneous/evoked neural activity into control commands for external communication. While convolutional neural networks (CNNs) remain the mainstream backbone fo…
View article: Magnetoencephalography (MEG) Based Non-Invasive Chinese Speech Decoding
Magnetoencephalography (MEG) Based Non-Invasive Chinese Speech Decoding Open
As an emerging paradigm of brain-computer interfaces (BCIs), speech BCI has the potential to directly reflect auditory perception and thoughts, offering a promising communication alternative for patients with aphasia. Chinese is one of the…
View article: CLEAN-MI: A Scalable and Efficient Pipeline for Constructing High-Quality Neurodata in Motor Imagery Paradigm
CLEAN-MI: A Scalable and Efficient Pipeline for Constructing High-Quality Neurodata in Motor Imagery Paradigm Open
The construction of large-scale, high-quality datasets is a fundamental prerequisite for developing robust and generalizable foundation models in motor imagery (MI)-based brain-computer interfaces (BCIs). However, EEG signals collected fro…
View article: SACM: SEEG-Audio Contrastive Matching for Chinese Speech Decoding
SACM: SEEG-Audio Contrastive Matching for Chinese Speech Decoding Open
Speech disorders such as dysarthria and anarthria can severely impair the patient's ability to communicate verbally. Speech decoding brain-computer interfaces (BCIs) offer a potential alternative by directly translating speech intentions i…
View article: CMCRD: Cross-Modal Contrastive Representation Distillation for Emotion Recognition
CMCRD: Cross-Modal Contrastive Representation Distillation for Emotion Recognition Open
Emotion recognition is an important component of affective computing, and also human-machine interaction. Unimodal emotion recognition is convenient, but the accuracy may not be high enough; on the contrary, multi-modal emotion recognition…
View article: Spiking Neural Network for Intra-cortical Brain Signal Decoding
Spiking Neural Network for Intra-cortical Brain Signal Decoding Open
Decoding brain signals accurately and efficiently is crucial for intra-cortical brain-computer interfaces. Traditional decoding approaches based on neural activity vector features suffer from low accuracy, whereas deep learning based appro…
View article: UltraRAG: A Modular and Automated Toolkit for Adaptive Retrieval-Augmented Generation
UltraRAG: A Modular and Automated Toolkit for Adaptive Retrieval-Augmented Generation Open
Retrieval-Augmented Generation (RAG) significantly enhances the performance of large language models (LLMs) in downstream tasks by integrating external knowledge. To facilitate researchers in deploying RAG systems, various RAG toolkits hav…
View article: Physicochemical and functional properties of anthocyanin microparticle encapsulated by ovalbumin and chitosan
Physicochemical and functional properties of anthocyanin microparticle encapsulated by ovalbumin and chitosan Open
View article: Using street view imagery and localized crowdsourcing survey to model perceived safety of the visual built environment by gender
Using street view imagery and localized crowdsourcing survey to model perceived safety of the visual built environment by gender Open
Scholars have documented that perceived safety of the visual built environment (VBE) can influence human behaviors. The dual developments of street view imagery (SVI) and deep learning techniques offer a cost-effective approach to measure …
View article: Canine EEG helps human: cross-species and cross-modality epileptic seizure detection via multi-space alignment
Canine EEG helps human: cross-species and cross-modality epileptic seizure detection via multi-space alignment Open
Epilepsy significantly impacts global health, affecting about 65 million people worldwide, along with various animal species. The diagnostic processes of epilepsy are often hindered by the transient and unpredictable nature of seizures. He…
View article: Revisiting Euclidean alignment for transfer learning in EEG-based brain–computer interfaces
Revisiting Euclidean alignment for transfer learning in EEG-based brain–computer interfaces Open
Due to large intra-subject and inter-subject variabilities of electroencephalogram (EEG) signals, EEG-based brain–computer interfaces (BCIs) usually need subject-specific calibration to tailor the decoding algorithm for each new subject, w…
View article: Multimodal Brain-Computer Interfaces: AI-powered Decoding Methodologies
Multimodal Brain-Computer Interfaces: AI-powered Decoding Methodologies Open
Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices. This review highlights the core decoding algorithms that enable multimodal BCIs, including a dissection of the elements, a unified view of…
View article: Mvcnet: Multi-View Contrastive Network for Motor Imagery Classification
Mvcnet: Multi-View Contrastive Network for Motor Imagery Classification Open
View article: Physicochemical and Functional Properties of Anthocyanin Microparticle Encapsulated by Ovalbumin and Chitosan
Physicochemical and Functional Properties of Anthocyanin Microparticle Encapsulated by Ovalbumin and Chitosan Open
View article: Fstam-Net: A Dual Attention Network for Motor Imagery Decoding and Visualization Analysis
Fstam-Net: A Dual Attention Network for Motor Imagery Decoding and Visualization Analysis Open
View article: Effective and Efficient Intracortical Brain Signal Decoding with Spiking Neural Networks
Effective and Efficient Intracortical Brain Signal Decoding with Spiking Neural Networks Open
View article: PAT: Privacy-preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding
PAT: Privacy-preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding Open
View article: Cation-Driven Electrostatic Modulation Enhances Cr(VI) Reduction by Biochar
Cation-Driven Electrostatic Modulation Enhances Cr(VI) Reduction by Biochar Open
View article: Effective and Efficient Intracortical Brain Signal Decoding with Spiking Neural Networks
Effective and Efficient Intracortical Brain Signal Decoding with Spiking Neural Networks Open
A brain-computer interface (BCI) facilitates direct interaction between the brain and external devices. To concurrently achieve high decoding accuracy and low energy consumption in invasive BCIs, we propose a novel spiking neural network (…
View article: Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment
Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment Open
Epilepsy significantly impacts global health, affecting about 65 million people worldwide, along with various animal species. The diagnostic processes of epilepsy are often hindered by the transient and unpredictable nature of seizures. He…
View article: A3E: Aligned and Augmented Adversarial Ensemble for Accurate, Robust and Privacy-Preserving EEG Decoding
A3E: Aligned and Augmented Adversarial Ensemble for Accurate, Robust and Privacy-Preserving EEG Decoding Open
An electroencephalogram (EEG) based brain-computer interface (BCI) enables direct communication between the brain and external devices. However, EEG-based BCIs face at least three major challenges in real-world applications: data scarcity …
View article: Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces
Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces Open
A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have…
View article: Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification
Knowledge-Data Fusion Based Source-Free Semi-Supervised Domain Adaptation for Seizure Subtype Classification Open
Electroencephalogram (EEG)-based seizure subtype classification enhances clinical diagnosis efficiency. Source-free semi-supervised domain adaptation (SF-SSDA), which transfers a pre-trained model to a new dataset with no source data and l…