Publications (32)
LaSNN: Layer-wise ANN-to-SNN Distillation for Effective and Efficient Training in Deep Spiking Neural Networks
Di Hong, Jiangrong Shen, Yu Qi +1
Spiking Neural Networks (SNNs) are biologically realistic and practically promising in low-power computation because of their event-driven mechanism. Usually, the training of SNNs…
A Simple Review of EEG Foundation Models: Datasets, Advancements and Future Perspectives
Junhong Lai, Jiyu Wei, Lin Yao +1
Electroencephalogram (EEG) signals play a crucial role in understanding brain activity and diagnosing neurological diseases. Because supervised EEG encoders are unable to learn rob…
Rethinking ANN-based Retrieval: Multifaceted Learnable Index for Large-scale Recommendation System
Jiang Zhang, Yubo Wang, Wei Chang +14
Approximate nearest neighbor (ANN) search is widely used in the retrieval stage of large-scale recommendation systems. In this stage, candidate items are indexed using their learne…
Improving Unsupervised Task-driven Models of Ventral Visual Stream via Relative Position Predictivity
Dazhong Rong, Hao Dong, Xing Gao +5
Based on the concept that ventral visual stream (VVS) mainly functions for object recognition, current unsupervised task-driven methods model VVS by contrastive learning, and have…
Directed tunneling of a prescribed number of dipolar bosons in shaken triple-well potentials
Xiaobing Luo, Yueming Wang, Xiaoguang Yu +4
We propose a scheme for precise control of tunneling dynamics of dipolar bosons in shaken triple-well potentials. In the high-frequency regimes and under the resonance conditions,…
How Charge Carrier Exchange between Absorber and Contact influences Time Constants in the Frequency Domain Response of Perovskite Solar Cells
Sandheep Ravishankar, Zhifa Liu, Yueming Wang +2
A model is derived for the frequency- and time-domain opto-electronic response of perovskite solar cells (PSCs) that emphasizes the role of charge carrier exchange, .i.e. extractio…
Speed-enhanced Subdomain Adaptation Regression for Long-term Stable Neural Decoding in Brain-computer Interfaces
Jiyu Wei, Dazhong Rong, Xinyun Zhu +2
Brain-computer interfaces (BCIs) offer a means to convert neural signals into control signals, providing a potential restoration of movement for people with paralysis. Despite thei…
Layer-dependent Optical and Dielectric Properties of Large-size PdSe Films Grown by Chemical Vapor Deposition
MingYang Wei, Jie Lian, Yu Zhang +3
Palladium diselenide (PdSe), a new type of two-dimensional noble metal dihalides (NMDCs), has received widespread attention for its excellent electrical and optoelectronic prop…
SciLens: Multi-modal Scientific Claim Verification with Agentic Entailment and Grounding
Yueming Wang, Tianshi Zheng, Jiaxin Bai +3
Scientific discovery increasingly relies on automated systems that generate hypotheses, inspect multimodal evidence, and validate claims at scale. Yet scientific claim verification…
Request-Only Optimization for Recommendation Systems
Liang Guo, Wei Li, Lucy Liao +25
Deep Learning Recommendation Models (DLRMs) represent one of the largest machine learning applications on the planet. Industry-scale DLRMs are trained with petabytes of recommendat…
Copiloting Diagnosis of Autism in Real Clinical Scenarios via LLMs
Yi Jiang, Qingyang Shen, Shuzhong Lai +5
Autism spectrum disorder(ASD) is a pervasive developmental disorder that significantly impacts the daily functioning and social participation of individuals. Despite the abundance…
Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
Jiaqi Zhai, Lucy Liao, Xing Liu +9
Large-scale recommendation systems are characterized by their reliance on high cardinality, heterogeneous features and the need to handle tens of billions of user actions on a dail…
Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces
Yu Qi, Bin Liu, Yueming Wang +1
Brain-computer interfaces (BCIs) have enabled prosthetic device control by decoding motor movements from neural activities. Neural signals recorded from cortex exhibit nonstationar…
Self-Attentive Spatio-Temporal Calibration for Precise Intermediate Layer Matching in ANN-to-SNN Distillation
Di Hong, Yueming Wang
Spiking Neural Networks (SNNs) are promising for low-power computation due to their event-driven mechanism but often suffer from lower accuracy compared to Artificial Neural Networ…
Robust Face Recognition by Constrained Part-based Alignment
Yuting Zhang, Kui Jia, Yueming Wang +3
Developing a reliable and practical face recognition system is a long-standing goal in computer vision research. Existing literature suggests that pixel-wise face alignment is the…
Neurocircuitry-Inspired Hierarchical Graph Causal Attention Networks for Explainable Depression Identification
Weidao Chen, Yuxiao Yang, Yueming Wang
Major Depressive Disorder (MDD), affecting millions worldwide, exhibits complex pathophysiology manifested through disrupted brain network dynamics. Although graph neural networks…
Dynamic Ensemble Bayesian Filter for Robust Control of a Human Brain-machine Interface
Yu Qi, Xinyun Zhu, Kedi Xu +6
Objective: Brain-machine interfaces (BMIs) aim to provide direct brain control of devices such as prostheses and computer cursors, which have demonstrated great potential for mobil…
Human-like Cognitive Generalization for Large Models via Brain-in-the-loop Supervision
Jiaxuan Chen, Yu Qi, Yueming Wang +1
Recent advancements in deep neural networks (DNNs), particularly large-scale language models, have demonstrated remarkable capabilities in image and natural language understanding.…
Characterizing Fill Factor Limitations in Perovskite-Silicon Tandem Solar Cells
Yueming Wang, Nan Sun, Chris Dreessen +4
Perovskite-silicon tandem technology has exceeded the single junction theoretical efficiency limit. However, there is still distance to the thermodynamic limit mainly caused by the…
Revisiting Neural Retrieval on Accelerators
Jiaqi Zhai, Zhaojie Gong, Yueming Wang +4
Retrieval finds a small number of relevant candidates from a large corpus for information retrieval and recommendation applications. A key component of retrieval is to model (user,…
Decoding Chinese phonemes from intracortical brain signals with hyperbolic-space neural representations
Xianhan Tan, Junming Zhu, Jianmin Zhang +2
Speech brain-computer interfaces (BCIs), which translate brain signals into spoken words or sentences, have shown significant potential for high-performance BCI communication. Phon…
Sparse Principal Component Analysis via Rotation and Truncation
Zhenfang Hu, Gang Pan, Yueming Wang +1
Sparse principal component analysis (sparse PCA) aims at finding a sparse basis to improve the interpretability over the dense basis of PCA, meanwhile the sparse basis should cover…
Quantum solitons in spin-orbit-coupled Bose-Bose mixtures
Andrea Tononi, Yueming Wang, Luca Salasnich
Recent experimental and theoretical results show that weakly interacting atomic Bose-Bose mixtures with attractive interspecies interaction are stabilized by beyond-mean-field effe…
ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks
Jiangrong Shen, Qi Xu, Jian K. Liu +3
Spiking neural networks (SNNs) have manifested remarkable advantages in power consumption and event-driven property during the inference process. To take full advantage of low powe…
A Cyclic Adaptation-Generalization Framework with Uncertainty-Guided Self-Paced Learning for Long-Term Brain-Machine Interfaces
Jiyu Wei, Di Hong, Zhanjie Zhang +3
Brain-Machine Interfaces (BMIs), which link the brain to external devices, hold great potential in rehabilitation, human performance augmentation, and human-centered robotics. Howe…
A Human-Machine Joint Learning Framework to Boost Endogenous BCI Training
Hanwen Wang, Yu Qi, Lin Yao +3
Brain-computer interfaces (BCIs) provide a direct pathway from the brain to external devices and have demonstrated great potential for assistive and rehabilitation technologies. En…
ASD-Chat: An Innovative Dialogue Intervention System for Children with Autism based on LLM and VB-MAPP
Chengyun Deng, Shuzhong Lai, Chi Zhou +5
Early diagnosis and professional intervention can help children with autism spectrum disorder (ASD) return to normal life. However, the scarcity and imbalance of professional medic…
TD-DPO: Difference-Aware Preference Optimization for Mitigating Sycophancy in Clinical Autism Intervention Dialogue
Shuzhong Lai, Junhong Lai, Chenxi Li +5
The sycophancy of large language models can increase the safety risk in intervention dialogue for autistic children. Supervised fine-tuning can somewhat reduce sycophancy, but rely…
MindGPT: Interpreting What You See with Non-invasive Brain Recordings
Jiaxuan Chen, Yu Qi, Yueming Wang +1
Decoding of seen visual contents with non-invasive brain recordings has important scientific and practical values. Efforts have been made to recover the seen images from brain sign…
Self-Supervised Consistency Enhanced Disentangled Learning for Neural Decoding Generalization in Brain-Machine Interface
Jiyu Wei, Di Hong, Zhanjie Zhang +3
Brain-Machine Interfaces (BMIs) provide a direct communication pathway between the brain and external devices, enabling humans to control assistive and robotic technologies, with p…
From Synthesis to Clinical Assistance: A Strategy-Aware Agent Framework for Autism Intervention based on Real Clinical Dataset
Junhong Lai, Shuzhong Lai, Yanhao Yu +5
The development of AI-assisted Early Intensive Behavioral Intervention (EIBI) for Autism Spectrum Disorder (ASD) is severely constrained by data scarcity. Furthermore, while Applie…
Spectral Sparse Representation for Clustering: Evolved from PCA, K-means, Laplacian Eigenmap, and Ratio Cut
Zhenfang Hu, Gang Pan, Yueming Wang +1
Dimensionality reduction, cluster analysis, and sparse representation are basic components in machine learning. However, their relationships have not yet been fully investigated. I…