Publications (22)
Tumor can originate from not only rare cancer stem cells
Min Hu, Yu-Fei He
Tumors are believed to consist of a heterogeneous population of tumor cells originating from rare cancer stem cells (CSCs). However, emerging evidences show that tumor may also ori…
Energy threshold in Smith-Purcell radiation
Sunchao Huang, Xihang Shi, Xiaoqiuyan Zhang +6
Smith Purcell radiation has emerged as a crucial platform for investigating light-matter interactions and developing compact, tunable light sources that span from microwaves to X-r…
Lossless Attention in Convolutional Networks for Facial Expression Recognition in the Wild
Chuang Wang, Ruimin Hu, Min Hu +5
Unlike the constraint frontal face condition, faces in the wild have various unconstrained interference factors, such as complex illumination, changing perspective and various occl…
Look, Listen, and Answer: Overcoming Biases for Audio-Visual Question Answering
Jie Ma, Min Hu, Pinghui Wang +5
Audio-Visual Question Answering (AVQA) is a complex multi-modal reasoning task, demanding intelligent systems to accurately respond to natural language queries based on audio-video…
AR Visualization System for Ship Detection and Recognition Based on AI
Ziqi Ye, Limin Huang, Yongji Wu +1
Augmented reality technology has been widely used in industrial design interaction, exhibition guide, information retrieval and other fields. The combination of artificial intellig…
Futures Quantitative Investment with Heterogeneous Continual Graph Neural Network
Min Hu, Zhizhong Tan, Bin Liu +1
This study aims to address the challenges of futures price prediction in high-frequency trading (HFT) by proposing a continuous learning factor predictor based on graph neural netw…
Two-level Attention with Two-stage Multi-task Learning for Facial Emotion Recognition
Xiaohua Wang, Muzi Peng, Lijuan Pan +3
Compared with facial emotion recognition on categorical model, the dimensional emotion recognition can describe numerous emotions of the real world more accurately. Most prior work…
HUSH-Bench: Measuring Memory-Use Boundaries for Sensitive History in Conversational Agents
Lingxiang Xu, Jiaoyun Yang, Min Hu +2
Long-term memory helps conversational agents maintain continuity across sessions, while relevance and current-turn warrant remain distinct decisions. We study this boundary under a…
Speed by Simplicity: A Single-Stream Architecture for Fast Audio-Video Generative Foundation Model
SII-GAIR, Sand. ai, : +43
We present daVinci-MagiHuman, an open-source audio-video generative foundation model for human-centric generation. daVinci-MagiHuman jointly generates synchronized video and audio…
Enhancing heat transfer in X-ray tube by van der heterostructures-based thermionic emission
Sunchao Huang, Suguo Chen, Yue Wang +7
Van der Waals (vdW) heterostructures have attracted much attention due to their distinctive optical, electrical, and thermal properties, demonstrating promising potential in areas…
Speaker Change Detection for Transformer Transducer ASR
Jian Wu, Zhuo Chen, Min Hu +2
Speaker change detection (SCD) is an important feature that improves the readability of the recognized words from an automatic speech recognition (ASR) system by breaking the word…
Atomic origin for hydrogenation promoted bulk oxygen vacancies removal in vanadium dioxide
Bowen Li, Min Hu, Hui Ren +5
Oxygen vacancies (VO), a common type of point defects in metal oxides materials, play important roles on the physical and chemical properties. To obtain stoichiometric oxide crysta…
Neural CRF transducers for sequence labeling
Kai Hu, Zhijian Ou, Min Hu +1
Conditional random fields (CRFs) have been shown to be one of the most successful approaches to sequence labeling. Various linear-chain neural CRFs (NCRFs) are developed to impleme…
ReverseNER: A Self-Generated Example-Driven Framework for Zero-Shot Named Entity Recognition with Large Language Models
Anbang Wang, Difei Mei, Zhichao Zhang +9
This paper presents ReverseNER, a method aimed at overcoming the limitation of large language models (LLMs) in zero-shot named entity recognition (NER) tasks, arising from their re…
Robust Anomaly Detection for Time-series Data
Min Hu, Yi Wang, Xiaowei Feng +3
Time-series anomaly detection plays a vital role in monitoring complex operation conditions. However, the detection accuracy of existing approaches is heavily influenced by pattern…
Dual-Splitting Conformal Prediction for Multi-Step Time Series Forecasting
Qingdi Yu, Zhiwei Cao, Ruihang Wang +5
Time series forecasting is crucial for applications like resource scheduling and risk management, where multi-step predictions provide a comprehensive view of future trends. Uncert…
Adaptive loose optimization for robust question answering
Jie Ma, Pinghui Wang, Zewei Wang +4
Question answering methods are well-known for leveraging data bias, such as the language prior in visual question answering and the position bias in machine reading comprehension (…
Enhancing Zero-Shot Time Series Forecasting in Off-the-Shelf LLMs via Noise Injection
Xingyou Yin, Ceyao Zhang, Min Hu +1
Large Language Models (LLMs) have demonstrated effectiveness as zero-shot time series (TS) forecasters. The key challenge lies in tokenizing TS data into textual representations th…
A compact unshielded optically-pumped magnetic gradiometer
Hangfei Ye, Chenlu Xu, Min Hu +1
Optically-pumped magnetic gradiometers (OPGs) play a crucial role in applications such as magnetic anomaly detection and bio-magnetic measurements. This study classifies current OP…
Ultrahigh ion diffusion in oxide crystal by engineering the interfacial transporter channels
Liang Li, Min Hu, Changlong Hu +6
The mass storage and removal in solid conductors always played vital role on the technological applications such as modern batteries, permeation membranes and neuronal computations…
MAGI-1: Autoregressive Video Generation at Scale
Sand. ai, Hansi Teng, Hongyu Jia +36
We present MAGI-1, a world model that generates videos by autoregressively predicting a sequence of video chunks, defined as fixed-length segments of consecutive frames. Trained to…
A general approach to improve the bias stability of NMR gyroscope
Haifeng Dong, Min Hu
In recent years, progress in improving the bias stability of NMR gyroscopes has been hindered. Taking inspiration from the core idea of rotation modulation in the strapdown inertia…