4 citations · 9 across the 7 of their papers we have counts for
7 papers
DS-HGCN: A Dual-Stream Hypergraph Convolutional Network for Predicting Student Engagement via Social Contagion
Ziyang Fan, Li Tao, Yi Wang +3
Student engagement is a critical factor influencing academic success and learning outcomes. Accurately predicting student engagement is essential for optimizing teaching strategies…
In-Context Clustering with Large Language Models
Ying Wang, Mengye Ren, Andrew Gordon Wilson
We propose In-Context Clustering (ICC), a flexible LLM-based procedure for clustering data from diverse distributions. Unlike traditional clustering algorithms constrained by prede…
QiMeng: Fully Automated Hardware and Software Design for Processor Chip
Rui Zhang, Yuanbo Wen, Shuyao Cheng +17
Processor chip design technology serves as a key frontier driving breakthroughs in computer science and related fields. With the rapid advancement of information technology, conven…
Variable-frame CNNLSTM for Breast Nodule Classification using Ultrasound Videos
Xiangxiang Cui, Zhongyu Li, Xiayue Fan +5
The intersection of medical imaging and artificial intelligence has become an important research direction in intelligent medical treatment, particularly in the analysis of medical…
Instance-adaptive Zero-shot Chain-of-Thought Prompting
Xiaosong Yuan, Chen Shen, Shaotian Yan +6
Zero-shot Chain-of-Thought (CoT) prompting emerges as a simple and effective strategy for enhancing the performance of large language models (LLMs) in real-world reasoning tasks. N…
Understanding Auditory Evoked Brain Signal via Physics-informed Embedding Network with Multi-Task Transformer
Wanli Ma, Xuegang Tang, Jin Gu +2
In the fields of brain-computer interaction and cognitive neuroscience, effective decoding of auditory signals from task-based functional magnetic resonance imaging (fMRI) is key t…
Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
Ying Wang, Tim G. J. Rudner, Andrew Gordon Wilson
Vision-language pretrained models have seen remarkable success, but their application to safety-critical settings is limited by their lack of interpretability. To improve the inter…