6 citations · 19 across the 13 of their papers we have counts for
13 papers
VowelPrompt: Hearing Speech Emotions from Text via Vowel-level Prosodic Augmentation
Yancheng Wang, Osama Hanna, Ruiming Xie +11
Emotion recognition in speech presents a complex multimodal challenge, requiring comprehension of both linguistic content and vocal expressivity, particularly prosodic features suc…
Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
Chengshuai Zhao, Zhen Tan, Pingchuan Ma +5
Chain-of-Thought (CoT) prompting has been shown to be effective in eliciting structured reasoning (i.e., CoT reasoning) from large language models (LLMs). Regardless of its popular…
Compact Vision Transformer by Reduction of Kernel Complexity
Yancheng Wang, Yingzhen Yang
Self-attention and transformer architectures have become foundational components in modern deep learning. Recent efforts have integrated transformer blocks into compact neural arch…
Learning Informative Attention Weights for Person Re-Identification
Yancheng Wang, Nebojsa Jojic, Yingzhen Yang
Attention mechanisms have been widely used in deep learning, and recent efforts have been devoted to incorporating attention modules into deep neural networks (DNNs) for person Re-…
Diffusion on Graph: Augmentation of Graph Structure for Node Classification
Yancheng Wang, Changyu Liu, Yingzhen Yang
Graph diffusion models have recently been proposed to synthesize entire graphs, such as molecule graphs. Although existing methods have shown great performance in generating entire…
IDNet: A Novel Dataset for Identity Document Analysis and Fraud Detection
Hong Guan, Yancheng Wang, Lulu Xie +8
Effective fraud detection and analysis of government-issued identity documents, such as passports, driver's licenses, and identity cards, are essential in thwarting identity theft…
Efficient Visual Transformer by Learnable Token Merging
Yancheng Wang, Yingzhen Yang
Self-attention and transformers have been widely used in deep learning. Recent efforts have been devoted to incorporating transformer blocks into different neural architectures, in…
Learning Low-Rank Feature for Thorax Disease Classification
Rajeev Goel, Utkarsh Nath, Yancheng Wang +3
Deep neural networks, including Convolutional Neural Networks (CNNs) and Visual Transformers (ViT), have achieved stunning success in medical image domain. We study thorax disease…
Graph Contrastive Learning with Low-Rank Regularization and Low-Rank Attention for Noisy Node Classification
Yancheng Wang, Yingzhen Yang
Graph Neural Networks (GNNs) have achieved remarkable success in learning node representations and have shown strong performance in tasks such as node classification. However, rece…
Declarative Privacy-Preserving Inference Queries
Hong Guan, Ansh Tiwari, Summer Gautier +8
Detecting inference queries running over personal attributes and protecting such queries from leaking individual information requires tremendous effort from practitioners. To tackl…
RecMind: Large Language Model Powered Agent For Recommendation
Yancheng Wang, Ziyan Jiang, Zheng Chen +7
While the recommendation system (RS) has advanced significantly through deep learning, current RS approaches usually train and fine-tune models on task-specific datasets, limiting…
RNAS-CL: Robust Neural Architecture Search by Cross-Layer Knowledge Distillation
Utkarsh Nath, Yancheng Wang, Yingzhen Yang
Deep Neural Networks are vulnerable to adversarial attacks. Neural Architecture Search (NAS), one of the driving tools of deep neural networks, demonstrates superior performance in…
Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning
Kaize Ding, Yancheng Wang, Yingzhen Yang +1
Graph Contrastive Learning (GCL) has recently drawn much research interest for learning generalizable node representations in a self-supervised manner. In general, the contrastive…