8 papers
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…
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…
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-…
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…
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…
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…