10 citations · 38 across the 12 of their papers we have counts for
12 papers
SpliceMix: A Cross-scale and Semantic Blending Augmentation Strategy for Multi-label Image Classification
Lei Wang, Yibing Zhan, Leilei Ma +3
Recently, Mix-style data augmentation methods (e.g., Mixup and CutMix) have shown promising performance in various visual tasks. However, these methods are primarily designed for s…
Careful Selection and Thoughtful Discarding: Graph Explicit Pooling Utilizing Discarded Nodes
Chuang Liu, Wenhang Yu, Kuang Gao +5
Graph pooling has been increasingly recognized as crucial for Graph Neural Networks (GNNs) to facilitate hierarchical graph representation learning. Existing graph pooling methods…
Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation
Changtong Zan, Liang Ding, Li Shen +4
Zero-shot translation (ZST), which is generally based on a multilingual neural machine translation model, aims to translate between unseen language pairs in training data. The comm…
Chasing Consistency in Text-to-3D Generation from a Single Image
Yichen Ouyang, Wenhao Chai, Jiayi Ye +3
Text-to-3D generation from a single-view image is a popular but challenging task in 3D vision. Although numerous methods have been proposed, existing works still suffer from the in…
Divide, Conquer, and Combine: Mixture of Semantic-Independent Experts for Zero-Shot Dialogue State Tracking
Qingyue Wang, Liang Ding, Yanan Cao +5
Zero-shot transfer learning for Dialogue State Tracking (DST) helps to handle a variety of task-oriented dialogue domains without the cost of collecting in-domain data. Existing wo…
Noise-Resistant Multimodal Transformer for Emotion Recognition
Yuanyuan Liu, Haoyu Zhang, Yibing Zhan +4
Multimodal emotion recognition identifies human emotions from various data modalities like video, text, and audio. However, we found that this task can be easily affected by noisy…