8 citations · 8 across the 5 of their papers we have counts for
8 papers
Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training Model
Kanzhi Cheng, Wenpo Song, Zheng Ma +3
Current captioning approaches tend to generate correct but "generic" descriptions that lack real-world knowledge, e.g., named entities and contextual information. Considering that…
Extrapolating Large Language Models to Non-English by Aligning Languages
Wenhao Zhu, Yunzhe Lv, Qingxiu Dong +6
Existing large language models show disparate capability across different languages, due to the imbalance in the training data. Their performances on English tasks are often strong…
SIFTER: A Task-specific Alignment Strategy for Enhancing Sentence Embeddings
Chao Yu, Wenhao Zhu, Chaoming Liu +2
The paradigm of pre-training followed by fine-tuning on downstream tasks has become the mainstream method in natural language processing tasks. Although pre-trained models have the…
INK: Injecting kNN Knowledge in Nearest Neighbor Machine Translation
Wenhao Zhu, Jingjing Xu, Shujian Huang +2
Neural machine translation has achieved promising results on many translation tasks. However, previous studies have shown that neural models induce a non-smooth representation spac…
On Structural Expressive Power of Graph Transformers
Wenhao Zhu, Tianyu Wen, Guojie Song +2
Graph Transformer has recently received wide attention in the research community with its outstanding performance, yet its structural expressive power has not been well analyzed. I…
Hierarchical Transformer for Scalable Graph Learning
Wenhao Zhu, Tianyu Wen, Guojie Song +2
Graph Transformer is gaining increasing attention in the field of machine learning and has demonstrated state-of-the-art performance on benchmarks for graph representation learning…