27 citations · 140 across the 12 of their papers we have counts for
16 papers
LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models
Peng Xu, Wenqi Shao, Kaipeng Zhang +7
Large Vision-Language Models (LVLMs) have recently played a dominant role in multimodal vision-language learning. Despite the great success, it lacks a holistic evaluation of their…
How to Understand Masked Autoencoders
Shuhao Cao, Peng Xu, David A. Clifton
"Masked Autoencoders (MAE) Are Scalable Vision Learners" revolutionizes the self-supervised learning method in that it not only achieves the state-of-the-art for image pre-training…
Automatic Speech Recognition Datasets in Cantonese: A Survey and New Dataset
Tiezheng Yu, Rita Frieske, Peng Xu +9
Automatic speech recognition (ASR) on low resource languages improves the access of linguistic minorities to technological advantages provided by artificial intelligence (AI). In t…
Contrastive Document Representation Learning with Graph Attention Networks
Peng Xu, Xinchi Chen, Xiaofei Ma +2
Recent progress in pretrained Transformer-based language models has shown great success in learning contextual representation of text. However, due to the quadratic self-attention…
Attention-guided Generative Models for Extractive Question Answering
Peng Xu, Davis Liang, Zhiheng Huang +1
We propose a novel method for applying Transformer models to extractive question answering (QA) tasks. Recently, pretrained generative sequence-to-sequence (seq2seq) models have ac…
Multiplicative Position-aware Transformer Models for Language Understanding
Zhiheng Huang, Davis Liang, Peng Xu +1
Transformer models, which leverage architectural improvements like self-attention, perform remarkably well on Natural Language Processing (NLP) tasks. The self-attention mechanism…