5 citations · 10 across the 10 of their papers we have counts for
6 papers · 1 filter
Sharing, Teaching and Aligning: Knowledgeable Transfer Learning for Cross-Lingual Machine Reading Comprehension
Tingfeng Cao, Chengyu Wang, Chuanqi Tan +2
In cross-lingual language understanding, machine translation is often utilized to enhance the transferability of models across languages, either by translating the training data fr…
PAI-Diffusion: Constructing and Serving a Family of Open Chinese Diffusion Models for Text-to-image Synthesis on the Cloud
Chengyu Wang, Zhongjie Duan, Bingyan Liu +4
Text-to-image synthesis for the Chinese language poses unique challenges due to its large vocabulary size, and intricate character relationships. While existing diffusion models ha…
TransPrompt v2: A Transferable Prompting Framework for Cross-task Text Classification
Jianing Wang, Chengyu Wang, Cen Chen +3
Text classification is one of the most imperative tasks in natural language processing (NLP). Recent advances with pre-trained language models (PLMs) have shown remarkable success…
Towards Adaptive Prefix Tuning for Parameter-Efficient Language Model Fine-tuning
Zhen-Ru Zhang, Chuanqi Tan, Haiyang Xu +3
Fine-tuning large pre-trained language models on various downstream tasks with whole parameters is prohibitively expensive. Hence, Parameter-efficient fine-tuning has attracted att…
Uncertainty-aware Self-training for Low-resource Neural Sequence Labeling
Jianing Wang, Chengyu Wang, Jun Huang +2
Neural sequence labeling (NSL) aims at assigning labels for input language tokens, which covers a broad range of applications, such as named entity recognition (NER) and slot filli…
From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression
Runxin Xu, Fuli Luo, Chengyu Wang +4
Pre-trained Language Models (PLMs) have achieved great success in various Natural Language Processing (NLP) tasks under the pre-training and fine-tuning paradigm. With large quanti…