32 citations · 86 across the 19 of their papers we have counts for
7 papers · 1 filter
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…
Meta-Learning Siamese Network for Few-Shot Text Classification
Chengcheng Han, Yuhe Wang, Yingnan Fu +4
Few-shot learning has been used to tackle the problem of label scarcity in text classification, of which meta-learning based methods have shown to be effective, such as the prototy…
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…
Understanding Long Programming Languages with Structure-Aware Sparse Attention
Tingting Liu, Chengyu Wang, Cen Chen +2
Programming-based Pre-trained Language Models (PPLMs) such as CodeBERT have achieved great success in many downstream code-related tasks. Since the memory and computational complex…
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification
ChengCheng Han, Zeqiu Fan, Dongxiang Zhang +3
Meta-learning has emerged as a trending technique to tackle few-shot text classification and achieved state-of-the-art performance. However, existing solutions heavily rely on the…
Learning Relation Prototype from Unlabeled Texts for Long-tail Relation Extraction
Yixin Cao, Jun Kuang, Ming Gao +3
Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG) by extracting entity relations from texts.However, it usually suffers from the long-tail issue. The traini…