Abstract The Out-of-Domain (OOD) intent classification is a basic and challenging task for
dialogue systems. Previous methods commonly restrict the region (in feature space) of In …

Abstract Multi-Label Text Classification (MLTC) is a fundamental and challenging task in
natural language processing. Previous studies mainly focus on learning text representation …

Transformer-based language models have achieved significant success in various domains.
However, the data-intensive nature of the transformer architecture requires much labeled …

Pre-trained language models have contributed significantly to relation extraction by
demonstrating remarkable few-shot learning abilities. However, prompt tuning methods for …

Abstract Recently, Few-shot Named Entity Recognition has received wide attention with the
growing need for NER models to learn new classes with minimized annotation costs …

Natural language understanding (NLU) models often rely on dataset biases rather than
intended task-relevant features to achieve high performance on specific datasets. As a …

Cross-domain sentiment analysis aims to predict the sentiment of texts in the target domain
using the model trained on the source domain to cope with the scarcity of labeled data …

Wheat (Triticum spp.) has been one of the most important cereal crops, serving as a source
of protein and energy in the human diet. It remains a vital component of global food security …

Modern email clients support predicate-based folder assignment rules that can automatically
organize emails. Unfortunately, users still need to write these rules manually. Prior machine …

The goal of stance detection is to automatically recognize the author's expressed attitude in
text towards a given target. However, social media users often express themselves briefly …