Pre-trained Language Models (PLMs) which are trained on large text corpus via self-
supervised learning method, have yielded promising performance on various tasks in …

Abstract Aspect-based Sentiment Analysis (ABSA) is a crucial natural language
understanding (NLU) research field which aims to accurately recognize reviewers' opinions …

Cross-lingual named entity recognition (CrossNER) faces challenges stemming from
uneven performance due to the scarcity of multilingual corpora, especially for non-English …

Commonsense question answering is important for making decisions about everyday
matters. Although existing commonsense question answering works based on fully fine …

The objective of few-shot named entity recognition is to identify named entities with limited
labeled instances. Previous works have primarily focused on optimizing the traditional token …

Knowledge-enhanced Pre-trained Language Model (PLM) has recently received significant
attention, which aims to incorporate factual knowledge into PLMs. However, most existing …

Existing knowledge-enhanced methods have achieved remarkable results in certain QA
tasks via obtaining diverse knowledge from different knowledge bases. However, limited by …

Definitions are a fundamental building block in lexicography, linguistics and computational
semantics. In NLP, they have been used for retrofitting word embeddings or augmenting …

For both humans and machines to acquire vocabulary, it is effective to learn words from
context while using dictionaries as an auxiliary tool. It has been shown in previous linguistic …

We introduce CDBert, a new learning paradigm that enhances the semantics understanding
ability of the Chinese PLMs with dictionary knowledge and structure of Chinese characters …