Chinese short text classification approaches based on lexicon information and pretrained
language models have yielded state-of-the-art results. However, they simply use the …

Text classification (TC) is an important basic task in the field of Natural Language
Processing (NLP), and multi-label text classification (MLTC) is an important branch of TC …

Semantic matching plays a critical role in many downstream tasks of natural language
processing. Existing semantic matching methods, which focus on learning sentence …

Modern Chinese characters evolved from 3,000 years ago. Up to now, tens of thousands of
glyphs of ancient characters have been discovered, which must be deciphered by experts to …

Word sense disambiguation is a crucial task to test whether a model can perform deep
understanding. Nowadays, the rise of pre-trained language models facilitates substantial …

Text classification is a fundamental and classical problem in natural language processing.
Existing methods in this area attach more attention to structure modeling of texts, while …

Chinese characters are generally correlated with their semantic meanings, and the structure
of radicals, in particular, can be a clear indication of how characters are related to each …

In the task of matching Chinese sentences, the key semantics within sentences and the
deep interaction between them significantly affect the matching performance. However …

Reading psychology believes text comprehension to involve a complex psychological
construction process, with the reader mind being a dynamic associative system that stores …

Research has verified that associative learning will improve learning efficiency during the
process of recognizing Chinese characters. Therefore, some scholars believe that the …