Hierarchical text classification is a challenging subtask of multi-label classification due to its
complex label hierarchy. Existing methods encode text and label hierarchy separately and …

Hierarchical text classification (HTC) is an important task with broad applications, and few-
shot HTC has gained increasing interest recently. While in-context learning (ICL) with large …

Multi-Intent spoken language understanding (SLU) can handle complicated utterances
expressing multiple intents, which has attracted increasing attention from researchers …

News media always pursue informing the public at large. It is impossible to overestimate the
significance of understanding the semantics of news coverage. Traditionally, a news text is …

We propose a CNN-BiLSTM-Attention classifier to classify online short messages in Chinese
posted by users on government web portals, so that a message can be directed to one or …

Implicit discourse relation recognition (IDRR) is a challenging but crucial task in discourse
analysis. Most existing methods train multiple models to predict multi-level labels …

The human mind grows in learning new knowledge, which finally organizes and develops a
basic mental pattern called cognitive structure. Hierarchical multi-label text classification …

This paper scrutinizes the act of patent classification as it is performed by specialists, namely
patent examiners, and currently supported by automated systems in patent offices for …

It is often the case that collections of documents are annotated with hierarchically-structured
concepts. However, the benefits of this structure are rarely taken into account by …

Multimodal affective computing (MAC) has garnered increasing attention due to its broad
applications in analyzing human behaviors and intentions, especially in text-dominated …