In this competitive world, the supervision and monitoring of human resources are primary
and necessary tasks to drive context-aware applications. Advancement in sensor and …

Traditional methods for sentiment analysis, when applied in a monolingual context, often
yield less than optimal results in multilingual settings. This underscores the need for a more …

The rapid development of aspect-based sentiment analysis (ABSA) within recent decades
shows great potential for real-world society. The current ABSA works, however, are mostly …

Large pre-trained language models (LMs) have demonstrated the ability to obtain good
performance on downstream tasks with limited examples in cross-lingual settings. However …

In this paper, we address the task of zero-shot cross-lingual news sentiment classification.
Given the annotated dataset of positive, neutral, and negative news in Slovene, the aim is to …

Existing research on cross-lingual retrieval cannot take good advantage of large-scale
pretrained language models such as multilingual BERT and XLM. We hypothesize that the …

Due to the insufficient sentiment corpus in many languages, recent studies have proposed
cross-lingual sentiment analysis to adapt sentiment analysis models from rich-resource …

Recent pretrained vision-language models have achieved impressive performance on cross-
modal retrieval tasks in English. Their success, however, heavily depends on the availability …

Cross-lingual text classification aims at training a classifier on the source language and
transferring the knowledge to target languages, which is very useful for low-resource …

Most of research on the identification of offensive speech on social media platforms exist in
English and other rich languages. A series of recently proposed methods for detecting low …