Recent advancements in deep learning (DL) have posed a significant challenge for
automatic speech recognition (ASR). ASR relies on extensive training datasets, including …

This study presents a financial distress prediction model focusing on the linguistic analysis
of risk-related sections of corporate annual reports. Here, we introduce a novel methodology …

Natural language processing for finance has gained significant attention from both
academia and the industry as the continuously increasing amount of financial texts has …

The primary objective of knowledge tracing (KT) is to trace learners' changing knowledge
states and predict their future performance by analyzing their learning trajectories. One of …

Abstract Student Performance Prediction (SPP) has received a lot of attention due to its
educational implications, such as personalized instruction. Among numerous attempts in …

With the recent development of large language models (LLMs), models that focus on certain
domains and languages have been discussed for their necessity. There is also a growing …

With the growing importance of environmental, social, and governance (ESG) information,
ESG scores, which have been rated and published by various institutions, are used for …

Recent advances in large language models (LLMs) have unlocked novel opportunities for
machine learning applications in the financial domain. These models have demonstrated …

In recent years, the type and quantity of news are growing rapidly, and it is not easy for users
to find the news they are interested in the massive amount of news. A news recommendation …

With the development of e-government, multiple local governments in China are developing
Internet-based open policy platforms, and these online platforms need to automatically …