The development of AI applications is a multidisciplinary effort, involving multiple roles
collaborating with the AI developers, an umbrella term we use to include data scientists and …

Automated machine learning (AutoML) can make data scientists more productive. But if
machine learning is totally automated, that leaves no room for data scientists to apply their …

With most technical fields, there exists a delay between fundamental academic research and
practical industrial uptake. Whilst some sciences have robust and well-established …

This paper addresses the task of predicting the occurrence of corporate events based on
earning call transcripts. We introduce a novel dataset of earning call transcripts specifically …

The rise of automated text processing systems has led to the development of tools designed
for a wide variety of application domains. These technologies are often developed to support …

Accurate prediction of the stock price volatility, the rate at which the price of a stock
increases or decreases over a particular period, is an important problem in finance …

While automated machine learning (AutoML) can save human labor in finding well-
performing pipelines, it often suffers from two problems: overfitting and using excessive …

Scenario-Technique offers the possibility to make future-robust decisions and act with
foresight to be prepared for future challenges. Scenario-Technique is a method that …

This paper offers a thorough assessment of large language models (LLMs) in the context of
corporate event prediction. To achieve this, we formally establish the task of corporate event …