Large language models represent a significant advancement in the field of AI. The
underlying technology is key to further innovations and, despite critical views and even bans …

Large language models (LLMs) have been recently leveraged as training data generators
for various natural language processing (NLP) tasks. While previous research has explored …

Heterogeneous tabular data are the most commonly used form of data and are essential for
numerous critical and computationally demanding applications. On homogeneous datasets …

We study the application of large language models to zero-shot and few-shot classification
of tabular data. We prompt the large language model with a serialization of the tabular data …

GPT (Generative Pre-trained Transformer) represents advanced language models that have
significantly reshaped the academic writing landscape. These sophisticated language …

Machine unlearning, the study of efficiently removing the impact of specific training points on
the trained model, has garnered increased attention of late, driven by the need to comply …

Traditional recommender systems leverage users' item preference history to recommend
novel content that users may like. However, modern dialog interfaces that allow users to …

Harnessing Large Language Models (LLMs) for recommendation is rapidly emerging, which
relies on two fundamental steps to bridge the recommendation item space and the language …

With the rapid development of online services, recommender systems (RS) have become
increasingly indispensable for mitigating information overload. Despite remarkable …

Personalized content-based recommender systems have become indispensable tools for
users to navigate through the vast amount of content available on platforms like daily news …