The complex nature of logographic writing systems, characterized by their visually intricate
characters and context-dependent meanings, presents unique challenges for computational …

Vector quantization, renowned for its unparalleled feature compression capabilities, has
been a prominent topic in signal processing and machine learning research for several …

The potential use of large language models (LLMs) in healthcare robotics can help address
the significant demand put on healthcare systems around the world with respect to an aging …

Personalization of Large Language Models (LLMs) has recently become increasingly
important with a wide range of applications. Despite the importance and recent progress …

Recommender systems are essential for providing personalized content across various
platforms. However, traditional systems often struggle with limited information, known as the …

Utilizing user profiles to personalize Large Language Models (LLMs) has been shown to
enhance the performance on a wide range of tasks. However, the precise role of user …

Sequential recommendation systems aim to provide personalized recommendations for
users based on their interaction history. To achieve this, they often incorporate auxiliary …

Real-world recommendation systems commonly offer diverse content scenarios for users to
interact with. Considering the enormous number of users in industrial platforms, it is …

Sequential recommendation (SR) systems have evolved significantly over the past decade,
transitioning from traditional collaborative filtering to deep learning approaches and, more …

Client-Service Representatives (CSRs) are vital to organizations. Frequent interactions with
disgruntled clients, however, disrupt their mental well-being. To help CSRs regulate their …