Dialogue System

Dialogue systems aim to create natural and engaging conversations between humans and machines, primarily focusing on improving the accuracy, fluency, and contextual understanding of these interactions. Current research emphasizes enhancing memory capabilities, mitigating biases like hallucination and over-association, and improving robustness to noisy input such as from automatic speech recognition. This involves leveraging large language models (LLMs) and exploring novel architectures like mixture-of-experts and neuro-symbolic approaches, alongside the development of new evaluation benchmarks and datasets to better assess system performance. The advancements in this field have significant implications for various applications, including customer service, mental health support, and personalized education.