HOW CONVERSATIONAL SYSTEMS ARE BUILT USING LANGUAGE MODELS

Аннотация

Conversational systems, also known as chatbots or virtual assistants, have evolved significantly with the advancement of large language models (LLMs). These systems rely on natural language processing (NLP), deep learning, and reinforcement learning to generate human-like interactions. This paper explores the fundamental architecture of conversational systems, including data preprocessing, model training, response generation, and evaluation techniques. Special emphasis is given to state-of-the-art language models such as GPT, BERT, and T5, which have revolutionized conversational AI. The study also discusses the challenges associated with bias, interpretability, and ethical considerations in building robust and responsible conversational agents.