Dialogue Evaluation

Dialogue evaluation aims to automatically assess the quality of conversations generated by AI systems, striving to align automated scores with human judgments of factors like coherence, fluency, and relevance. Current research heavily utilizes large language models (LLMs), often fine-tuned or prompted for specific evaluation tasks, to create automated metrics and datasets for benchmarking dialogue systems across multiple languages and domains. This field is crucial for advancing the development of more human-like and effective conversational AI, impacting both research methodologies and the practical deployment of chatbots and other dialogue agents in various applications.