Conversation Metric

Conversation metrics aim to quantitatively assess the quality and effectiveness of dialogues, particularly those involving large language models (LLMs). Current research focuses on developing nuanced metrics that capture aspects beyond simple textual similarity, incorporating multimodal signals, semantic coherence, and task-specific performance in domains like mental health and education. These advancements are crucial for improving LLM-based conversational agents, enabling more reliable evaluation of their capabilities, and facilitating the development of more human-like and helpful conversational AI systems.