Chinese Natural

Research on Chinese natural language processing (NLP) focuses on developing and evaluating models capable of understanding and generating human-like Chinese text across diverse conversational contexts. Current efforts concentrate on creating robust benchmarks for evaluating dialogue agents, including those handling clarification requests, role-playing, and topic shifts, often employing large language models (LLMs) and incorporating multi-modal and multi-granularity approaches to better capture the nuances of language. These advancements are crucial for improving the performance of conversational AI systems, particularly in applications like chatbots and virtual assistants, and for furthering our understanding of human-computer interaction in Chinese. The development of high-quality, annotated datasets in various domains is a key driver of progress in this field.