Paraphrase Generation

Paraphrase generation, the task of rewriting text while preserving meaning, is a core area of natural language processing research focused on improving both the quality and diversity of generated text. Current research emphasizes leveraging large language models (LLMs) and diffusion models, often incorporating techniques like knowledge distillation, in-context learning, and syntactic control to enhance generation capabilities and address challenges such as hallucination and maintaining semantic consistency. This field is crucial for applications ranging from improving the accessibility of complex texts to mitigating the spread of harmful or misleading AI-generated content, and its advancements are driving progress in various NLP tasks.