Text Generator

Text generation research focuses on creating systems that produce coherent and relevant text, addressing challenges like factual accuracy and controllability. Current efforts involve developing models that leverage planning mechanisms to improve text structure and grounding in evidence, as well as employing techniques like prompt engineering and ensemble methods to optimize model performance and address limitations in single-model approaches. These advancements are significant for applications ranging from question answering and encyclopedic content creation to solving complex problems expressed in natural language, impacting fields like information retrieval and natural language processing.