Outline Conditioned Text Generation

Outline-conditioned text generation focuses on improving the quality and controllability of text generated by large language models (LLMs) by providing them with structured outlines as input. Current research emphasizes developing methods to enhance the consistency between outlines and generated text, address issues like pacing and concreteness in long-form generation, and improve the handling of diverse outline formats, from keyword lists to detailed sentence-level structures. This area is significant because it allows for more precise control over the generated content, leading to improved applications in various fields, including automated writing assistance, story generation, and multilingual dialogue systems.