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We consider the problem of automatically generating longer stories of overtwo thousand words. Compared to prior work on shorter stories, long-range plotcoherence and relevance are more central challenges here. We propose theRecursive Reprompting and Revision framework (Re3) to address these challengesby (a) prompting a general-purpose language model to construct a structuredoverarching plan, and (b) generating story passages by repeatedly injectingcontextual information from both the plan and current story state into alanguage model prompt. We then revise by (c) reranking different continuationsfor plot coherence and premise relevance, and finally (d) editing the bestcontinuation for factual consistency. Compared to similar-length storiesgenerated directly from the same base model, human evaluators judgedsubstantially more of Re3's stories as having a coherent overarching plot (by14% absolute increase), and relevant to the given initial premise (by 20%).

Re3: Generating Longer Stories With Recursive Reprompting and Revision