Wordcraft: Story Writing With Large Language Models

Citations Over TimeTop 1% of 2022 papers

Abstract

The latest generation of large neural language models such as GPT-3 have achieved new levels of performance on benchmarks for language understanding and generation. These models have even demonstrated an ability to perform arbitrary tasks without explicit training. In this work, we sought to learn how people might use such models in the process of creative writing. We built Wordcraft, a text editor in which users collaborate with a generative language model to write a story. We evaluated Wordcraft with a user study in which participants wrote short stories with and without the tool. Our results show that large language models enable novel co-writing experiences. For example, the language model is able to engage in open-ended conversation about the story, respond to writers’ custom requests expressed in natural language (such as ”rewrite this text to be more Dickensian”), and generate suggestions that serve to unblock writers in the creative process. Based on these results, we discuss design implications for future human-AI co-writing systems.

Related Papers

• → Probabilistically Masked Language Model Capable of Autoregressive Generation in Arbitrary Word Order(2020)28 cited
• → Evaluation in the context of natural language generation(1998)67 cited
• Context-aware Natural Language Generation for Spoken Dialogue Systems.(2016)
• Evaluation in Natural Language Generation: Lessons from Referring Expression Generation(2007)
• Affective Natural Language Generation(1999)