CoEdit Leverages a Large Language Model Fine-Tuned on Diverse Text Editing Instructions to Produce High-Quality and Natural Edits.
Paper Title: CoEdIT: Text Editing by Task-Specific Instruction Tuning
Journal Name: arXiv (submitted to NAACL demo track)
Authors’ Names: Vipul Raheja, Dhruv Kumar, Ryan Koo, Dongyeop Kang
What problem this paper solves?
Writing is a complex and challenging task that requires various skills and knowledge, such as grammar, vocabulary, style, and content. However, many writers struggle with writing effectively and efficiently, and often need assistance or feedback to improve their writing.
Existing writing assistance tools, such as grammar checkers, spell checkers, or paraphrasing tools, are limited in their scope and functionality, as they are tailored to specific tasks, formats, or domains, and do not allow users to specify their own editing preferences or goals. Moreover, these tools often produce unnatural or inappropriate edits, as they do not consider the context, meaning, or tone of the original text.
What approach this paper utilizes:?
The paper presents CoEdIT, a novel system for writing assistance that takes instructions from the user specifying the attributes of the desired text, such as “Make the sentence simpler” or “Write it in a more neutral style”, and outputs the edited text. CoEdIT leverages a large language model (LLM) fine-tuned on a diverse collection of task-specific instructions for text editing, collected from various sources, such as online writing guides, blogs, and forums. CoEdIT’s LLM can handle various text editing tasks, such as grammar correction, style transfer, text summarization, text generation, and text rewriting, as well as generalize to unseen or composite instructions, such as “Make the sentence shorter and more formal” or “Rewrite the sentence using a metaphor”.
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What are the impacts of this approach on AI research?
CoEdIT is a state-of-the-art system for writing assistance that demonstrates the power and flexibility of instruction-tuned LLMs for text editing. CoEdIT achieves high performance on various text editing benchmarks, and outperforms other LLMs trained on instructions, while being much smaller in size. CoEdIT also exhibits abilities to generalize to unseen or composite instructions, and to produce high-quality and natural edits, as preferred by human writers.
CoEdIT is a community-driven platform, where users can create, share, and explore different text editing instructions, and provide feedback and ratings to the system. CoEdIT aims to facilitate the development and improvement of writing skills, as well as to promote the research and practice of instruction-based text editing.
Summary of the research?
CoEdIT is a new system for writing assistance that takes instructions from the user specifying the attributes of the desired text, and outputs the edited text. CoEdIT leverages a large language model fine-tuned on a diverse collection of task-specific instructions for text editing, collected from various sources. CoEdIT can handle various text editing tasks, as well as generalize to unseen or composite instructions. CoEdIT produces high-quality and natural edits, as preferred by human writers. CoEdIT is a community-driven platform, where users can create, share, and explore different text editing instructions, and provide feedback and ratings to the system.
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