Conversational interfaces powered by Large Language Models (LLMs) have recently become a popular way to obtain feedback during document editing. However, standard chat-based conversational interfaces do not support transparency and verifiability of the editing changes that they suggest. To give the author more agency when editing with an LLM, we present InkSync, an editing interface that suggests executable edits directly within the document being edited. Because LLMs are known to introduce factual errors, Inksync also supports a 3-stage approach to mitigate this risk: Warn authors when a suggested edit introduces new information, help authors Verify the new information's accuracy through external search, and allow an auditor to perform an a-posteriori verification by Auditing the document via a trace of all auto-generated content. Two usability studies confirm the effectiveness of InkSync's components when compared to standard LLM-based chat interfaces, leading to more accurate, more efficient editing, and improved user experience.

InkSync是一种编辑界面，通过在正在编辑的文档中直接建议可执行的编辑，提供给作者更多的编辑自主权。它通过警告作者、帮助作者验证新信息的准确性和允许审计人员通过跟踪所有自动生成的内容来对文档进行事后验证，实现对LLM引入的事实错误的缓解。两个可用性研究证实了InkSync的组件与标准LLM为基础的聊天界面相比的有效性，从而实现了更准确、更高效的编辑和改善用户体验。

超越聊天机器人：具备可执行和可验证功能的文本编辑技术