The use of Large Language Models (LLMs) for writing has sparked controversy both among readers and writers. On one hand, writers are concerned that LLMs will deprive them of agency and ownership, and readers are concerned about spending their time on text generated by soulless machines. On the other hand, writers who genuinely want to use LLMs must conform to publisher policies for AI-assisted writing, and readers need assurance that a text has been verified by a human. We argue that a system that captures the provenance of interaction with an LLM can help writers retain their agency, conform to policies, and communicate their use of AI to publishers and readers transparently. Thus we propose HaLLMark, a tool for facilitating and visualizing writers' interaction with LLMs. We evaluated HaLLMark with 13 creative writers, and found that it helped them retain a sense of control and ownership of the written text.

翻译：大型语言模型（LLMs）在写作中的应用引发了读者和作者双方的争议。一方面，作者担忧LLMs会剥夺其能动性与所有权，读者则担心花费时间阅读无情感机器生成的内容；另一方面，真正希望使用LLMs的作者必须遵守出版商关于AI辅助写作的政策，而读者也需要确保文本经过人工审核。我们认为，能够捕获与LLM交互溯源的系统有助于作者保持能动性、遵循政策，并向出版商和读者透明地传达其AI使用情况。因此，我们提出HaLLMark——一个用于促进和可视化作者与LLMs交互的工具。通过13位创意作家的评估，我们发现该工具帮助他们保持了写作过程中的控制感与文本所有权。