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：大语言模型（LLM）在写作中的应用引发了读者与作者双方的争议。一方面，作者担心LLM会剥夺其写作自主权与作品所有权，读者则忧虑耗费时间阅读由缺乏灵魂的机器生成的文本。另一方面，真正希望使用LLM的作者必须遵循出版商关于AI辅助写作的政策，而读者也需要确信文本经过人工审核。我们认为，一种能够捕获与LLM交互完整溯源信息的系统，可帮助作者保持自主权、遵守政策，并向出版商与读者透明传达AI使用情况。由此我们提出HaLLMark——一款支持作者与LLM交互可视化与溯源的工具。我们邀请13位创意写作者对HaLLMark进行评估，发现该工具有效帮助他们维持对书写文本的控制感与归属感。