This new study uses continued pretraining with historical documents on Qwen2.5, along with supervised fine-tuning and reinforcement learning for a more historically accurate CoT-tuned model. Cool methods! arxiv.org/pdf/2504.09488

New preprint from @lauraknelson.bsky.social, @mattwilkens.bsky.social, and myself tests different ways of simulating the past with LLMs. We don't fully answer the title question here—just show that simple strategies based on prompting and fine-tuning are insufficient. +

There are many ways to identify texts that seem ahead of their time. Our CHR 2024 paper asks which measures of textual precocity align best with social evidence about influence and change.