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If I Could Turn Back Time: Temporal Reframing as a Historical Reasoning Task for LLMs

Year: 2025

Type: preprint

Abstract: In this study, we experiment with the ability of LLMs to do temporal reasoning. Using a Norwegian book from 1940 containing trivia questions, we prompt the LLMs to answer the questions as if it were 1940. We also pose the questions in both English and Norwegian. Correct answers are often presented as sentences, and grading is done by means of LLM-as-judge, with sampled checks by a native speaker. Prompting in English consistently gave better results than in Norwegian, an unexpected result. In contrast, using larger LLMs improved results. We tested the DeepSeek-R1, Gemma3, Qwen3, and Llama3.1 model families, and also the largest available LLM especially crafted for Norwegian.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2511.04432

Authors: Bungum, Lars, Huang, Charles Yijia, Kashar, Abeer

Institutions: Norwegian University of Science and Technology, University of Waterloo

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4416025998

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