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    <abstract>Large language models compress centuries of discourse into fixed parameters, yet how they organize historical variation and whether this organization shapes generation remain unclear. We introduce the Time Travel Engine (TTE), a framework that compares geometric accounts of era-conditioned residual states and tests their behavioral accessibility under fixed prompts. Across six decoder language models in Chinese and English, broad eras repeatedly form ordered trajectories, although their exact spacing varies across model–language settings. Steering along these trajectories shifts both historical register and access to period-compatible knowledge, while adjacent anchors support local interpolation. Epistemic effects partly survive style removal, linking temporal steering to knowledge access beyond surface register. Across Chinese and English, partially alignable trajectories reveal corresponding chronological relations whose geometric realization remains language-specific. Together, ordered temporal geometry offers a testable account of how static language models organize diachronic variation, linking internal structure to historical register and access to period-compatible knowledge. Code and datasets: https://github.com/LilTiger/Time-Travel-Engine.</abstract>
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%0 Conference Proceedings
%T Time Travel Engine: Ordered Temporal Geometry Enables Era-Level Historical Steering in Large Language Models
%A An, Jingmin
%A Liu, Wei
%A Wang, Qian
%A Fang, Fang
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Findings of the Association for Computational Linguistics: EMNLP 2026
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-462-0
%F an-etal-2026-time
%X Large language models compress centuries of discourse into fixed parameters, yet how they organize historical variation and whether this organization shapes generation remain unclear. We introduce the Time Travel Engine (TTE), a framework that compares geometric accounts of era-conditioned residual states and tests their behavioral accessibility under fixed prompts. Across six decoder language models in Chinese and English, broad eras repeatedly form ordered trajectories, although their exact spacing varies across model–language settings. Steering along these trajectories shifts both historical register and access to period-compatible knowledge, while adjacent anchors support local interpolation. Epistemic effects partly survive style removal, linking temporal steering to knowledge access beyond surface register. Across Chinese and English, partially alignable trajectories reveal corresponding chronological relations whose geometric realization remains language-specific. Together, ordered temporal geometry offers a testable account of how static language models organize diachronic variation, linking internal structure to historical register and access to period-compatible knowledge. Code and datasets: https://github.com/LilTiger/Time-Travel-Engine.
%U https://aclanthology.org/2026.findings-emnlp.417/
%P 8786-8812

Markdown (Informal)

[Time Travel Engine: Ordered Temporal Geometry Enables Era-Level Historical Steering in Large Language Models](https://aclanthology.org/2026.findings-emnlp.417/) (An et al., Findings 2026)

• Time Travel Engine: Ordered Temporal Geometry Enables Era-Level Historical Steering in Large Language Models (An et al., Findings 2026)

ACL

• Jingmin An, Wei Liu, Qian Wang, and Fang Fang. 2026. Time Travel Engine: Ordered Temporal Geometry Enables Era-Level Historical Steering in Large Language Models. In Findings of the Association for Computational Linguistics: EMNLP 2026, pages 8786–8812, Budapest, Hungary. Association for Computational Linguistics.