TimeCapsuleLLM: LLM trained only on data from 1800-1875

Re:TimeCapsuleLLM: LLM trained only on data from 1800-1875 by bravura on Monday January 12, 2026 @01:03PM (#46591981)

A rigorous approach to predicting the future of text was proposed by Li et al 2024, "Evaluating Large Language Models for Generalization and Robustness via Data Compression" (https://ar5iv.labs.arxiv.org/html//2402.00861) and I think that work should get more recognition.

They measure compression (perplexity) on future Wikipedia, news articles, code, arXiv papers, and multi-modal data. Data compression is intimately connected with robustness and generalization.

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Re:TimeCapsuleLLM: LLM trained only on data from 1800-1875 by Otterly99 on Tuesday January 13, 2026 @05:08AM (#46599111)

Thanks for the paper, I just read it and loved the approach. I hope the concept of using data compression as a benchmark will take off. In a sense it is kind of similar to the maxim "If you cannot explain something in simple terms, you do not understand it fully".

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