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Scaling Point-in-Time Language Models: Enabling Economic Evaluation of Embeddings
Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromises the validity of backtests and causal inference in finance and the social sciences. Point-in-time language models--trained exclusively on text avail
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