arXiv cs.CL
· Papers
Scaling Point-in-Time Language Models
arXiv:2607.11889v2 Announce Type: replace Abstract: 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--t