How Do Large Language Models Think of Time?
How Do Large Language Models Think of Time? Large language models can reason about chronology, dates, durations, and future possibilities by identifying relationships among events. What they do not inherently possess is a continuously updating sense of the present comparable to the way humans experience time passing. This distinction helps explain how an AI system can reconstruct events from centuries ago while still requiring an external reference to establish what “today” means. Temporal knowledge and temporal experience are not necessarily the same capability. Text Has an Order, but Events Have Another Large language models process sequences of text. Words and tokens appear in particular positions, and Transformer-based models use positional information to help represent those relationships. That sequence should not be confused with the chronology described by the text. A biography might begin with someone's death and then move backward to childhood. A novel can jump decades bet...