In ChronoCulture, naming the survey year in the prompt gives near-zero average benefit, but naming the older year increasingly helps as the real cultural shift between the two years grows larger

LLM-evaluationcultural-awarenessbenchmarkworld-values-surveytemporal-reasoningarxivprompting

ChronoCulture compares each model's prediction when told the exact survey year against the same model's prediction when given no year at all, measuring whether naming the year reduces prediction error relative to that year's real distribution. Across models, naming a year helped 20–44% of items but hurt a similar share, so the average effect across all pairs was close to zero or slightly negative — a plausible-sounding intervention (tell the model what decade to simulate) that mostly washes out.

The effect is not flat across all conditions, though. As the real shift between the older and newer year grew larger, naming the older year started to show a consistent benefit: positive in most models for strong shifts, and positive in all six tested models for very strong shifts. Naming the newer year showed little benefit at any shift level. So the one place the intervention reliably earns its keep is anchoring a model to the earlier of two very different moments — a case where, per claim-chronoculture-llm-predictions-track-direction-better-than-magnitude-of-cultural-shift, the model's default (undifferentiated, roughly-averaged) answer is furthest from correct for either year.