#贝叶斯

Unlike implicit in-context opinion shifts, BCA lets social-simulation builders verify a stubbornness setting numerically, matching Friedkin–Johnsen fixed points at R² 0.93–0.99 and recovering prescribed parameters perfectly across four LLMs.

The framework explains why few-shot prompting has mixed effects on RL-tuned models and provides insights for modern reasoning pipelines like DeepSeek-R1 and o1-style models.