String Seed of Thought: Prompting for Distribution-Faithful, Diverse Generation
Researchers introduce String Seed of Thought (SSoT), a prompting technique that improves distribution-faithful and diverse text generation. The method uses string seeds to guide language models toward more varied outputs while maintaining fidelity to training data distributions. Experimental results show SSoT outperforms existing prompting approaches across multiple benchmarks.