Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text 事件

Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text arXiv:2605.29076v1 Announce Type: new Abstract: LLMs have advanced text classification, yet existing paradigms face a trade-off: supervised (label only) fine-tuning is scalable but offers limited reasoning on complex text and lacks broader model transparency, while discrete prompt optimization offers human-readable instructions but struggles with performance and scalability. We in