Recent advances in large language models have demonstrated promising capabilities in following simple instructions through instruction tuning. However, real-world tasks often involve complex, multi-step instructions that remain challenging for current NLP systems. Despite growing interest in this area, there lacks a comprehensive survey that systematically analyzes the landscape of complex instruction understanding and processing. Through a systematic review of the literature, we analyze available resources, representation schemes, and downstream tasks related to instructional text. Our study examines 177 papers, identifying trends, challenges, and opportunities in this emerging field. We provide AI/NLP researchers with essential background knowledge and a unified view of various approaches to complex instruction understanding, bridging gaps between different research directions and highlighting future research opportunities.

本研究解决了当前自然语言处理系统在处理复杂多步骤指令时面临的挑战，并提供了一份关于复杂指令理解与处理的系统性综述。通过分析177篇相关文献，我们识别了这一新兴领域的趋势、挑战与机遇，为AI/NLP研究人员提供了必要的背景知识和对各种复杂指令理解方法的统一视角，促进了不同研究方向之间的联系，并指出了未来的研究机会。

关于指令文本的系统性调研：从表示格式到下游自然语言处理任务