This survey paper proposes a clearer view of natural language reasoning in the field of Natural Language Processing (NLP), both conceptually and practically. Conceptually, we provide a distinct definition for natural language reasoning in NLP, based on both philosophy and NLP scenarios, discuss what types of tasks require reasoning, and introduce a taxonomy of reasoning. Practically, we conduct a comprehensive literature review on natural language reasoning in NLP, mainly covering classical logical reasoning, natural language inference, multi-hop question answering, and commonsense reasoning. The paper also identifies and views backward reasoning, a powerful paradigm for multi-step reasoning, and introduces defeasible reasoning as one of the most important future directions in natural language reasoning research. We focus on single-modality unstructured natural language text, excluding neuro-symbolic techniques and mathematical reasoning.

翻译：本综述论文旨在从概念和实践两个维度，为自然语言处理（NLP）领域内的自然语言推理提供更清晰的视角。在概念层面，我们基于哲学与NLP场景，为NLP中的自然语言推理给出了明确界定，探讨了哪些类型的任务需要推理，并引入了推理的分类体系。在实践层面，我们对NLP中的自然语言推理进行了全面的文献回顾，主要涵盖经典逻辑推理、自然语言推理、多跳问答以及常识推理。本文还识别并审视了反向推理这一多步推理的强大范式，并将可废止推理引入作为自然语言推理研究中最重要的未来方向之一。我们聚焦于单模态非结构化自然语言文本，不包括神经符号技术与数学推理。