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Natural Language Reasoning, A Survey

2023-03-26 · Fei Yu, Hongbo Zhang, Prayag Tiwari, Benyou Wang

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.

📄 PDF Abstract BibTeX arXiv:2303.14725

Code (1)

freedomintelligence/reasoningnlp 공식 구현 pytorch

Tasks

Logical ReasoningMathematical ReasoningMulti-hop Question AnsweringNatural Language InferencePhilosophyQuestion AnsweringSurvey

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