Before revision: AI has long pursued the goal of having systems reason over *explicitly provided* knowledge, but building suitable representations has proved challenging. Here we explore whether transformers can similarly learn to reason (or emulate reasoning) , but using rules expressed in language , thus bypassing a formal representation.
After revision: AI has long pursued the goal of providing a system with explicit, general knowledge and having the system reason over that knowledge. However, expressing the knowledge in a formal (logical or probabilistic) representation has been a major obstacle to this research. This paper investigates a modern approach to this problem where the facts and rules are provided as natural language sentences , thus bypassing a formal representation.