Proof Generation

In this paper, we investigate the problem of reasoning over natural language statements. Prior neural based approaches do not explic- itly consider the inter-dependency among an- swers and their proofs. …...

AbstractReasoning over natural language is a challenging problem in NLP. In this work, we focus on proof generation: Given a hypothesis and a set of supporting facts, the model generates …...

AbstractWe present IBR, an Iterative Backward Reasoning model to solve the proof generation tasks on rule-based Question Answering (QA), where models are required to reason over a series of textual …...

AbstractProof generation focuses on deductive reasoning: given a hypothesis and a set of theories, including some supporting facts and logical rules expressed in natural language, the model generates a proof …...