Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative impact, these new …

We explore how generating a chain of thought---a series of intermediate reasoning steps---
significantly improves the ability of large language models to perform complex reasoning. In …

Complex reasoning aims to draw a correct inference based on complex rules. As a hallmark
of human intelligence, it involves a degree of explicit reading comprehension, interpretation …

This paper presents a novel approach to learning to solve simple arithmetic word problems.
Our system, ARIS, analyzes each of the sentences in the problem statement to identify the …

We present an approach for automatically learning to solve algebra word problems. Our
algorithm reasons across sentence boundaries to construct and solve a system of linear …

Solving mathematical word problems (MWPs) automatically is challenging, primarily due to
the semantic gap between human-readable words and machine-understandable logics …

Little work from the Natural Language Processing community has targeted the role of
quantities in Natural Language Understanding. This paper takes some key steps towards …

We introduce a learning semantic parser, SCISSOR, that maps natural-language sentences
to a detailed, formal, meaningrepresentation language. It first uses an integrated statistical …

This paper presents a new algorithm to automatically solve algebra word problems. Our
algorithm solves a word problem via analyzing a hypothesis space containing all possible …

Numeracy is the ability to understand and work with numbers. It is a necessary skill for
composing and understanding documents in clinical, scientific, and other technical domains …