Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Answering Elementary Science Questions by Constructing Coherent Scenes using Background Knowledge
Much of what we understand from text is not explicitly stated. Rather, the reader uses his/her knowledge to fill in gaps and create a coherent, mental picture or “scene” depicting what text appears…
Exploring Markov Logic Networks for Question Answering
Elementary-level science exams pose significant knowledge acquisition and reasoning challenges for automatic question answering. We develop a system that reasons with knowledge derived from…
Learning to Solve Arithmetic Word Problems with Verb Categorization
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 relevant…
Modeling Biological Processes for Reading Comprehension
Machine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. In this paper, we focus on a new reading…
Learning Biological Processes with Global Constraints
Biological processes are complex phenomena involving a series of events that are related to one another through various relationships. Systems that can understand and reason over biological…
Semi-Markov Phrase-based Monolingual Alignment
We introduce a novel discriminative model for phrase-based monolingual alignment using a semi-Markov CRF. Our model achieves stateof-the-art alignment accuracy on two phrasebased alignment datasets…