Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
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…
VisKE: Visual Knowledge Extraction and Question Answering by Visual Verification of Relation Phrases
How can we know whether a statement about our world is valid. For example, given a relationship between a pair of entities e.g., 'eat(horse, hay)', how can we know whether this relationship is true…
Higher-order Lexical Semantic Models for Non-factoid Answer Reranking
Lexical semantic models provide robust performance for question answering, but, in general, can only capitalize on direct evidence seen during training. For example, monolingual alignment models…
Learning Knowledge Graphs for Question Answering through Conversational Dialog
We describe how a question-answering system can learn about its domain from conversational dialogs. Our system learns to relate concepts in science questions to propositions in a fact corpus, stores…
Spinning Straw into Gold: Using Free Text to Train Monolingual Alignment Models for Non-factoid Question Answering
Monolingual alignment models have been shown to boost the performance of question answering systems by "bridging the lexical chasm" between questions and answers. The main limitation of these…
Identifying Meaningful Citations
We introduce the novel task of identifying important citations in scholarly literature, i.e., citations that indicate that the cited work is used or extended in the new effort. We believe this task…
Elementary School Science and Math Tests as a Driver for AI: Take the Aristo Challenge!
While there has been an explosion of impressive, datadriven AI applications in recent years, machines still largely lack a deeper understanding of the world to answer questions that go beyond…
Looking Beyond Text: Extracting Figures, Tables and Captions from Computer Science Papers
Identifying and extracting figures and tables along with their captions from scholarly articles is important both as a way of providing tools for article summarization, and as part of larger systems…
Connotation Frames: A Data-Driven Investigation
Through a particular choice of a predicate (e.g., "x violated y"), a writer can subtly connote a range of implied sentiments and presupposed facts about the entities x and y: (1) writer's…
Insights Into Parallelism with Intensive Knowledge Sharing
Novel search space splitting techniques have recently been successfully exploited to paralleliz Constraint Programming and Mixed Integer Programming solvers. We first show how universal hashing can…