Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
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…
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…
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction
We present the Mind the Gap Model (MGM), an approach for interpretable feature extraction and selection. By placing interpretability criteria directly into the model, we allow for the model to both…
Parsing Algebraic Word Problems into Equations
This paper formalizes the problem of solving multi-sentence algebraic word problems as that of generating and scoring equation trees. We use integer linear programming to generate equation trees and…
Semantic Role Labeling for Process Recognition Questions
We consider a 4th grade level question answering task. We focus on a subset involving recognizing instances of physical, biological, and other natural processes. Many processes involve similar…
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…
VISALOGY: Answering Visual Analogy Questions
In this paper, we study the problem of answering visual analogy questions. These questions take the form of image A is to image B as image C is to what. Answering these questions entails discovering…
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…
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…
A Data Scientist's Guide to Start-Ups
In August 2013, we held a panel discussion at the KDD 2013 conference in Chicago on the subject of data science, data scientists, and start-ups. KDD is the premier conference on data science…