Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Discriminative and Consistent Similarities in Instance-Level Multiple Instance Learning
In this paper we present a bottom-up method to instance level Multiple Instance Learning (MIL) that learns to discover positive instances with globally constrained reasoning about local pairwise…
Generating Notifications for Missing Actions: Don’t forget to turn the lights off!
We all have experienced forgetting habitual actions among our daily activities. For example, we probably have forgotten to turn the lights off before leaving a room or turn the stove off after…
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…
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…
Learning Everything about Anything: Webly-Supervised Visual Concept Learning
Recognition is graduating from labs to real-world applications. While it is encouraging to see its potential being tapped, it brings forth a fundamental challenge to the vision researcher:…
Diagram Understanding in Geometry Questions
Automatically solving geometry questions is a longstanding AI problem. A geometry question typically includes a textual description accompanied by a diagram. The first step in solving geometry…