Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Designing AI Systems that Obey Our Laws and Values
Operational AI systems (for example, self-driving cars) need to obey both the law of the land and our values. We propose AI oversight systems ("AI Guardians") as an approach to addressing this…
Tables as Semi-structured Knowledge for Question Answering
Question answering requires access to a knowledge base to check facts and reason about information. Knowledge in the form of natural language text is easy to acquire, but difficult for automated…
Actions ~ Transformations
What defines an action like “kicking ball”? We argue that the true meaning of an action lies in the change or transformation an action brings to the environment. In this paper, we propose a novel…
Adaptive Concentration Inequalities for Sequential Decision Problems
A key challenge in sequential decision problems is to determine how many samples are needed for an agent to make reliable decisions with good probabilistic guarantees. We introduce Hoeffding-like…
A Diagram Is Worth A Dozen Images
Diagrams are common tools for representing complex concepts, relationships and events, often when it would be difficult to portray the same information with natural images. Understanding natural…
Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects
Human vision greatly benefits from the information about sizes of objects. The role of size in several visual reasoning tasks has been thoroughly explored in human perception and cognition. However,…
A Task-Oriented Approach for Cost-sensitive Recognition
With the recent progress in visual recognition, we have already started to see a surge of vision related real-world applications. These applications, unlike general scene understanding, are task…
Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference
Random projections have played an important role in scaling up machine learning and data mining algorithms. Recently they have also been applied to probabilistic inference to estimate properties of…
Creating Causal Embeddings for Question Answering with Minimal Supervision
A common model for question answering (QA) is that a good answer is one that is closely related to the question, where relatedness is often determined using generalpurpose lexical models such as…
Cross-Sentence Inference for Process Knowledge
For AI systems to reason about real world situations, they need to recognize which processes are at play and which entities play key roles in them. Our goal is to extract this kind of rolebased…