Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Question Answering via Integer Programming over Semi-Structured Knowledge
Answering science questions posed in natural language is an important AI challenge. Answering such questions often requires non-trivial inference and knowledge that goes beyond factoid retrieval.…
Probabilistic Models for Learning a Semantic Parser Lexicon
We introduce several probabilistic models for learning the lexicon of a semantic parser. Lexicon learning is the first step of training a semantic parser for a new application domain and the quality…
Stating the Obvious: Extracting Visual Common Sense Knowledge
Obtaining common sense knowledge using current information extraction techniques is extremely challenging. In this work, we instead propose to derive simple common sense statements from fully…
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,…
Toward a Taxonomy and Computational Models of Abnormalities in Images
The human visual system can spot an abnormal image, and reason about what makes it strange. This task has not received enough attention in computer vision. In this paper we study various types of…
Instructable Intelligent Personal Agent
Unlike traditional machine learning methods, humans often learn from natural language instruction. As users become increasingly accustomed to interacting with mobile devices using speech, their…
Toward Automatic Bootstrapping of Online Communities Using Decision-theoretic Optimization
Successful online communities (e.g., Wikipedia, Yelp, and StackOverflow) can produce valuable content. However, many communities fail in their initial stages. Starting an online community is…
AI assisted ethics
The growing number of 'smart' instruments, those equipped with AI, has raised concerns because these instruments make autonomous decisions; that is, they act beyond the guidelines provided them by…
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
Sequence-to-sequence models have shown strong performance across a broad range of applications. However, their application to parsing and generating text using Abstract Meaning Representation (AMR)…
My Computer is an Honor Student — but how Intelligent is it? Standardized Tests as a Measure of AI
Given the well-known limitations of the Turing Test, there is a need for objective tests to both focus attention on, and measure progress towards, the goals of AI. In this paper we argue that…