Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
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…
Examples are not enough. Learn to criticize! Criticism for Interpretability
Example-based explanations are widely used in the effort to improve the interpretability of highly complex distributions. However, prototypes alone are rarely sufficient to represent the gist of the…
IKE - An Interactive Tool for Knowledge Extraction
Recent work on information extraction has suggested that fast, interactive tools can be highly effective; however, creating a usable system is challenging, and few publicly available tools exist. In…
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…
Metaphor as a Medium for Emotion: An Empirical Study
It is generally believed that a metaphor tends to have a stronger emotional impact than a literal statement; however, there is no quantitative study establishing the extent to which this is true.…
Moving Beyond the Turing Test with the Allen AI Science Challenge
The field of Artificial Intelligence has made great strides forward recently, for example AlphaGo's recent victory against the world champion Lee Sedol in the game of Go, leading to great optimism…
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…
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.…