Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Domain-Targeted, High Precision Knowledge Extraction
Our goal is to construct a domain-targeted, high precision knowledge base (KB), containing general (subject,predicate,object) statements about the world, in support of a downstream…
End-to-end Neural Coreference Resolution
We introduce the first end-to-end coreference resolution model and show that it significantly outperforms all previous work without using a syntactic parser or handengineered mention detector. The…
How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets
Large scale machine learning produces massive datasets whose items are often associated with a confidence level and can thus be ranked. However, computing the precision of these resources requires…
Learning What is Essential in Questions
Question answering (QA) systems are easily distracted by irrelevant or redundant words in questions, especially when faced with long or multi-sentence questions in difficult domains. This paper…
Leveraging Term Banks for Answering Complex Questions: A Case for Sparse Vectors
While open-domain question answering (QA) systems have proven effective for answering simple questions, they struggle with more complex questions. Our goal is to answer more complex questions…
Neural Semantic Parsing with Type Constraints for Semi-Structured Tables
We present a new semantic parsing model for answering compositional questions on semi-structured Wikipedia tables. Our parser is an encoder-decoder neural network with two key technical innovations:…
QSAnglyzer: Visual Analytics for Prismatic Analysis of Question Answering System Evaluations
Developing sophisticated artificial intelligence (AI) systems requires AI researchers to experiment with different designs and analyze results from evaluations (we refer this task as evaluation…
Tell Me Why: Using Question Answering as Distant Supervision for Answer Justification
For many applications of question answering (QA), being able to explain why a given model chose an answer is critical. However, the lack of labeled data for answer justifications makes learning this…
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task
A writer’s style depends not just on personal traits but also on her intent and mental state. In this paper, we show how variants of the same writing task can lead to measurable differences in…
Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge
Traditional semantic parsers map language onto compositional, executable queries in a fixed schema. This map- ping allows them to effectively leverage the information con- tained in large, formal…