Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
See the Glass Half Full: Reasoning about Liquid Containers, their Volume and Content
Humans have rich understanding of liquid containers and their contents; for example, we can effortlessly pour water from a pitcher to a cup. Doing so requires estimating the volume of the cup,…
Pros and Cons of Autonomous Weapons Systems
Autonomous weapons systems and military robots are progressing from science fiction movies to designers' drawing boards, to engineering laboratories, and to the battlefield. These machines have…
Interactive Visualization for Linguistic Structure
We provide a visualization library and web interface for interactively exploring a parse tree or a forest of parses. The library is not tied to any particular linguistic representation, but provides…
Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers
We present an approach for answering questions that span multiple sentences and exhibit sophisticated cross-sentence anaphoric phenomena, evaluating on a rich source of such questions--the math…
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:…
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…
Ontology Aware Token Embeddings for Prepositional Phrase Attachment
Type-level word embeddings use the same set of parameters to represent all instances of a word regardless of its context, ignoring the inherent lexical ambiguity in language. Instead, we embed…
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…
Automatic Selection of Context Configurations for Improved Class-Specific Word Representations
This paper is concerned with identifying contexts useful for training word representation models for different word classes such as adjectives (A), verbs (V), and nouns (N). We introduce a simple…
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…