Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Insights Into Parallelism with Intensive Knowledge Sharing
Novel search space splitting techniques have recently been successfully exploited to paralleliz Constraint Programming and Mixed Integer Programming solvers. We first show how universal hashing can…
Learning Everything about Anything: Webly-Supervised Visual Concept Learning
Recognition is graduating from labs to real-world applications. While it is encouraging to see its potential being tapped, it brings forth a fundamental challenge to the vision researcher:…
Learning to Solve Arithmetic Word Problems with Verb Categorization
This paper presents a novel approach to learning to solve simple arithmetic word problems. Our system, ARIS, analyzes each of the sentences in the problem statement to identify the relevant…
Modeling Biological Processes for Reading Comprehension
Machine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. In this paper, we focus on a new reading…
Open Question Answering Over Curated and Extracted Knowledge Bases
We consider the problem of open-domain question answering (Open QA) over massive knowledge bases (KBs). Existing approaches use either manually curated KBs like Freebase or KBs automatically…
Diagram Understanding in Geometry Questions
Automatically solving geometry questions is a longstanding AI problem. A geometry question typically includes a textual description accompanied by a diagram. The first step in solving geometry…
Discourse Complements Lexical Semantics for Non-factoid Answer Reranking
We propose a robust answer reranking model for non-factoid questions that integrates lexical semantics with discourse information, driven by two representations of discourse: a shallow…
A Lightweight and High Performance Monolingual Word Aligner
Fast alignment is essential for many natural language tasks. But in the setting of monolingual alignment, previous work has not been able to align more than one sentence pair per second. We describe…
Automatic Coupling of Answer Extraction and Information Retrieval
Information Retrieval (IR) and Answer Extraction are often designed as isolated or loosely connected components in Question Answering (QA), with repeated overengineering on IR, and not necessarily…
Answer Extraction as Sequence Tagging with Tree Edit Distance
Our goal is to extract answers from preretrieved sentences for Question Answering (QA). We construct a linear-chain Conditional Random Field based on pairs of questions and their possible answer…