Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Automatic Construction of Inference-Supporting Knowledge Bases
While there has been tremendous progress in automatic database population in recent years, most of human knowledge does not naturally fit into a database form. For example, knowledge that "metal…
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…
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…
A Data Scientist's Guide to Start-Ups
In August 2013, we held a panel discussion at the KDD 2013 conference in Chicago on the subject of data science, data scientists, and start-ups. KDD is the premier conference on data science…
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…
Freebase QA: Information Extraction or Semantic Parsing?
We contrast two seemingly distinct approaches to the task of question answering (QA) using Freebase: one based on information extraction techniques, the other on semantic parsing. Results over the…
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:…
Chinese Open Relation Extraction for Knowledge Acquisition
This study presents the Chinese Open Relation Extraction (CORE) system that is able to extract entity-relation triples from Chinese free texts based on a series of NLP techniques, i.e., word…
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…
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…