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Research - Papers

Explore a selection of our published work on a variety of key research challenges in AI.

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Metaphor as a Medium for Emotion: An Empirical Study

Saif M. MohammadEkaterina Shutovaand Peter D. Turney
2016
SEM

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

Carissa SchoenickPeter ClarkOyvind Tafjordand Oren Etzioni
2016
CACM

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… 

Much Ado About Time: Exhaustive Annotation of Temporal Data

Gunnar A. SigurdssonOlga RussakovskyAli Farhadiand Abhinav Gupta
2016
HCOMP

Large-scale annotated datasets allow AI systems to learn from and build upon the knowledge of the crowd. Many crowdsourcing techniques have been developed for collecting image annotations. These… 

Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images

Roozbeh MottaghiHessam BagherinezhadMohammad Rastegariand Ali Farhadi
2016
CVPR

In this paper, we study the challenging problem of predicting the dynamics of objects in static images. Given a query object in an image, our goal is to provide a physical understanding of the… 

PDFFigures 2.0: Mining Figures from Research Papers

Christopher Clark and Santosh Divvala
2016
JCDL

Figures and tables are key sources of information in many scholarly documents. However, current academic search engines do not make use of figures and tables when semantically parsing documents or… 

Probabilistic Models for Learning a Semantic Parser Lexicon

Jayant Krishnamurthy
2016
NAACL

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

Daniel KhashabiTushar KhotAshish Sabharwaland Dan Roth
2016
IJCAI

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.… 

Semantic Parsing to Probabilistic Programs for Situated Question Answering

Jayant KrishnamurthyOyvind Tafjordand Aniruddha Kembhavi
2016
EMNLP

Situated question answering is the problem of answering questions about an environment such as an image or diagram. This problem requires jointly interpreting a question and an environment using… 

Situation Recognition: Visual Semantic Role Labeling for Image Understanding

Mark YatskarLuke Zettlemoyerand Ali Farhadi
2016
CVPR

This paper introduces situation recognition, the problem of producing a concise summary of the situation an image depicts including: (1) the main activity (e.g., clipping), (2) the participating… 

Stating the Obvious: Extracting Visual Common Sense Knowledge

Mark YatskarVicente Ordonezand Ali Farhadi
2016
NAACL

Obtaining common sense knowledge using current information extraction techniques is extremely challenging. In this work, we instead propose to derive simple common sense statements from fully…