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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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Detecting English Writing Styles For Non Native Speakers

Yanging ChenRami Al-RfouYejin Choi
2017
arXiv

This paper presents the first attempt, up to our knowledge, to classify English writing styles on this scale with the challenge of classifying day to day language written by writers with different… 

Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects

Hessam BagherinezhadHannaneh HajishirziYejin Choiand Ali Farhadi
2016
AAAI

Human vision greatly benefits from the information about sizes of objects. The role of size in several visual reasoning tasks has been thoroughly explored in human perception and cognition. However,… 

Neural AMR: Sequence-to-Sequence Models for Parsing and Generation

Ioannis KonstasSrini IyerMark YatskarLuke Zettlemoyer
2016
ACL

Sequence-to-sequence models have shown strong performance across a broad range of applications. However, their application to parsing and generating text using Abstract Meaning Representation (AMR)… 

Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing

Hamid IzadiniaFereshteh SadeghiSantosh Divvalaand Ali Farhadi
2015
ICCV

We introduce Segment-Phrase Table (SPT), a large collection of bijective associations between textual phrases and their corresponding segmentations. Leveraging recent progress in object recognition… 

Connotation Frames: A Data-Driven Investigation

Hannah RashkinSameer SinghYejin Choi
2015
ACL

Through a particular choice of a predicate (e.g., "x violated y"), a writer can subtly connote a range of implied sentiments and presupposed facts about the entities x and y: (1) writer's… 

Finding Deceptive Opinion Spam by Any Stretch of the Imagination

Myle OttYejin ChoiClaire CardieJ. Hancock
2011
ACL

Consumers increasingly rate, review and research products online (Jansen, 2010; Litvin et al., 2008). Consequently, websites containing consumer reviews are becoming targets of opinion spam. While… 

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