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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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SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

Rowan ZellersYonatan BiskRoy Schwartzand Yejin Choi
2018
EMNLP

Given a partial description like"she opened the hood of the car,"humans can reason about the situation and anticipate what might come next ("then, she examined the engine"). In this paper, we… 

Syntactic Scaffolds for Semantic Structures

Swabha SwayamdiptaSam ThomsonKenton Leeand Noah A. Smith
2018
EMNLP

We introduce the syntactic scaffold, an approach to incorporating syntactic information into semantic tasks. Syntactic scaffolds avoid expensive syntactic processing at runtime, only making use of a… 

AllenNLP: A Deep Semantic Natural Language Processing Platform

Matt GardnerJoel GrusMark NeumannLuke Zettlemoyer
2018
ACL • NLP OSS Workshop

This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. AllenNLP is designed to support researchers who want to build novel language… 

Event2Mind: Commonsense Inference on Events, Intents, and Reactions

Maarten SapHannah RashkinEmily AllawayNoah A. Smith and Yejin Choi
2018
ACL

We investigate a new commonsense inference task: given an event described in a short free-form text (“X drinks coffee in the morning”), a system reasons about the likely intents (“X wants to stay… 

Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples

Vidur JoshiMatthew Petersand Mark Hopkins
2018
ACL

We revisit domain adaptation for parsers in the neural era. First we show that recent advances in word representations greatly diminish the need for domain adaptation when the target domain is… 

LSTMs Exploit Linguistic Attributes of Data

Nelson F. LiuOmer LevyRoy SchwartzNoah A. Smith
2018
ACL • RepL4NLP Workshop

While recurrent neural networks have found success in a variety of natural language processing applications, they are general models of sequential data. We investigate how the properties of natural… 

Simple and Effective Multi-Paragraph Reading Comprehension

Christopher ClarkMatt Gardner
2018
ACL

We consider the problem of adapting neural paragraph-level question answering models to the case where entire documents are given as input. Our proposed solution trains models to produce well… 

Ultra-Fine Entity Typing

Eunsol ChoiOmer LevyYejin Choi and Luke Zettlemoyer
2018
ACL

We introduce a new entity typing task: given a sentence with an entity mention, the goal is to predict a set of free-form phrases (e.g. skyscraper, songwriter, or criminal) that describe appropriate… 

A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications

Dongyeop KangWaleed AmmarBhavana Dalvi MishraRoy Schwartz
2018
NAACL-HLT

Peer reviewing is a central component in the scientific publishing process. We present the first public dataset of scientific peer reviews available for research pur- poses (PeerRead v1), providing… 

Annotation Artifacts in Natural Language Inference Data

Suchin GururanganSwabha SwayamdiptaOmer LevySam Bowman and Noah A. Smith
2018
NAACL

Large-scale datasets for natural language inference are created by presenting crowd workers with a sentence (premise), and asking them to generate three new sentences (hypotheses) that it entails,…