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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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EARLY FUSION for Goal Directed Robotic Vision

Aaron WalsmanYonatan BiskSaadia GabrielD. Fox
2018
IROS

Building perceptual systems for robotics which perform well under tight computational budgets requires novel architectures which rethink the traditional computer vision pipeline. Modern vision… 

Bridging Knowledge Gaps in Neural Entailment via Symbolic Models

Dongyeop KangTushar KhotAshish Sabharwal and Peter Clark
2018
EMNLP

Most textual entailment models focus on lexical gaps between the premise text and the hypothesis, but rarely on knowledge gaps. We focus on filling these knowledge gaps in the Science Entailment… 

Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Todor MihaylovPeter ClarkTushar KhotAshish Sabharwal
2018
EMNLP

We present a new kind of question answering dataset, OpenBookQA, modeled after open book exams for assessing human understanding of a subject. The open book that comes with our questions is a set of… 

Dissecting Contextual Word Embeddings: Architecture and Representation

Matthew PetersMark NeumannWen-tau Yihand Luke Zettlemoyer
2018
EMNLP

Contextual word representations derived from pre-trained bidirectional language models (biLMs) have recently been shown to provide significant improvements to the state of the art for a wide range… 

Rational Recurrences

Hao PengRoy SchwartzSam Thomsonand Noah A. Smith
2018
EMNLP

Despite the tremendous empirical success of neural models in natural language processing, many of them lack the strong intuitions that accompany classical machine learning approaches. Recently,… 

Spot the Odd Man Out: Exploring the Associative Power of Lexical Resources

Gabriel StanovskyMark Hopkins
2018
EMNLP

We propose Odd-Man-Out, a novel task which aims to test different properties of word representations. An Odd-Man-Out puzzle is composed of 5 (or more) words, and requires the system to choose the… 

Structured Alignment Networks for Matching Sentences

Yang LiuMatt GardnerMirella Lapata
2018
EMNLP

Many tasks in natural language processing involve comparing two sentences to compute some notion of relevance, entailment, or similarity. Typically this comparison is done either at the word level… 

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… 

Neural Metaphor Detection in Context

Ge GaoEunsol ChoiYejin Choi and Luke Zettlemoyer
2018
EMNLP

We present end-to-end neural models for detecting metaphorical word use in context. We show that relatively standard BiLSTM models which operate on complete sentences work well in this setting, in…