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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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SLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search

S. MacAvaneyArman CohanN. Goharian
2020
EMNLP

With worldwide concerns surrounding the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there is a rapidly growing body of literature on the virus. Clinicians, researchers, and… 

Social Chemistry 101: Learning to Reason about Social Norms and Moral Norms

Maxwell ForbesJena D. HwangVered ShwartzYejin Choi
2020
EMNLP

Social norms---the unspoken commonsense rules about acceptable social behavior---are crucial in understanding the underlying causes and intents of people's actions in narratives. For example,… 

The Multilingual Amazon Reviews Corpus

Phillip KeungY. LuGyorgy SzarvasNoah A. Smith
2020
EMNLP

We present the Multilingual Amazon Reviews Corpus (MARC), a large-scale collection of Amazon reviews for multilingual text classification. The corpus contains reviews in English, Japanese, German,… 

Thinking Like a Skeptic: Defeasible Inference in Natural Language

Rachel RudingerVered ShwartzJena D. HwangNoah A. Smith and Yejin Choi
2020
Findings of EMNLP

Defeasible inference is a mode of reasoning in which an inference (X is a bird, therefore X flies) may be weakened or overturned in light of new evidence (X is a penguin). Though long recognized in… 

TLDR: Extreme Summarization of Scientific Documents

Isabel CacholaKyle LoArman CohanDaniel S. Weld
2020
Findings of EMNLP

We introduce TLDR generation for scientific papers, a new automatic summarization task with high source compression, requiring expert background knowledge and complex language understanding. To… 

TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions

Qiang NingHao WuRujun HanDan Roth
2020
EMNLP

A critical part of reading is being able to understand the temporal relationships between events described in a passage of text, even when those relationships are not explicitly stated. However,… 

UnifiedQA: Crossing Format Boundaries With a Single QA System

Daniel KhashabiSewon MinTushar KhotHannaneh Hajishirzi
2020
Findings of EMNLP

Question answering (QA) tasks have been posed using a variety of formats, such as extractive span selection, multiple choice, etc. This has led to format-specialized models, and even to an implicit… 

UnQovering Stereotyping Biases via Underspecified Questions

Tao LiTushar KhotDaniel KhashabiVivek Srikumar
2020
Findings of EMNLP

While language embeddings have been shown to have stereotyping biases, how these biases affect downstream question answering (QA) models remains unexplored. We present UNQOVER, a general framework… 

Unsupervised Commonsense Question Answering with Self-Talk

Vered ShwartzPeter WestRonan Le BrasYejin Choi
2020
EMNLP

Natural language understanding involves reading between the lines with implicit background knowledge. Current systems either rely on pre-trained language models as the sole implicit source of world… 

What-if I ask you to explain: Explaining the effects of perturbations in procedural text

Dheeraj RajagopalNiket TandonPeter ClarkEduard H. Hovy
2020
Findings of EMNLP

We address the task of explaining the effects of perturbations in procedural text, an important test of process comprehension. Consider a passage describing a rabbit's life-cycle: humans can easily…