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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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A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers

Pradeep DasigiKyle LoIz BeltagyMatt Gardner
2021
NAACL

Readers of academic research papers often read with the goal of answering specific questions. Question Answering systems that can answer those questions can make consumption of the content much more… 

Extracting a Knowledge Base of Mechanisms from COVID-19 Papers

Aida AminiT. HopeDavid WaddenHannaneh Hajishirzi
2021
NAACL

The urgency of mitigating COVID-19 has spawned a large and diverse body of scientific literature that is challenging for researchers to navigate. This explosion of information has stimulated… 

Simplified Data Wrangling with ir_datasets

Sean MacAvaneyAndrew YatesSergey FeldmanNazli Goharian
2021
arXiv

Managing the data for Information Retrieval (IR) experiments can be challenging. Dataset documentation is scattered across the Internet and once one obtains a copy of the data, there are numerous… 

Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols

Andrew HeadKyle LoDongyeop KangMarti A. Hearst
2021
CHI

Despite the central importance of research papers to scientific progress, they can be difficult to read. Comprehension is often stymied when the information needed to understand a passage resides… 

Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance

Gagan BansalTongshuang (Sherry) WuJoyce ZhouDaniel S. Weld
2021
CHI

Many researchers motivate explainable AI with studies showing that human-AI team performance on decision-making tasks improves when the AI explains its recommendations. However, prior studies… 

What Do We Mean by “Accessibility Research”?: A Literature Survey of Accessibility Papers in CHI and ASSETS from 1994 to 2019

K. MackEmma J. McDonnellDhruv JainLeah Findlater
2021
CHI

Accessibility research has grown substantially in the past few decades, yet there has been no literature review of the field. To understand current and historical trends, we created and analyzed a… 

CODE: COMPILER-BASED NEURON-AWARE ENSEMBLE TRAINING

E. TrainitiThanapon NorasetDavid DemeterSimone Campanoni
2021
Proceedings of Machine Learning and Systems

Deep Neural Networks (DNNs) are redefining the state-of-the-art performance in a variety of tasks like speech recognition and image classification. These impressive results are often enabled by… 

Searching for Scientific Evidence in a Pandemic: An Overview of TREC-COVID

Kirk RobertsTasmeer AlamSteven BedrickW. Hersh
2021
arXiv

We present an overview of the TREC-COVID Challenge, an information retrieval (IR) shared task to evaluate search on scientific literature related to COVID-19. The goals of TREC-COVID include the… 

Improving the Accessibility of Scientific Documents: Current State, User Needs, and a System Solution to Enhance Scientific PDF Accessibility for Blind and Low Vision Users

Lucy Lu WangIsabel CacholaJonathan BraggDaniel S. Weld
2021
arXiv

The majority of scientific papers are distributed in PDF, which pose challenges for accessibility, especially for blind and low vision (BLV) readers. We characterize the scope of this problem by… 

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

Zejiang ShenRuochen ZhangMelissa DellWeining Li
2021
arXiv

Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production and extended for…