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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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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… 

Gender trends in computer science authorship

Lucy Lu WangGabriel StanovskyLuca WeihsOren Etzioni
2021
CACM

A comprehensive and up-to-date analysis of Computer Science literature (2.87 million papers through 2018) reveals that, if current trends continue, parity between the number of male and female… 

On Generating Extended Summaries of Long Documents

Sajad SotudehArman CohanNazli Goharian
2021
AAAI • Scientific Document Understanding Workshop

Prior work in document summarization has mainly focused on generating short summaries of a document. While this type of summary helps get a high-level view of a given document, it is desirable in… 

Optimizing AI for Teamwork

Gagan BansalBesmira NushiEce KamarDaniel S. Weld
2021
AAAI

In many high-stakes domains such as criminal justice, finance, and healthcare, AI systems may recommend actions to a human expert responsible for final decisions, a context known as AI-advised… 

GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation

Daniel KhashabiGabriel StanovskyJonathan BraggDaniel S. Weld
2021
arXiv

Leaderboards have eased model development for many NLP datasets by standardizing their evaluation and delegating it to an independent external repository. Their adoption, however, is so far limited…