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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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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… 

Text mining approaches for dealing with the rapidly expanding literature on COVID-19

Lucy Lu WangKyle Lo
2020
Briefings in Bioinformatics

More than 50 000 papers have been published about COVID-19 since the beginning of 2020 and several hundred new papers continue to be published every day. This incredible rate of scientific… 

Mitigating Biases in CORD-19 for Analyzing COVID-19 Literature

Anshul KanakiaKuansan WangYuxiao DongChieh-Han Wu
2020
Frontiers in Research Metrics and Analytics

On the behest of the Office of Science and Technology Policy in the White House, six institutions, including ours, have created an open research dataset called COVID-19 Research Dataset (CORD-19) to… 

Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions

Dongyeop KangAndrew HeadRisham SidhuMarti A. Hearst
2020
EMNLP • SDP workshop

The task of definition detection is important for scholarly papers, because papers often make use of technical terminology that may be unfamiliar to readers. Despite prior work on definition… 

PySBD: Pragmatic Sentence Boundary Disambiguation

Nipun SadvilkarM. Neumann
2020
EMNLP • NLP-OSS Workshop

In this paper, we present a rule-based sentence boundary disambiguation Python package that works out-of-the-box for 22 languages. We aim to provide a realistic segmenter which can provide logical… 

Fact or Fiction: Verifying Scientific Claims

David WaddenKyle LoLucy Lu WangHannaneh Hajishirzi
2020
EMNLP

We introduce the task of scientific fact-checking. Given a corpus of scientific articles and a claim about a scientific finding, a fact-checking model must identify abstracts that support or refute… 

MedICaT: A Dataset of Medical Images, Captions, and Textual References

Sanjay SubramanianLucy Lu WangSachin MehtaHannaneh Hajishirzi
2020
Findings of EMNLP

Understanding the relationship between figures and text is key to scientific document understanding. Medical figures in particular are quite complex, often consisting of several subfigures (75% of…