584 citations · 1.1k across the 51 of their papers we have counts for
9 papers · 1 filter
Document-Level Definition Detection in Scholarly Documents: Existing Models, Error Analyses, and Future Directions
Dongyeop Kang, Andrew Head, Risham Sidhu +3
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…
Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols
Andrew Head, Kyle Lo, Dongyeop Kang +4
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…
TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick +6
TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pand…
Don't Stop Pretraining: Adapt Language Models to Domains and Tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta +4
Language models pretrained on text from a wide variety of sources form the foundation of today's NLP. In light of the success of these broad-coverage models, we investigate whether…
TLDR: Extreme Summarization of Scientific Documents
Isabel Cachola, Kyle Lo, Arman Cohan +1
We introduce TLDR generation, a new form of extreme summarization, for scientific papers. TLDR generation involves high source compression and requires expert background knowledge…
Fact or Fiction: Verifying Scientific Claims
David Wadden, Shanchuan Lin, Kyle Lo +4
We introduce scientific claim verification, a new task to select abstracts from the research literature containing evidence that SUPPORTS or REFUTES a given scientific claim, and t…