58 citations · 143 across the 7 of their papers we have counts for
28 papers
On Generating Extended Summaries of Long Documents
Sajad Sotudeh, Arman Cohan, Nazli Goharian
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…
SLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search
Sean MacAvaney, Arman Cohan, Nazli Goharian
With worldwide concerns surrounding the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there is a rapidly growing body of scientific literature on the virus. Clinici…
SPECTER: Document-level Representation Learning using Citation-informed Transformers
Arman Cohan, Sergey Feldman, Iz Beltagy +2
Representation learning is a critical ingredient for natural language processing systems. Recent Transformer language models like BERT learn powerful textual representations, but t…
SLEDGE: A Simple Yet Effective Baseline for COVID-19 Scientific Knowledge Search
Sean MacAvaney, Arman Cohan, Nazli Goharian
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, resear…
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…