59 citations · 275 across the 31 of their papers we have counts for
6 papers · 1 filter
Pretrained Language Models for Sequential Sentence Classification
Arman Cohan, Iz Beltagy, Daniel King +2
As a step toward better document-level understanding, we explore classification of a sequence of sentences into their corresponding categories, a task that requires understanding s…
SUPP.AI: Finding Evidence for Supplement-Drug Interactions
Lucy Lu Wang, Oyvind Tafjord, Arman Cohan +5
Dietary supplements are used by a large portion of the population, but information on their pharmacologic interactions is incomplete. To address this challenge, we present SUPP.AI,…
Ontology-Aware Clinical Abstractive Summarization
Sean MacAvaney, Sajad Sotudeh, Arman Cohan +3
Automatically generating accurate summaries from clinical reports could save a clinician's time, improve summary coverage, and reduce errors. We propose a sequence-to-sequence abst…
CEDR: Contextualized Embeddings for Document Ranking
Sean MacAvaney, Andrew Yates, Arman Cohan +1
Although considerable attention has been given to neural ranking architectures recently, far less attention has been paid to the term representations that are used as input to thes…
Structural Scaffolds for Citation Intent Classification in Scientific Publications
Arman Cohan, Waleed Ammar, Madeleine van Zuylen +1
Identifying the intent of a citation in scientific papers (e.g., background information, use of methods, comparing results) is critical for machine reading of individual publicatio…
SciBERT: A Pretrained Language Model for Scientific Text
Iz Beltagy, Kyle Lo, Arman Cohan
Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive. We release SciBERT, a pretrained language model based on BERT (Devlin et a…