activity
20162023
most citedDERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents

13 citations · 15 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20232 cited

Generating medically-accurate summaries of patient-provider dialogue: A multi-stage approach using large language models

Varun Nair, Elliot Schumacher, Anitha Kannan

A medical provider's summary of a patient visit serves several critical purposes, including clinical decision-making, facilitating hand-offs between providers, and as a reference f…

cs.CL202313 cited

DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents

Varun Nair, Elliot Schumacher, Geoffrey Tso +1

Large language models (LLMs) have emerged as valuable tools for many natural language understanding tasks. In safety-critical applications such as healthcare, the utility of these…

cs.CL2021

Improving Zero-Shot Multi-Lingual Entity Linking

Elliot Schumacher, James Mayfield, Mark Dredze

Entity linking -- the task of identifying references in free text to relevant knowledge base representations -- often focuses on single languages. We consider multilingual entity l…

cs.CL2019

Phenotyping of Clinical Notes with Improved Document Classification Models Using Contextualized Neural Language Models

Andriy Mulyar, Elliot Schumacher, Masoud Rouhizadeh +1

Clinical notes contain an extensive record of a patient's health status, such as smoking status or the presence of heart conditions. However, this detail is not replicated within t…

cs.CL2016

A Readability Analysis of Campaign Speeches from the 2016 US Presidential Campaign

Elliot Schumacher, Maxine Eskenazi

Readability is defined as the reading level of the speech from grade 1 to grade 12. It results from the use of the REAP readability analysis (vocabulary - Collins-Thompson and Call…