activity
20162025
most citedSnorkel: Rapid Training Data Creation with Weak Supervision

786 citations · 865 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL202212 cited

BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing

Jason Alan Fries, Leon Weber, Natasha Seelam +40

Training and evaluating language models increasingly requires the construction of meta-datasets --diverse collections of curated data with clear provenance. Natural language prompt…

cs.LG202219 cited

Language Models in the Loop: Incorporating Prompting into Weak Supervision

Ryan Smith, Jason A. Fries, Braden Hancock +1

We propose a new strategy for applying large pre-trained language models to novel tasks when labeled training data is limited. Rather than apply the model in a typical zero-shot or…

cs.LG202221 cited

PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts

Stephen H. Bach, Victor Sanh, Zheng-Xin Yong +24

PromptSource is a system for creating, sharing, and using natural language prompts. Prompts are functions that map an example from a dataset to a natural language input and target…

cs.CL2020

Ontology-driven weak supervision for clinical entity classification in electronic health records

Jason A. Fries, Ethan Steinberg, Saelig Khattar +4

In the electronic health record, using clinical notes to identify entities such as disorders and their temporality (e.g. the order of an event relative to a time index) can inform…

cs.LG20192 cited

The accuracy vs. coverage trade-off in patient-facing diagnosis models

Anitha Kannan, Jason Alan Fries, Eric Kramer +3

A third of adults in America use the Internet to diagnose medical concerns, and online symptom checkers are increasingly part of this process. These tools are powered by diagnosis…

cs.CY2019

Medical device surveillance with electronic health records

Alison Callahan, Jason A Fries, Christopher Ré +4

Post-market medical device surveillance is a challenge facing manufacturers, regulatory agencies, and health care providers. Electronic health records are valuable sources of real…