Search Results for author: Christopher Parisien

Found 5 papers, 1 papers with code

AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts

no code implementations9 Apr 2024 Shaona Ghosh, Prasoon Varshney, Erick Galinkin, Christopher Parisien

As Large Language Models (LLMs) and generative AI become more widespread, the content safety risks associated with their use also increase.

CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues

no code implementations4 Apr 2024 Makesh Narsimhan Sreedhar, Traian Rebedea, Shaona Ghosh, Christopher Parisien

Recent advancements in instruction-tuning datasets have predominantly focused on specific tasks like mathematical or logical reasoning.

Chatbot Instruction Following +1

Prompt Learning for Domain Adaptation in Task-Oriented Dialogue

no code implementations10 Nov 2022 Makesh Narsimhan Sreedhar, Christopher Parisien

We show that canonical forms offer a promising alternative to traditional methods for intent classification.

Domain Adaptation intent-classification +4

GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

no code implementations2 Feb 2022 Xi Yang, Aokun Chen, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G Flores, Ying Zhang, Tanja Magoc, Christopher A Harle, Gloria Lipori, Duane A Mitchell, William R Hogan, Elizabeth A Shenkman, Jiang Bian, Yonghui Wu

GatorTron models scale up the clinical language model from 110 million to 8. 9 billion parameters and improve 5 clinical NLP tasks (e. g., 9. 6% and 9. 5% improvement in accuracy for NLI and MQA), which can be applied to medical AI systems to improve healthcare delivery.

Clinical Concept Extraction Language Modelling +5

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