George Mason NLP
George Mason NLP
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efficient-NLP/AI
A Paradigm Shift from “Human Writing” to “Machine Generation” in Personality Test Development: An Application of State-of-the-art Natural Language Processing
Synthetic Question Value Estimation for Domain Adaptation of Question Answering
Efficient NLP/AI
We study building NLP/AI models with limited supervision, especially for low-resource domains (e.g., healthcare).
CliniQG4QA: Generating diverse questions for domain adaptation of clinical question answering
An Imitation Game for Learning Semantic Parsers from User Interaction
StaQC: A systematically mined question-code dataset from stack overflow
Semi-Supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-Level Statistical Constraint
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