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A synthetic data approach for domain generalization of NLI models
We also demonstrate gains on test sets when in-domain training data is augmented with our domain-general synthetic data.
Measuring the Impact of Explanation Bias: A Study of Natural Language Justifications for Recommender Systems
Despite the potential impact of explanations on decision making, there is a lack of research on quantifying their effect on users' choices.
Applied Federated Learning: Architectural Design for Robust and Efficient Learning in Privacy Aware Settings
The advantage of this approach includes leveraging high performance hardware (such as GPUs) and the ability of machine learning practitioners to do in depth data analysis to improve model performance.
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