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PPLqa: An Unsupervised Information-Theoretic Quality Metric for Comparing Generative Large Language Models
The method and metric enables users to rank generative language models for quality of responses, so as to make a selection of the best model for a given task.
Representation Projection Invariance Mitigates Representation Collapse
In this paper, we propose Representation Projection Invariance (REPINA), a novel regularization method to maintain the information content of representation and reduce representation collapse during fine-tuning by discouraging undesirable changes in the representations.
Improving Early Sepsis Prediction with Multi Modal Learning
Clinical text provides essential information to estimate the severity of the sepsis in addition to structured clinical data.
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