Entropy Minimized Ensemble of Adapters

Overview of EMEA Entropy Minimized Ensemble of Adapters, or EMEA, is a method used to optimize ensemble weights in language adapter models for each test sentence. This is accomplished by minimizing the entropy of the predictions made for each test sentence. Essentially, what EMEA does is make sure that the language model is more confident in its predictions for each test input. EMEA uses adapter weights, which are parameters within pre-trained language models that allow for the model to adjust