The paper proposes a new method for training language models that is based on the idea of self-supervised learning. The method, called "self-supervised learning with contrastive estimation," involves training the model to predict the next word in a sequence of words, but with the addition of a "negative" example that is not the next word in the sequence. The model is then trained to minimize the distance between the predicted word and the actual next word, while maximizing the distance between the predicted word and the negative example. The authors argue that this method helps to improve the generalization ability of the model, as it forces the model to learn the underlying relationships between words.
What was the name of the treaty signed between Germany and the Soviet Union before the outbreak of World War II?
What was the name of the British Prime Minister who was in office when World War II broke out?
Who was the German Chancellor who came to power in 1933 and was responsible for the outbreak of World War II?