(1) Self-attention is a mechanism used in deep learning. Which of the following descriptions about self-attention is correct?Self-attention是一項深度學習的機制，下列哪個有關 self-attention 的描述是正確的？Self-attention is not used for text processing. Self-attention 不會用於文字處理。Self-attention mechanism in Transformer does not consider the adjacent tokens in a sentence. Transformer中的Self-attention機制不會考慮句子中相連的Token (詞元)。Self-attention mechanism can extract relations of tokens in the input. Self-attention機制能夠在輸入的Token(詞元)中抽取出關係。Self-attention mechanism in Transformer only considers the adjacent tokens in a sentence. Transformer中的Self-attention機制只考慮句子中相連的Token(詞元)。

In the context of machine learning, what is the purpose of self-attention mechanisms in Transformers?Question 17Answera.Self-attention assists in computing certain functions in machine learning algorithmsb. Self-attention enables efficient exploration of the in put spacec. Self-attention is used to determine specific strategies in machine learning tasksd. Self-attention helps in selecting relevant parts of the input sequence for processing

What is the primary function of the self-attention mechanism in transformers?Group of answer choicesTo perform backpropagationTo reduce the computational costTo reduce the computational cost of trainingTo allow the model to weigh the importance of different words in a sentence relative to each other

3.Question 3What is the self-attention that powers the transformer architecture?1 pointA mechanism that allows a model to focus on different parts of the input sequence during computation.A technique used to improve the generalization capabilities of a model by training it on diverse datasets.A measure of how well a model can understand and generate human-like language.The ability of the transformer to analyze its own performance and make adjustments accordingly.4.Question 4

Which of the following is NOT a core component of the Transformer self-attention mechanism?Question 5Answera.Convolutional Layerb.Query Vectorc.Key Vectord.Value Vector

Which of the following statements best describes the function of attention mechanisms in neural networks?Question 30Answera.They ignore certain input features entirelyb.They allocate computational resources evenly across all input features.c. They prioritize features randomly.d. They selectively weigh input features based on their relevance to the task