Question 14
Which statement is true?
Transformers process sequences sequentially but utilize parallelized loss computation to speed up training.
The attention mechanism strictly limits the context window size, whereas RNNs have a theoretically infinite context window in practice.
Self-attention enables direct interactions between any pair of tokens within a layer.
Transformers inherently encode positional information in their feed-forward weights, eliminating the need for explicit sequence tracking.