Beam search enhances the decoding process in sequence-to-sequence models compared to greedy decoding by considering multiple candidate sequences at each step, rather than just the single most likely word. Greedy decoding selects the word with the highest probability at each step, without considering the potential impact on future words. This can lead to suboptimal sequences, as a locally optimal choice might not lead to the best overall sequence. Be....
Log in to view the answer
