What is the potential disadvantage of using beam search with a very large beam size during decoding?

The potential disadvantage of using beam search with a very large beam size during decoding is the increased computational cost and memory requirements. Beam search is a decoding algorithm that maintains multiple candidate sequences (beams) at each step, expanding the most promising ones based on their probabilities. The beam size determines the number of candidate sequences that are kept alive at each step. While a larger beam size can potentially lead to better results by exploring a wider range of possibilities, it also significantly increases the computational cost because the model has to evaluate the probabilities of many more sequences at each step. Additionally, storing all these candidate sequences requires more memory. The computational cost increases linearly with the beam size. So, a beam size of 100 will take approximately 10 times as long and use ten times more memory compared to a beam size of 10. At some point, the increase in computation and memory outweighs the improvement in text quality, making a smaller beam size more practical. The returns on the larger beam begin to diminish as the computation costs drastically increase.