Logprobs, short for logarithm of probabilities, are a mathematical concept used frequently in machine learning models, especially for tasks like natural language processing. By taking the logarithm of probabilities, models can better handle very small numbers that would otherwise lead to numerical instability when multiplied. This transformation also converts these probabilities into additive scores, making operations like comparison and summation more straightforward. Logprobs are used in decision-making algorithms where probability outputs are involved, such as in beam search for sequence prediction.