A language model computes a probability distribution over its vocabulary by transforming a vector of aggregated distances. The transformation is applied to the negative of these distances, such that smaller distances result in higher probabilities. Given the following aggregated distances for four vocabulary tokens, which token will be assigned the highest probability?

• Token 'alpha': 5.2
• Token 'beta': 1.8
• Token 'gamma': 9.4
• Token 'delta': 2.1

True or False: In the process of creating a probability distribution from k-nearest neighbors, applying the Softmax function directly to the vector of positive aggregated distances (e.g., [d_0, ..., d_|V|]) would result in tokens with larger distances being assigned higher probabilities.

Debugging a k-NN Probability Calculation