At a certain step in a sequence generation process, the probabilities for the next token over a vocabulary V = {'A', 'B', 'C', 'D', 'E'} are as follows: Pr('A')=0.1, Pr('B')=0.4, Pr('C')=0.05, Pr('D')=0.3, Pr('E')=0.15. If the selection process is defined by the function argTopK with K=3, which set of tokens will be selected?

Analyzing a Formalism for Token Selection

Construction of Top-K Candidate Sequences in Beam Search

Formula for Constructing Top-K Candidate Sequences

Evaluating a Token Selection Implementation

Construction of the Optimal Sequence in Greedy Search

An autoregressive model generates the token sequence $y = (\text{'The'}, \text{'quick'}, \text{'brown'}, \text{'fox'})$, where $y_1 = \text{'The'}$, $y_2 = \text{'quick'}$, and so on. What does the notation $y_{<3}$ represent in this specific sequence?

True or False: For an autoregressive model generating the output sequence $y = (y_1, y_2, y_3, y_4)$, the notation $y_{<4}$ represents the complete subsequence $(y_1, y_2, y_3, y_4)$.

Formula for Constructing Top-K Candidate Sequences

An autoregressive language model is generating a sequence of tokens, one at a time. To predict the fifth token in the sequence, denoted as $y_5$, the model uses all the previously generated tokens as context. The standard notation for this preceding subsequence of tokens is ____.