A language model is tasked with generating a five-token sequence ($x_0, x_1, x_2, x_3, x_4$) in the specific permuted order: $x_3 \rightarrow x_1 \rightarrow x_4 \rightarrow x_0 \rightarrow x_2$. At each step, the model predicts the next token in the permutation using the embeddings (e.g., $\mathbf{e}_i$ for token $x_i$) of all previously generated tokens as context. Which of the following correctly represents the conditional probability for the third step of this generation process?

A language model generates a four-token sequence ($x_0, x_1, x_2, x_3$) using the specific permuted order: $x_2 \rightarrow x_0 \rightarrow x_3 \rightarrow x_1$. Arrange the following conditional probability expressions to match this generation sequence, where $\mathbf{e}_i$ represents the embedding of token $x_i$.

A language model is generating a five-token sequence ($x_0, x_1, x_2, x_3, x_4$) using a permuted, non-sequential order. At a specific step in the generation process, the model calculates the probability for token $x_2$ as: $\text{Pr}(x_2|\mathbf{e}_0, \mathbf{e}_4)$, where $\mathbf{e}_i$ is the embedding of token $x_i$. Based only on this information, what can be definitively concluded about the generation process?