Update README.md

README.md

@@ -235,8 +235,8 @@ $$\mathbf{s}_0 \sim \mathcal{N}(\mathbf{0}, \sigma^2 I_{n\cdot h})$$
 
 $$\mathbf{s}_i = R(\mathbf{e}, \mathbf{s}_{i-1}) \; \textnormal{for} \;  i \in \lbrace 1, \dots, r \rbrace$$
 
-$$\mathbf{p} = R(\mathbf{s}_r)$$
-where \\(\sigma\\) is the standard deviation of the initial random state. Given an init random state \\(\mathbf{s}_0\\), the model repeatedly applies the core 
+$$\mathbf{p} = C(\mathbf{s}_r)$$
+where \\(\sigma\\) is the standard deviation of the initial random state. Given an init random state \\(\mathbf{s}_0\\), the model repeatedly applies the core recurrent 
 block \\(R\\), which accepts the latent state \\(\mathbf{s}_{i-1}\\) and the embedded input \\(\mathbf{e}\\) and outputs a new latent state \\(\mathbf{s}_i\\). 
 After finishing all iterations, the coda block processes the last state and produces the probabilities of the next token.