Update README.md

README.md

@@ -52,8 +52,8 @@ $$
 
 Where:
 - $\theta_s$ and $\theta_t$ represent student (trainable) and teacher (frozen) model parameters
-- $$P_{\theta}^{(i)}$$ denotes the probability distribution at reasoning step $$i$$
-- $$ \lambda(t) = \lambda_0 \cdot (1 + \gamma \cdot \text{complexity}(x_t)) $$ is the dynamic weight function
+- $P_{\theta}^{(i)}$ denotes the probability distribution at reasoning step $i$
+- $\lambda(t) = \lambda_0 \cdot (1 + \gamma \cdot \text{complexity}(x_t))$ is the dynamic weight function
 - $\alpha_i = \exp(-\delta \cdot i/T)$ implements exponential decay for later reasoning steps
 - $\mathcal{L}_{\text{QS}}$ is the quality scoring loss ensuring reasoning coherence