Update README.md

README.md

@@ -59,7 +59,6 @@ output = gate * ASPP(x) + (1-gate) * Attention(x)
 ```python
 class ASPPOperator:
     """
-    Simplified ASPP without neighbor gathering to reduce overfitting
 
     Forward pass:
     1. Optional dimensionality reduction: h_t = down_proj(hidden_states)
@@ -246,7 +245,7 @@ Exponential convergence to fixed points with rate c=0.76 under Lipschitz continu
 ### Turing Completeness
 Proven via cyclic tag system simulation - ASPP can compute any Turing-computable function given sufficient depth.
 
-**Implementation Note**: This implementation simplifies theoretical ASPP to point-wise evolution (no neighbor gathering) to reduce overfitting while maintaining iterative refinement benefits.
+**Implementation Note**: This implementation simplifies theoretical ASPP to point-wise evolution to reduce overfitting while maintaining iterative refinement benefits.
 
 ## Files in Checkpoint