You can improve LLM logical reasoning by combining neural networks with symbolic reasoning modules to handle structured logic more effectively.
Here is the code snippet below:

In the above code we are using the following key points:
-
Neural encoder (LSTM) to process sequence embeddings
-
A symbolic reasoning-inspired layer to perform structured transformations
-
A simple decision classifier to output logical conclusions
Hence, neural-symbolic architectures enhance LLMs by adding structured logical manipulation capabilities alongside deep learning flexibility.