Relying heavily on neural network assistance for SAT problem solving may present certain limitations or drawbacks. One potential drawback is the interpretability of the neural network's decisions. Neural networks are often considered as black boxes due to their complex internal workings, making it challenging to understand how they arrive at a particular solution. This lack of transparency can hinder trust in the system and raise concerns about bias or errors in decision-making processes. Additionally, neural networks require significant computational resources for training and inference, which can lead to high costs and longer processing times compared to traditional methods.