Martin Ma focused on improving the correctness and stability of transformer internals in the rasbt/llms-from-scratch repository. During this period, he addressed a critical bug in the MultiHeadAttention module by correcting the masking logic for Key-Value caching, ensuring that the number of tokens in queries and keys was accurately reflected. This fix improved the reliability of attention score calculations, particularly in cached decoding scenarios. Working primarily with Python and leveraging deep learning frameworks such as PyTorch, Martin maintained codebase stability by resolving a nuanced edge-case, demonstrating a strong understanding of machine learning model internals and production-level reliability requirements.