A new method, HammingMark, is proposed for robust and efficient LLM watermarking. It uses the semantic hash of the preceding sentence as a dynamic center and accepts candidates whose hashes fall within its Hamming neighborhood. This approach retains a larger fraction of naturally likely semantic continuations and achieves strong robustness, high detectability, and near-unwatermarked generation quality.