In April 2026, Zahra Golpayegani focused on improving speculative decoding reliability in the vllm-project/vllm-ascend repository by addressing a bug in the block verification path of the rejection sampler. She implemented a block_verify-aware sampling flow in Python, aligning the acceptance criteria with referenced research to ensure tokens are sampled from the correct distribution based on the block verification flag. Zahra validated the changes with unit tests and began groundwork for broader correctness checks. Her work in algorithm design and data processing enhanced decoding correctness and stability, reducing mis-sampling and supporting more robust production deployments in machine learning applications.