Worked on the alibaba/ChatLearn repository to address a key bug affecting the consistency of special token handling during text generation. Focused on aligning the default value of the skip_special_tokens parameter across different VLLM module versions, the solution involved deriving the default directly from model arguments and updating the configuration logic. This change shifted the default from False to True, ensuring stable and predictable behavior in production deployments. The work required a strong understanding of LLM model configuration and was implemented using Python and YAML. The update improved cross-version reliability and traceability for teams deploying language models in varied environments.