Just-in-time compilers enhance the performance of future invocations of a function by generating code tailored to past behavior. To achieve this, compilers use a data structure, often referred to as a feedback vector, to record information about each function’s invocations. However, over time, feedback vectors tend to become less precise, leading to lower-quality code – a phenomenon known as feedback vector pollution. This paper examines feedback vector pollution within the context of a compiler for the R language. We provide data, discuss an approach to reduce pollution in practice, and implement a proof-of-concept implementation of this approach. The preliminary results of the implementation indicate ~30% decrease in polluted compilations and ~37% decrease in function pollution throughout our corpus.