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Partisan polarization in the American states affects the productivity and policy content that legislatures produce; however, the pattern of polarization is difficult to explain. This paper employs a set of estimates of the policy content of the universe of state legislation since 2009, generated by a machine learning approach using a large language model, to determine how interest group lobbying contributes to legislative polarization. It finds that interest group lobbying affects the policy agendas of different states, in particular, there is usually less legislation introduced in state policy areas with a denser interest group lobbying population, as interest groups are capable of exhibiting negative agenda control. These agenda effects have downstream impacts on the level of partisan division in roll-call voting. We conclude with the implications of these findings for the study of interest groups and public policy