Can i use other regression types that arent based in decision trees to use it like a weak learners in gradient boosting?
The issue of using any linear model (a polynomial regression is a particular case of a linear model, with polynomial features), is that an ensemble of linear models is still a linear model. So, the family of models to optimize from given by the boosted polynomial regression and the single polynomial regression are the same.
This doesn't happen with trees, as an ensemble of trees cannot be expressed as a tree anymore, so that's why trees are used more in the context of gbms.