An $($m$,$n$)$ correlating branch predictor uses the behavior of the most recent m executed branches to choose from $2$m predictors, each of which is an n$-$bit predictor. A two$-$level local predictor works in a similar fashion, but only keeps track of the past behavior of each individual branch to predict future behavior.