In practice, just remembering a minimal set of features called kernel features˜ f (j, S) suffices to evaluate the equivalence of states: (2) By merging equivalent states based on this condition, we only need to remember relevant information from the top d (d = 3 in our models) trees on the stack to evaluate the score of the next actions.
since the stack shrinks when a REDUCE-LEFT/RIGHT action is applied, you often need to recover the last element of the stack from the history.