  Recent coreference resolution models rely heavily on span representations to
find coreference links between word spans. As the number of spans is $O(n^2)$
in the length of text and the number of potential links is $O(n^4)$, various
pruning techniques are necessary to make this approach computationally
feasible. We propose instead to consider coreference links between individual
words rather than word spans and then reconstruct the word spans. This reduces
the complexity of the coreference model to $O(n^2)$ and allows it to consider
all potential mentions without pruning any of them out. We also demonstrate
that, with these changes, SpanBERT for coreference resolution will be
significantly outperformed by RoBERTa. While being highly efficient, our model
performs competitively with recent coreference resolution systems on the
OntoNotes benchmark.
