Before revision:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, and moreover allows for fasterdecoding .
After revision:  We find that policies learned in this way allow for interpretable table-to-text and headline generation that is competitive with or better than state-of-the-art autoregressive token-level policies in terms of automatic metrics, though on all but one dataset neighbor-based policies underperform a strong neighborless baseline. In all cases, however, generating by splicing is faster .