The skew divergence 2 accounts for zeros in q by mixing in a small amount of p. Lee found that as α → 1, the performance of skew divergence on natural language tasks improves.
it outperforms most other models and even beats pure KL divergence modified to avoid zeros with sophisticated smoothing models.