Adapting Word Representations Across Corpora
Table 3: Perplexity of the trained language model on various target domains (lower is better).
['[EMPTY]', 'Physics', 'Gaming', 'Android', 'Unix']
We observe that perplexity is lowest with our method of jointly training with target and selected source snippets. Surprisingly, the Src-Tune method does not perform as well on the LM task. On two of the four domains Src-Tune increases perplexity beyond the Tgt baseline. Likewise, Yang17C while providing gains over Tgt in the question deduplication task, increases perplexity for the LM task. Using our word stability measure instead of Yang17’s helps significantly reduce perplexity.