7a677bb4477ae2dd371add568dd19e23-AuthorFeedback.pdf

Thank reviewers for detailed comments. Our main contribution is the novel search-and-learning for1 UnsupTextGen, achieving remarkable performance (sometimes even better than SupTextGen). Forexample,8 the rules/heuristics in [18] only applies to sentiment style transfer.Future work MT: Thanks for9 suggesting the future work. We are currently considering MT by using word-level dictionary and10 performingsearchandlearning. R2: 3(Novelty): Our main novelty is the search-and-learning framework TGSL for UnsupTextGen,16 where our learning is non-trivial and involves two stages with different losses, well motivated and17 supportedbyablationstudy.