Before revision:  On a popular multi-hop QA dataset, HotpotQA, we show large improvements over a strong baseline , especially on adversarial and out-of-domain questions. Our method is generally applicable and automatically learns to decompose questions of different classes , while matching the performance of decomposition methods that rely heavily on hand-engineering and annotation .
After revision:  On a popular multi-hop QA dataset, HotpotQA, we show large improvements over a strong baseline , especially on adversarial and out-of-domain , and multi-hop dev sets. ONUS automatically learns to decompose questions of different classes , while matching the performance of decomposition methods that rely heavily on hand-engineering and annotation .