Breakthroughs, discoveries, and DIY tips sent every weekday. Judging by newly released photos and video, the crew aboard Ocean Exploration Trust's Nautilus research vessel had an extremely productive summer trip to the South Pacific. Over 22 days, the team completed detailed archaeological surveys of more than a dozen shipwrecks sunk amid the Solomon Islands campaign during World War II. In addition to imaging four of them for the first time, experts guided remotely operated vehicles (ROVs) towards the rediscovery of two long-lost vessels:the separated bow from the USS New Orleans as well as the Imperial Japanese Naval destroyer Teruzuki. Although researchers originally spotted some of these shipwrecks more than 34 years ago, Ocean Exploration Trust president Robert Ballard explained that the most recent trip to Iron Bottom Sound provided opportunities to document their finds using a new generation of technology including high-definition survey cameras, underwater vehicles, and imaging tools aboard the EV Nautilus.

End-to-end neural models have made significant progress in question answering, however recent studies show that these models implicitly assume that the answer and evidence appear close together in a single document. In this work, we propose the Coarse-grain Fine-grain Coattention Network (CFC), a new question answering model that combines information from evidence across multiple documents. The CFC consists of a coarse-grain module that interprets documents with respect to the query then finds a relevant answer, and a fine-grain module which scores each candidate answer by comparing its occurrences across all of the documents with the query. We design these modules using hierarchies of coattention and self-attention, which learn to emphasize different parts of the input. On the Qangaroo WikiHop multi-evidence question answering task, the CFC obtains a new state-of-the-art result of 70.6% on the blind test set, outperforming the previous best by 3% accuracy despite not using pretrained contextual encoders.