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This paper describes our system for The Microsoft AI Challenge India 2018:Ranking Passages for Web Question Answering. The system uses the biLSTM networkwith co-attention mechanism between query and passage representations.Additionally, we use self attention on embeddings to increase the lexicalcoverage by allowing the system to take union over different embeddings. Wealso incorporate hand-crafted features to improve the system performance. Oursystem achieved a Mean Reciprocal Rank (MRR) of 0.67 on eval-1 dataset.

Microsoft AI Challenge India 2018: Learning to Rank Passages for Web Question Answering with Deep Attention Networks