Transformer-XH: Multi-hop question answering with eXtra Hop attention

ICLR 2020 Anonymous

Transformers have obtained significant success modeling natural language as a sequence of text tokens. However, in many real world scenarios, textual data inherently exhibits structures beyond a linear sequence such as tree and graph; an important one being multi-hop question answering, where evidence required to answer questions are scattered across multiple related documents... (read more)

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