Papers › Ruminating Reader: Reasoning with Gated Multi-Hop Attention

Ruminating Reader: Reasoning with Gated Multi-Hop Attention

24 Apr 2017WS 2018 7arXiv:1704.07415archive 2025-07-28

Yichen Gong, Samuel R. Bowman

To answer the question in machine comprehension (MC) task, the models need to establish the interaction between the question and the context. To tackle the problem that the single-pass model cannot reflect on and correct its answer, we present Ruminating Reader. Ruminating Reader adds a second pass of attention and a novel information fusion component to the Bi-Directional Attention Flow model (BiDAF). We propose novel layer structures that construct an query-aware context vector representation and fuse encoding representation with intermediate representation on top of BiDAF model. We show that a multi-hop attention mechanism can be applied to a bi-directional attention structure. In experiments on SQuAD, we find that the Reader outperforms the BiDAF baseline by a substantial margin, and matches or surpasses the performance of all other published systems.

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