Papers with Multi-hop reading comprehension
Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension (P19-1)
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| Challenge: | Existing models for multi-hop reading comprehension only require a single-hop reasoning, meaning that the evidence needed to answer the question is scattered in a set of supporting documents. |
| Approach: | They propose an interpretable 3-module system called Explore-Propose-Assemble reader (EPAr) that explores and connects relevant information from multiple documents in order to answer a question about the context. |
| Outcome: | The proposed model approximates coarse-to-fine-grained comprehension behavior of human readers when facing multiple long documents. |
Deep Inductive Logic Reasoning for Multi-Hop Reading Comprehension (2022.acl-long)
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| Challenge: | a new method for multi-hop reading comprehension uses deep learning to reason across documents . a previous study showed that deep learning methods only implicitly encode query-related information into embeddings . |
| Approach: | They propose a deep-learning based inductive logic reasoning method that extracts query-related information and conducts logic reasoning among filtered information. |
| Outcome: | The proposed model is evaluated on two reading comprehension datasets . it uses attentive memories with novel differentiable logic operators . |