Papers with reading comprehension model

3 papers
Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering (D19-58)

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Challenge: Existing work on open-domain multi-hop question answering relies on off-the-shelf information retrieval techniques to retrieve answer passages.
Approach: They propose a new subproblem for open-domain multi-hop question answering . they aim to recognize the anchor from a set of start passages with a reading comprehension model .
Outcome: The proposed method significantly improves the baseline method on the open-domain hotpotQA benchmark.
Neural Models for Reasoning over Multiple Mentions Using Coreference (N18-2)

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Challenge: Existing Recurrent Neural Network (RNN) layers are biased towards short-term dependencies and hence not suited to such tasks.
Approach: They propose a recurrent layer which is instead biased towards coreferent dependencies and uses coreference annotations extracted from an external system to connect entity mentions belonging to the same cluster.
Outcome: The proposed layer improves performance on Wikihop, LAMBADA and the bAbi AI datasets with large gains when training data is scarce.
The Web as a Knowledge-Base for Answering Complex Questions (N18-1)

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Challenge: Recent work on reading comprehension made headway in answering simple questions, but tackling complex questions is still an ongoing research challenge.
Approach: They propose to decompose complex questions into a sequence of simple questions and compute the final answer from the sequence of answers.
Outcome: The proposed framework improves performance from 20.8 precision@1 to 27.5 precision@1.

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