# Dependent Gated Reading for Cloze-Style Question Answering

Source: [Dependent Gated Reading for Cloze-Style Question Answering](<https://www.sota2.com/research/paper/68fa65c51e209131cea0c61c>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T21:35:37.665Z

Authors: Reza Ghaeini, Xiaoli Z. Fern, Hamed Shahbazi, Prasad Tadepalli

Published: 2018-05-26T19:26:35.000Z

## Abstract

We present a novel deep learning architecture to address the cloze-style question answering task. Existing approaches employ reading mechanisms that do not fully exploit the interdependency between the document and the query. In this paper, we propose a novel \\emph{dependent gated reading} bidirectional GRU network (DGR) to efficiently model the relationship between the document and the query during encoding and decision making. Our evaluation shows that DGR obtains highly competitive performance on well-known machine comprehension benchmarks such as the Children's Book Test (CBT-NE and CBT-CN) and Who DiD What (WDW, Strict and Relaxed). Finally, we extensively analyze and validate our model by ablation and attention studies.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1805.10528>)

[PDF](<https://arxiv.org/pdf/1805.10528.pdf>)