# Consensus Attention-based Neural Networks for Chinese Reading Comprehension

arXiv: https://arxiv.org/abs/1607.02250 · HTML: https://mlsanity.com/paper/1607.02250/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jul 2016.

## Built on by (most cited first, 12 of 12)

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- [WeLM: A Well-Read Pre-trained Language Model for Chinese](https://mlsanity.com/paper/2209.10372/) (2022)
- [BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data](https://mlsanity.com/paper/2510.10159/) (2025)
- [More Than Reading Comprehension: A Survey on Datasets and Metrics of Textual Question Answering](https://mlsanity.com/paper/2109.12264/) (2021)
- [A Survey on non-English Question Answering Dataset](https://mlsanity.com/paper/2112.13634/) (2021)
- [Contextual embedding and model weighting by fusing domain knowledge on Biomedical Question Answering](https://mlsanity.com/paper/2206.12866/) (2022)
- [Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension](https://mlsanity.com/paper/2112.06494/) (2021)
- [ReverseNER: A Self-Generated Example-Driven Framework for Zero-Shot Named Entity Recognition with Large Language Models](https://mlsanity.com/paper/2411.00533/) (2024)

## Abstract (arXiv)

Reading comprehension has embraced a booming in recent NLP research. Several institutes have released the Cloze-style reading comprehension data, and these have greatly accelerated the research of machine comprehension. In this work, we firstly present Chinese reading comprehension datasets, which consist of People Daily news dataset and Children's Fairy Tale (CFT) dataset. Also, we propose a consensus attention-based neural network architecture to tackle the Cloze-style reading comprehension problem, which aims to induce a consensus attention over every words in the query. Experimental results show that the proposed neural network significantly outperforms the state-of-the-art baselines in several public datasets. Furthermore, we setup a baseline for Chinese reading comprehension task, and hopefully this would speed up the process for future research.