Implementation for the paper "Compositional Attention Networks for Machine Reasoning" (Hudson and Manning, ICLR 2018)
$ git clone https://github.com/stanfordnlp/mac-network.git北京航空航天大学大数据高精尖中心自然语言处理研究团队开展了智能问答的研究与应用总结。包括基于知识图谱的问答（KBQA），基于文本的问答系统（TextQA），基于表格的问答系统（TableQA）、基于视觉的问答系统（VisualQA）和机器阅读理解（MRC）等，每类任务分别对学术界和工业界进行了相关总结。
Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.
Dynamic Memory Networks (https://arxiv.org/abs/1603.01417) in Tensorflow
Tensorflow implementations of various Deep Semantic Matching Models (DSMM).
This repo collects and re-produces models related to domains of question answering and machine reading comprehension
Data from GitHub · snapshot Sep 24, 2026