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。
$ git clone https://github.com/BDBC-KG-NLP/QA-Survey-CN.gitdialogbot, provide search-based dialogue, task-based dialogue and generative dialogue model. 对话机器人，基于问答型对话、任务型对话、聊天型对话等模型实现，支持网络检索问答，领域知识问答，任务引导问答，闲聊问答，开箱即用。
AI Tool for querying natural language on tabular data.
Multimodal Question Answering in the Medical Domain: A summary of Existing Datasets and Systems
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.
Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN
🚀 RocketQA, dense retrieval for information retrieval and question answering, including both Chinese and English state-of-the-art models.
Data from GitHub · snapshot Sep 24, 2026