abachaa/Existing-Medical-QA-Datasets
Multimodal Question Answering in the Medical Domain: A summary of Existing Datasets and Systems
收集了目前为止中文领域的MRC抽取式数据集
$ git clone https://github.com/sherlcok314159/ChineseMRC-Data.gitMultimodal Question Answering in the Medical Domain: A summary of Existing Datasets and Systems
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.
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.
Framework for enhancing LLMs for RAG tasks using fine-tuning.
Data from GitHub · snapshot Sep 24, 2026