With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots. python nlp machine-learning information-retrieval ai transformers pytorch question-answering summarization language-model semantic-search squad bert rag gpt-3 large-...
3、TILE: CoQA: A Conversational Question Answering Challenge Author: Siva Reddy • Danqi Chen • Christopher D. Manning Paper: arxiv.org/pdf/1808.0704 Code: github.com/stanfordnlp/ 论文简述: 人类通过参与一系列的问答对话来收集信息。机器能够回答对话性问题对帮助其信息收集是至关重要的。
4、TILE: XQA: A Cross-lingual Open-domain Question Answering Dataset Author: Jiahua Liu , Yankai Lin , Zhiyuan Liu , Maosong Sun Paper:aclweb.org/anthology/P1 Code: github.com/thunlp/XQA 论文简述: 本文构建了一个用于跨语言OpenQA研究的新数据集XQA。它包括英语培训集以及其他八种语言的...
Adam Fisch , Jason Weston , Antoine BordesPaper:https://arxiv.org/pdf/1704.00051v2.pdfCode:https://github.com/facebookresearch/ParlAI论文简述:本文提出利用维基百科作为唯一的知识来源来解决开放领域的问题:任何事实性问题的答案都是维基百科文章的一个文本范围。大...
Code:https://github.com/allenai/bi-att-flow 论文简述:机器理解(Machine comprehension, MC)主要用于回答关于给定上下文段落的查询,它需要对上下文和查询之间的复杂交互进行建模。最近,注意力机制已经成功地扩展到MC。通常,这些方法将注意力集中在上下文的一小部分,并以固定大小的向量、时间上的耦合注意力和/或通常...
Code:https://github.com/facebookresearch/LAMA 论文简述:本文深入分析了在一系列最先进的预训练语言模型中已经存在(没有微调)的关系知识。我们发现:(1)在没有微调的情况下,BERT包含了与传统NLP方法相竞争的关系知识,后者可以访问oracle知识;(2)BERT在有监督基线的开放域问题回答上也做得非常好,(3)通过标准语言...
Explore an emerging NLP capability with WikiQA, an automated question answering system built on top of Wikipedia. - bwiandt/CML_AMP_Question_Answering
https://github.com/ncbi-nlp/BioWordVec https://www.webmd.com/ BookCorpus [60], CC-NEWS, OpenWebText, Stories [61] and English Wikipedia References Qiao J, Yuan Z, Xiong G, Yu Q, Ying H, Tan C, Chen M, Huang S, Liu X, Yu S (2022) Biomedical question answering: a survey of...
Visual Question Answering (VQA) models fail catastrophically on questions related to the reading of text-carrying images. However, TextVQA aims to answer questions by understanding the scene texts in an image–question context, such as the brand name of a product or the time on a clock from ...
Whereas these NLI definitions might be suitable for the broad topic of text understanding, their relation to practical information retrieval or question answering systems is not straightforward. In contrast, RQE needs tailoring to the question answering task. For instance, if the premise question is ...