Several large size datasets on the Document-based Question Answering (DQA) have been released and numerous neural network models achieve good performance. These two tasks above are similar in that they all select sentences from a document to answer a given query/question. We therefore propose a ...
昨天arxiv刚刚也放出了一篇工作《PDFTriage: Question Answering over Long, Structured Documents 》,算是一个不错的解决思路,更加细颗粒度地来做recall,当然如果是希望在学术内容上来提升质量,学术相关的embedding模型、指令数据,以及更加细致和更具针对性的pdf解析都是必要的。 2、llm现在的选择太多了,如果你希望简...
1) Use slide titles to retrieve relevant and engaging text, figures, and tables; 2) Summarize the retrieved context into bullet points with long-form question answering. Our evaluation suggests that long-form QA outperforms state-of-the-art summarization baselines on both automated ROUGE metrics ...
RAGFlowis an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from...
Question answering (QA) is the task of retrieving an answer in response to a question by analyzing documents. Although most of the efforts in developing QA systems are devoted to dealing with electronic text, we consider it is also necessary to develop systems for document images. In this pape...
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from...
Document similarity is the problem of estimating the degree to which a given pair of documents has similar semantic content. An accurate document similarity measure can improve several enterprise relevant tasks such as document clustering, text mining, and question-answering. In this paper, we show ...
Setting RCTs in opposition to other systematic approaches for generating knowledge creates a false dichotomy, and it distracts from the more important question that Shelton addresses—namely, which research method is best suited for the question at hand? The choice of a rese...
Document-based Question AnsweringQuery-focused Multi-document SummarizationTask adaptationDue to the lack of large scale datasets, it remains difficult to train neural Query-focused Multi-Document Summarization (QMDS) models. Several large size datasets on the Document-based Question An...
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from...