Intelligent Knowledge Processing: Self-evolving knowledge graphs, advanced document parsing & sophisticated Large Language Model (LLM) integration that continuously refine search, analysis, and insights generation. Deployment Flexibility Comprehensive deployment options, including cloud, hybrid, and on-...
Additionally, SCoPE refines the CVEFixes dataset, which can be used for fine-tuning pre-trained LLMs for software vulnerability detection. Malware detection In malware detection, LLMs can serve as both the static analysis assistant and the dynamic debugging assistant, improving the efficiency and ...
The Planning for and Assessing Rigor in Rapid Qualitative Analysis (PARRQA) framework is organized progressively across phases from design to dissemination, as follows: 1) rigorous design (rationale and staffing), 2) semi-structured data collection (pilot and planning), 3) RQA: summary template de...
Recognition of Arabic-like scripts such as Persian and Urdu is more challenging than Latin-based scripts. This is due to the presence of a two-dimensional structure, context-dependent character shapes, spaces and overlaps, and placement of diacritics. We present an attention based encoder-decoder ...
Will leave this PR in a draft state for now. More work needs to be done to make a better chunker/retrieval. Different types of prompting modes (novel generation, chat, QA) have fixed formats that should make it easy to create specialty chunkers/retrievers that yield consistently good results...
例如,当文档频繁相互交叉引用或一项任务需要来自许多文档的详细信息时,Refine 链可能会表现不佳。 from langchain.chains import RetrievalQA ruff = RetrievalQA.from_chain_type( llm=llm, chain_type="refine", retriever=db.as_retriever() ) ruff.run(query) 生成结果如下: maprecude信息聚合检索框架 Map...
opportunities to explore the benefits of Chinese medicine. While new drug delivery systems have shown promise in treating brain diseases, they are still in their early stages, and numerous challenges are encountered. Further research is necessary to refine drug delivery carriers and optimize TCM ...
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augmentation summar
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augmentation summar
Segmentation: Implement an additional process after the segmentation stage to refine the segments and preserve the shape of historical handwritten text. Classification models: Combining various classifiers to handle the recognition of hybrid-form documents, in other words, documents that include printed and...