📄 中文摘要
NVIDIA NeMo Retriever 引入了一种新的检索管道，旨在提升信息检索的效率和准确性。该管道不仅关注语义相似性，还引入了代理检索的概念，使得模型能够在多种上下文中灵活应用。通过结合深度学习和自然语言处理技术，该系统能够处理复杂的查询，并从大规模数据集中提取相关信息。研究表明，这种方法在多种任务上表现出色，具有良好的泛化能力，适用于不同领域的应用场景。
超越语义相似性：NVIDIA NeMo Retriever 的可泛化代理检索管道
📄 English Summary
Beyond Semantic Similarity: Introducing NVIDIA NeMo Retriever’s Generalizable Agentic Retrieval Pipeline
NVIDIA NeMo Retriever introduces a novel retrieval pipeline aimed at enhancing the efficiency and accuracy of information retrieval. This pipeline goes beyond mere semantic similarity by incorporating the concept of agentic retrieval, allowing the model to adapt flexibly across various contexts. By leveraging deep learning and natural language processing techniques, the system can handle complex queries and extract relevant information from large-scale datasets. Research indicates that this approach performs exceptionally well across multiple tasks, demonstrating strong generalization capabilities suitable for applications in diverse fields.