New Intelligence Report Source: Google AI Editor: LRS [New Intelligence Guide] Based on pre-training experience, more data leads to better performance! Google recently published a paper at NAACL 2021 that can automatically generate text data from knowledge graphs, so there’s no need to worry about insufficient corpora anymore! Large pre-trained natural language processing (NLP) models, … Read more
Author: Gao Kaiyuan School: Shanghai Jiao Tong University Research Direction: Natural Language Processing Zhihu Column: BERT on the Shoulders of Giants Original Article Link: https://zhuanlan.zhihu.com/p/91052495 Introduction In the previous blog, I discussed some knowledge representation learning models. Today, let’s explore the current most popular BERT model and how it develops with the addition of external … Read more
Author丨Zhou Peng Affiliation丨Tencent Research Direction丨Natural Language Processing, Knowledge Graph Background In the past two years, unsupervised pre-trained language representation models such as Google’s BERT have achieved remarkable results in various NLP tasks. These models are pre-trained on large-scale open-domain corpora to obtain general language representations and then fine-tuned on specific downstream tasks to absorb domain-specific … Read more
Many practitioners have found that although RAG can quickly build a demo in a short time, it faces numerous challenges in actual production environments. This article analyzes the core issue of RAG’s industrial implementation from the perspective of entrepreneurs in the AI large model field—problem grading—and discusses the challenges and solutions of four types of … Read more
Reprinted from WeChat Official Account | Blue’s Little Firefly In this article, I would like to accurately introduce the application areas of Knowledge Graphs (KG) in the RAG pipeline. We will explore the different types of questions that arise in the RAG pipeline and how to address these issues by applying knowledge graphs at various … Read more
On the Chaoxing and Zhihuishu course platforms, there are application sections based on the OBE concept for knowledge graphs. Chaoxing refers to it as the target map, while Zhihuishu calls it OBE teaching management. Both are forms of application that measure, evaluate, and provide feedback on the achievement of course objectives under the guidance of … Read more
The knowledge graph is a very popular technology recently, integrating web crawling, natural language processing, machine learning, deep learning, graph databases, complex network analysis, and many other hot technologies into one. The technology density is high, making it a product that companies are very interested in, such as constructing semantic search, Q&A platforms, and intelligent … Read more
A knowledge graph is a technology for organizing and representing knowledge in a graph structure, which builds a computable and inferable knowledge base by abstracting entities, attributes, and relationships. The graphical data structure allows machines to process and understand complex information more naturally, making data retrieval and analysis more efficient. In recent years, knowledge graphs … Read more
Professor Dong Lili, Dean of the School of Architecture and Urban Planning at Chongqing Jiaotong University, National Level Registered Architect, and National Model Teacher for Ideological and Political Education in Courses;Vice Chairman of the Humanities Quality Education Guidance Committee for Ordinary Undergraduate Colleges in Chongqing, Member of the Teaching Guidance Committee for Civil Engineering and … Read more
Click the above“Little Director” to follow the WeChat public account “Construction and Application of Professional Knowledge Graph” Speaker: Ruan Xin Vice President of Tongji University Current Teaching Issues 1Current teaching issues: rapid industry transformation poses challenges for talent training 2“Internet+” background learning model Students have very strong self-learning abilities, learning time is highly fragmented and … Read more