Original Article from New Intelligence Editors: Zhang Jia, Jin Lei [New Intelligence Overview] The Google NLP model BERT, which once broke 11 records, has recently faced skepticism from netizens: the model’s success in some benchmark tests is merely due to exploiting false statistical cues in the dataset, and without them, it might perform worse than … Read more
Machine Heart Column Author: Xiaomi AI Lab NLP Team When a technology is applied in practice, it often encounters various challenges. Taking BERT as an example, when adapting to business needs, engineers need to make various adjustments according to specific scenarios. This article introduces the practical exploration of the Xiaomi AI Lab NLP team in … Read more
Guest Speaker: Wei Tianwen, Xiaomi AI Department Edited by: Li Shuna Source: DataFunTalk Introduction: Xiao Ai is an intelligent voice system developed by Xiaomi, widely used in smartphones, bands, speakers, TVs, and other electronic products, supporting various voice interaction scenarios such as casual conversation, Q&A, and voice control. The accuracy of Automatic Speech Recognition (ASR) … Read more
Authorized Reprint from Andy’s Writing Room Author:ANDY The BERT pre-trained model is like a pig ready for cooking, and fine-tuning is the cooking method. The pig’s head can be made into fragrant and rich roasted pig head meat, the trotters can be made into hearty braised trotters, and the various cuts like pork belly and … Read more
Ali Sister’s Guide: BERT, a landmark in the field of natural language processing, did not appear out of nowhere; it has its development principles behind it. Today, the Ant Financial Wealth Dialogue Algorithm Team has organized and compared the development history of deep learning models in the field of natural language processing. From simple neurons … Read more
Paper: https://arxiv.org/abs/2501.00888 Github: https://github.com/Alibaba-NLP/CHRONOS Demo: https://modelscope.cn/studios/vickywu1022/CHRONOS In the digital age, the exponential growth of news information makes it crucial to extract and organize historical event timelines from massive texts. To address this challenge, Alibaba’s Tongyi Lab and researchers from Shanghai Jiao Tong University proposed a new framework for news timeline summarization based on agents—CHRONOS, named … Read more
To effectively implement <span>RAG</span>, there are indeed many aspects that need refinement, and today we will learn about the Reject Module. Official Explanation In the RAG (Retrieval-Augmented Generation) model, the Reject Module is an important component designed to enhance the robustness of the generation model when facing irrelevant queries or information. Plain Explanation A simple … Read more
This is the sixth article in the large model programming series, and also my notes from the free course on some cloud large model engineer ACA certification[1]. This course is really good, highly recommended! 👍🏻 If you’re interested in the course, please click the link at the bottom to view the original article. Here are … Read more
TrustRAG Project Address🌟: **https://github.com/gomate-community/TrustRAG** Configurable Modular RAG Framework Introduction to Chunking In the RAG (Retrieval-Augmented Generation) task, chunking is a critical step, especially when dealing with complex PDF documents.PDF documents may contain images, strange layouts, etc., which increases the difficulty of chunking. Impact of Chunk Granularity Sentence/Word Granularity: Focuses on local, key information queries but … Read more
Reply ‘data’ to receive a collection of algorithm interview questions (large models, deep learning, machine learning). 1. What is Retrieval-Augmented Generation (RAG)? RAG is a hybrid approach that combines retrieval systems and generative language models. It consists of two steps: Retrieval Component: Searches for relevant information in large external corpora or datasets based on the … Read more