Natural Language Processing

Instant Consumer Technology Team

Jun 4, 2025 · Artificial Intelligence

Unlocking Retrieval-Augmented Generation: Theory, Practice, and Future Trends

This comprehensive article examines Retrieval‑Augmented Generation (RAG), covering its historical evolution, core theory, implementation variants, practical code examples, diverse applications, current controversies, and future research directions within the AI and NLP landscape.

Artificial IntelligenceGenerative ModelsNatural Language Processing

0 likes · 21 min read

Unlocking Retrieval-Augmented Generation: Theory, Practice, and Future Trends

AntData

May 30, 2025 · Artificial Intelligence

DeepInsight Copilot: AI‑Powered Data Analysis Platform Overview and Technical Evolution

The article presents an in‑depth overview of DeepInsight Copilot, an AI‑driven business intelligence product that streamlines data, information, insight, and decision‑recommendation stages, detailing its functional modules, intelligent agents, multi‑generation technical evolution, architecture, model fine‑tuning, and future challenges and solutions in data analysis.

AIBusiness IntelligenceCopilot

0 likes · 21 min read

DeepInsight Copilot: AI‑Powered Data Analysis Platform Overview and Technical Evolution

Beijing SF i-TECH City Technology Team

Apr 7, 2025 · Artificial Intelligence

LLM Application in Text Information Detection and Extraction: A Case Study of Blue-Collar Recruitment Data Processing

This article explores the application of Large Language Models (LLM) in text information detection and extraction, focusing on blue-collar recruitment data processing. It details the implementation of LLM through prompt engineering, RAG enhancement, and model fine-tuning to improve data cleaning efficiency and accuracy.

AI applicationsLLMNatural Language Processing

0 likes · 31 min read

LLM Application in Text Information Detection and Extraction: A Case Study of Blue-Collar Recruitment Data Processing

Cognitive Technology Team

Mar 30, 2025 · Artificial Intelligence

Why Prompt Engineering Is the “Mind‑Reading” Technique of AI: The Crucial Role of In‑Context Learning

Prompt engineering uses in‑context learning to turn large language models into precise, task‑aware assistants by providing well‑crafted prompts that guide the model’s probability distribution, reduce hallucinations, and unlock hidden knowledge without any parameter tuning.

Artificial IntelligenceIn-Context LearningLarge Language Models

0 likes · 6 min read

Why Prompt Engineering Is the “Mind‑Reading” Technique of AI: The Crucial Role of In‑Context Learning

Efficient Ops

Mar 16, 2025 · Artificial Intelligence

How AI Digital Humans Transform Banking Services: Architecture, Capabilities, and Use Cases

This article explains how AI-powered digital humans can modernize banking by offering modular, multi‑modal interaction, personalized multilingual service, 24‑hour availability, and risk‑aware automation, while detailing the underlying AI foundation, decision engine, visual rendering, and deployment strategies.

AICustomer ServiceDigital Human

0 likes · 7 min read

How AI Digital Humans Transform Banking Services: Architecture, Capabilities, and Use Cases

Xiaohongshu Tech REDtech

Jan 16, 2025 · Artificial Intelligence

Enhancing Uncertainty Modeling with Semantic Graph for Hallucination Detection

The authors present a semantic‑graph‑enhanced uncertainty modeling framework that captures token, sentence, and paragraph dependencies, propagates uncertainty through entity relations and contradiction probabilities, and achieves roughly a 20 % gain in paragraph‑level hallucination detection on WikiBio and NoteSum compared with existing uncertainty‑based baselines.

Hallucination DetectionLarge Language ModelsNatural Language Processing

0 likes · 13 min read

Enhancing Uncertainty Modeling with Semantic Graph for Hallucination Detection

Java Architecture Diary

Jan 8, 2025 · Backend Development

How to Use Spring AI MCP with Chat2DB for Natural Language Database Queries

This tutorial explains how to integrate Spring AI's Model Context Protocol (MCP) with Chat2DB to enable secure, natural‑language queries against a PostgreSQL database, covering configuration, core Java code, execution flow, and sample SQL queries.

BackendChat2DBDatabase Query

0 likes · 8 min read

How to Use Spring AI MCP with Chat2DB for Natural Language Database Queries

DaTaobao Tech

Aug 16, 2024 · Artificial Intelligence

Effective Prompt Design for Large Language Models

Effective prompt design for large language models requires clear goals, relevant context, explicit input/output formats, evaluation criteria, and illustrative examples, combined with specific language, step‑by‑step instructions, edge‑case handling, ethical considerations, and proper tokenization, encoding, decoding, and post‑processing to produce accurate, concise, low‑hallucination responses.

AILarge Language ModelsNatural Language Processing

0 likes · 33 min read

Effective Prompt Design for Large Language Models

JD Tech

Jul 11, 2024 · Artificial Intelligence

Intelligent Parcel Identification in JD Express Logistics Using Large Language Models

This article examines the challenges of low parcel matching rates in JD Express logistics and proposes a large‑model‑based intelligent identification system, detailing its architecture, accuracy validation, cost‑saving cache strategy, and future prospects for improved efficiency and personalized services.

AI in e-commerceLarge Language ModelsLogistics

0 likes · 24 min read

Intelligent Parcel Identification in JD Express Logistics Using Large Language Models

Baidu Tech Salon

May 27, 2024 · Artificial Intelligence

Intelligent Agent Technology in Commercial Advertising Platforms: Architecture and Applications

The paper describes Baidu’s AI‑native advertising platform that employs a multi‑agent architecture built on large‑language models—combining large‑small model collaboration, domain SOP‑driven coordination, and long‑term memory—to enable natural‑language understanding, proactive planning, execution and human‑like responses, illustrated by GBI analytics and JarvisBot operations, delivering higher consumption, accuracy, speed and efficiency.

AI-native platformsAIOpsBusiness Intelligence

0 likes · 16 min read

Intelligent Agent Technology in Commercial Advertising Platforms: Architecture and Applications

Architect's Guide

May 13, 2024 · Artificial Intelligence

Understanding the Core Principles of Transformer Architecture

This article explains how Transformer models work by detailing the encoder‑decoder structure, self‑attention, multi‑head attention, positional encoding, and feed‑forward networks, and shows their applications in machine translation, recommendation systems, and large language models.

AINatural Language ProcessingTransformer

0 likes · 11 min read

Understanding the Core Principles of Transformer Architecture

New Oriental Technology

Apr 19, 2024 · Artificial Intelligence

Effective Prompt Engineering for Large Language Models

This article explains how large language models work, why well‑crafted prompts are essential, and presents practical strategies—such as clarity, conciseness, focus, role‑setting, delimiters, few‑shot examples, and step‑by‑step instructions—to help users obtain accurate and relevant responses from AI systems.

AILLM strategiesNatural Language Processing

0 likes · 12 min read

Effective Prompt Engineering for Large Language Models

DataFunSummit

Mar 17, 2024 · Databases

Exploring Natural Language Interaction Methods for Database Systems

Postdoctoral researcher Fan Yuankai from Fudan University will present his work on enabling natural-language queries for database systems, covering NL2SQL approaches, reliable ranking mechanisms, and guiding large models to generate accurate SQL, aiming to improve usability for users unfamiliar with query languages.

AI for DatabasesDatabase InteractionLarge Language Models

0 likes · 3 min read

Exploring Natural Language Interaction Methods for Database Systems

DataFunSummit

Mar 6, 2024 · Artificial Intelligence

Document Intelligence: Background, Technology, Large Models, and Enterprise Applications

This article presents a comprehensive overview of document intelligence, covering its background, technical evolution, large‑model advancements, and practical enterprise digital transformation use cases, with a focus on multimodal processing, unified document representation, and industry‑specific applications such as legal contract automation.

Large Language ModelsNatural Language Processingdocument intelligence

0 likes · 14 min read

Document Intelligence: Background, Technology, Large Models, and Enterprise Applications

Bilibili Tech

Feb 18, 2024 · Artificial Intelligence

Bilibili Personal Attack Content Governance: Background, Goals, Methods, and Effectiveness

Bilibili combats personal‑attack and trolling comments by combining sector‑specific keyword databases, user‑group analysis, advanced word‑matching (including pinyin and homophone detection) and multiple NLP/graph models, which has cut personal‑attack reports in entertainment, film and gaming by about 32 % and trolling reports by roughly 25 % between June and December 2023.

BilibiliNatural Language ProcessingText Classification

0 likes · 12 min read

Bilibili Personal Attack Content Governance: Background, Goals, Methods, and Effectiveness

DataFunSummit

Jan 17, 2024 · Artificial Intelligence

Applying Large Language Models in Zhihu’s Jianqiao Enterprise Analytics Platform

This article shares the practical application of large language models within Zhihu’s internal Jianqiao analytics platform, covering business background, knowledge taxonomy organization, natural‑language‑to‑filter conversion, natural‑language data analysis, and summarizing challenges, solutions, and future outlooks.

AI applicationsLarge Language ModelsNatural Language Processing

0 likes · 14 min read

Applying Large Language Models in Zhihu’s Jianqiao Enterprise Analytics Platform

DataFunTalk

Dec 26, 2023 · Artificial Intelligence

The Evolution of AI and Its Challenges in the Data Industry

This article reviews the historical development of artificial intelligence, explains how AI technologies such as large language models are reshaping data processing and analysis, and discusses the practical challenges, trust issues, and governance requirements when applying AI to the data industry.

Artificial IntelligenceData IndustryGPT

0 likes · 10 min read

The Evolution of AI and Its Challenges in the Data Industry

DataFunSummit

Dec 21, 2023 · Artificial Intelligence

The Evolution of AI and Its Challenges and Opportunities in the Data Industry

This article reviews the historical development of artificial intelligence, examines how AI—especially large language models like GPT—can transform data analysis and governance, and outlines the practical challenges, reliability concerns, and future opportunities of integrating AI into the data industry.

Artificial IntelligenceData AnalyticsGPT

0 likes · 8 min read

The Evolution of AI and Its Challenges and Opportunities in the Data Industry

DataFunSummit

Sep 19, 2023 · Artificial Intelligence

Advances in Information Extraction: From PLM to LLM Paradigms at Alibaba DAMO Academy

This article reviews Alibaba DAMO Academy's research on information extraction, covering background concepts, PLM-era extraction paradigms, few‑shot extraction techniques, and the emerging LLM‑era approaches, while also sharing practical insights, benchmark results, and future directions.

Alibaba DAMOInformation ExtractionLarge Language Models

0 likes · 24 min read

Advances in Information Extraction: From PLM to LLM Paradigms at Alibaba DAMO Academy

Model Perspective

Sep 11, 2023 · Artificial Intelligence

Why Chinese Word Segmentation Matters: Techniques, Challenges, and Python Demo

This article explores Chinese word segmentation, illustrating its linguistic nuances with a humorous example, explains key methods—including dictionary‑based, statistical, and deep‑learning approaches—and provides Python code using a simple dictionary algorithm and the popular jieba library to demonstrate practical implementation.

Chinese NLPNatural Language ProcessingPython

0 likes · 6 min read

Why Chinese Word Segmentation Matters: Techniques, Challenges, and Python Demo