BestHub
Sign in
Tag

Retrieval

0 views collected around this technical thread.

DataFunSummit
DataFunSummit
May 9, 2025 · Artificial Intelligence

Practical Experience Building Zhihu Direct Answer: An AI‑Powered Search Product

This article presents a comprehensive overview of Zhihu Direct Answer, describing its AI‑driven search architecture, RAG framework, query understanding, retrieval, chunking, reranking, generation, evaluation mechanisms, engineering optimizations, and the professional edition, while sharing concrete performance‑boosting practices and future development plans.

AIGenerationRAG
0 likes · 14 min read
Practical Experience Building Zhihu Direct Answer: An AI‑Powered Search Product
Tencent Technical Engineering
Tencent Technical Engineering
Apr 22, 2025 · Artificial Intelligence

Conan-Embedding-V2: A 1.4B LLM‑Based Multilingual Embedding Model Achieving SOTA on MTEB

Conan‑Embedding‑V2, a newly trained 1.4 B‑parameter LLM with a custom tokenizer, 32 k token context, SoftMask, cross‑lingual retrieval data and dynamic hard‑negative mining, delivers state‑of‑the‑art multilingual embeddings that surpass larger models on both English and Chinese MTEB benchmarks while remaining compact and fast.

MTEBRetrievalcross-lingual retrieval
0 likes · 14 min read
Conan-Embedding-V2: A 1.4B LLM‑Based Multilingual Embedding Model Achieving SOTA on MTEB
Architecture and Beyond
Architecture and Beyond
Feb 22, 2025 · Artificial Intelligence

Understanding Retrieval‑Augmented Generation (RAG) and Its Role in Enhancing Large Language Models

The article explains how the inherent knowledge‑staleness, hallucination, lack of private data, non‑traceable output, limited long‑text handling, and data‑security concerns of large language models can be mitigated by Retrieval‑Augmented Generation, which combines external retrieval, augmentation, and generation to provide up‑to‑date, reliable, and secure AI responses.

AILLMRAG
0 likes · 15 min read
Understanding Retrieval‑Augmented Generation (RAG) and Its Role in Enhancing Large Language Models
iKang Technology Team
iKang Technology Team
Feb 7, 2025 · Artificial Intelligence

Retrieval‑Augmented Generation (RAG) with LangChain: Concepts and Python Implementation

Retrieval‑Augmented Generation (RAG) using LangChain lets developers enhance large language models by embedding user queries, fetching relevant documents from a vector store, inserting the context into a prompt template, and generating concise, source‑grounded answers, offering low‑cost, up‑to‑date knowledge while reducing hallucinations and fine‑tuning expenses.

LLMLangChainRAG
0 likes · 10 min read
Retrieval‑Augmented Generation (RAG) with LangChain: Concepts and Python Implementation
Zhihu Tech Column
Zhihu Tech Column
Jan 17, 2025 · Artificial Intelligence

Zhihu Direct Answer: Product Overview and Technical Practices

This article summarizes the key technical insights from Zhihu Direct Answer, an AI-powered search product, covering its product overview, RAG framework, query understanding, retrieval strategies, chunking, reranking, generation techniques, evaluation methods, and engineering optimizations for cost and performance.

AI SearchChunkingEngineering Optimization
0 likes · 13 min read
Zhihu Direct Answer: Product Overview and Technical Practices
DataFunSummit
DataFunSummit
Nov 8, 2024 · Artificial Intelligence

ChatDBA: An AI‑Powered Database Fault Diagnosis Assistant Using Retrieval‑Augmented Generation

ChatDBA, developed by Shanghai Aikesheng, is an AI-driven database operation assistant that leverages large language models and Retrieval‑Augmented Generation to provide fault diagnosis, knowledge learning, SQL generation and optimization, addressing challenges such as vague outputs, complex troubleshooting logic, and memory management through a structured architecture and multi‑modal retrieval strategies.

AIDatabaseFault Diagnosis
0 likes · 10 min read
ChatDBA: An AI‑Powered Database Fault Diagnosis Assistant Using Retrieval‑Augmented Generation
DevOps
DevOps
Oct 27, 2024 · Artificial Intelligence

Best Practices for Building Efficient Retrieval‑Augmented Generation (RAG) Systems

This article reviews Wang et al.'s 2024 research on Retrieval‑Augmented Generation, outlining optimal practices such as query classification, chunk sizing, hybrid metadata search, embedding selection, vector databases, query transformation, reranking, document repacking, summarization, fine‑tuning, and multimodal retrieval to guide developers in constructing high‑performance RAG pipelines.

LLMRAGRetrieval
0 likes · 11 min read
Best Practices for Building Efficient Retrieval‑Augmented Generation (RAG) Systems
AntTech
AntTech
Sep 12, 2024 · Artificial Intelligence

Knowledge‑Enhanced Large Model Service Framework (KAG): Integrating Knowledge Graphs with LLMs for Vertical Domain Applications

The KAG framework combines knowledge‑graph‑driven symbolic reasoning with large language model generation to improve accuracy, reduce hallucinations, and enable controllable, domain‑specific AI services such as government and medical Q&A, with open‑source support via OpenSPG and TuGraph‑DB.

AIRetrievalframework
0 likes · 13 min read
Knowledge‑Enhanced Large Model Service Framework (KAG): Integrating Knowledge Graphs with LLMs for Vertical Domain Applications
AntData
AntData
Jul 12, 2024 · Databases

Recent Advances in Vector Databases Presented at SIGMOD 2024

This article reviews the latest vector database research showcased at SIGMOD 2024, covering system designs such as Starling, Vexless, RaBitQ, and ACORN, and discusses current academic hotspots including query processing, index structures, optimization techniques, and hardware acceleration for large‑scale similarity search.

AIBig DataIndexing
0 likes · 20 min read
Recent Advances in Vector Databases Presented at SIGMOD 2024
DataFunSummit
DataFunSummit
Nov 24, 2023 · Artificial Intelligence

Cold-Start Content Recommendation Practices at Kuaishou

This article describes Kuaishou's approach to cold-start content recommendation, outlining the problems addressed, challenges in modeling sparse new videos, and solutions including graph neural networks, I2U retrieval, TDM hierarchical retrieval, bias correction, and future research directions.

Cold StartKuaishouRetrieval
0 likes · 19 min read
Cold-Start Content Recommendation Practices at Kuaishou
HomeTech
HomeTech
Sep 26, 2023 · Artificial Intelligence

Integrating Large Language Models with Search for Automotive Knowledge Retrieval

This article explores how combining traditional keyword search with large language models (LLMs) enhances understanding of user intent, builds a robust automotive knowledge base, and delivers more accurate, context‑aware answers through a multi‑stage retrieval and generation pipeline.

AIAutomotiveLLM
0 likes · 17 min read
Integrating Large Language Models with Search for Automotive Knowledge Retrieval
Python Programming Learning Circle
Python Programming Learning Circle
Mar 27, 2023 · Artificial Intelligence

OpenAI Launches ChatGPT Plugins: Browser, Code Interpreter, Retrieval and Third‑Party Extensions

OpenAI has unveiled a suite of ChatGPT plugins—including a web‑browser, a code interpreter, a retrieval tool, and support for third‑party services—enabling the model to access up‑to‑date information, run Python code, query vector databases, and integrate external APIs, dramatically expanding its practical capabilities.

Artificial IntelligenceChatGPTCode Interpreter
0 likes · 8 min read
OpenAI Launches ChatGPT Plugins: Browser, Code Interpreter, Retrieval and Third‑Party Extensions
DataFunSummit
DataFunSummit
Mar 24, 2023 · Artificial Intelligence

OpenAI Launches ChatGPT Plugin System: Features, Examples, and Safety Discussion

OpenAI announced a safety‑focused ChatGPT plugin system that connects the model to third‑party APIs for real‑time information retrieval, knowledge‑base access, and task execution, showcasing first‑party browser and code‑interpreter plugins, third‑party extensions, an open‑source retrieval plugin, and a detailed debate on security implications.

AI safetyChatGPTCode Interpreter
0 likes · 9 min read
OpenAI Launches ChatGPT Plugin System: Features, Examples, and Safety Discussion
DataFunTalk
DataFunTalk
Jan 28, 2023 · Artificial Intelligence

Industry Search: Background, Technologies, and Real‑World Applications

This article presents a comprehensive overview of industry search, covering its background, core retrieval and ranking technologies—including sparse and dense retrieval, pre‑trained language models, tokenization, NER, adaptive multi‑task training, and re‑ranking models—followed by detailed case studies such as address analysis, family‑ID unification, emergency call handling, education photo‑search, and power‑knowledge‑base integration.

NLPRetrievaladdress analysis
0 likes · 13 min read
Industry Search: Background, Technologies, and Real‑World Applications
DataFunTalk
DataFunTalk
Nov 8, 2022 · Artificial Intelligence

Retrieval-Based Dialogue System Framework for Customer Service: Architecture, Retrieval, Ranking, and Practical Applications

This article presents a comprehensive retrieval‑based dialogue system designed to assist customer‑service agents by recommending candidate replies, detailing its five‑layer architecture, metric suite, text and vector retrieval modules, ranking strategies, and real‑world deployment results across multiple business scenarios.

AICustomer ServiceNatural Language Processing
0 likes · 34 min read
Retrieval-Based Dialogue System Framework for Customer Service: Architecture, Retrieval, Ranking, and Practical Applications
Zhuanzhuan Tech
Zhuanzhuan Tech
Sep 29, 2022 · Artificial Intelligence

Design and Implementation of ZhiZhuan's Low-Result Search Module with Hybrid Hard and Soft Retrieval

The article details the architecture and techniques of ZhiZhuan's low-result search module, explaining how it combines ElasticSearch hard matching and sBert semantic vector soft matching, along with sophisticated negative sample strategies, to improve recommendation coverage and user experience.

ElasticsearchRetrievalVector Search
0 likes · 17 min read
Design and Implementation of ZhiZhuan's Low-Result Search Module with Hybrid Hard and Soft Retrieval
DataFunSummit
DataFunSummit
Feb 21, 2022 · Artificial Intelligence

Advances in E‑commerce Search: Embedding, Knowledge Graphs, and Retrieval Models

This article reviews recent research on e‑commerce search, covering transformer‑based complementary rankings, Alibaba's cognitive concept net and its extension, joint deep retrieval with product quantization, personalized semantic retrieval, multi‑granularity deep semantic retrieval, and graph‑attention networks for long‑tail shop search.

AIRetrievalembedding
0 likes · 12 min read
Advances in E‑commerce Search: Embedding, Knowledge Graphs, and Retrieval Models
DataFunTalk
DataFunTalk
Dec 13, 2021 · Artificial Intelligence

Dual Vector Foil (DVF): Decoupled Index and Model for Large‑Scale Retrieval

The article introduces the Dual Vector Foil (DVF) algorithm system, which decouples index construction from model training to enable lightweight, high‑precision large‑scale recall using arbitrary complex models, and details its two‑stage and one‑stage solutions, graph‑based retrieval implementation, performance optimizations, and experimental results.

Large ScaleRecommendation systemsRetrieval
0 likes · 28 min read
Dual Vector Foil (DVF): Decoupled Index and Model for Large‑Scale Retrieval
DataFunTalk
DataFunTalk
Nov 12, 2021 · Artificial Intelligence

Xiaomi Xiao AI Intelligent Question‑Answering System: Architecture, Techniques, and Applications

This article presents a comprehensive overview of Xiaomi's Xiao AI intelligent QA system, detailing its background, three core answering modules—knowledge‑graph QA, retrieval‑based FAQ, and reading‑comprehension—and the underlying methods such as template matching, cross‑domain semantic parsing, path‑based reasoning, semantic retrieval, and neural matching, while also discussing performance results and practical trade‑offs.

AINLPReading Comprehension
0 likes · 18 min read
Xiaomi Xiao AI Intelligent Question‑Answering System: Architecture, Techniques, and Applications