BestHub
Sign in
Tagged articles
174 articles
Page 2 of 2
Baobao Algorithm Notes
Baobao Algorithm Notes
Oct 17, 2024 · Artificial Intelligence

How Meta’s Movie Gen Pushes Text‑to‑Video Generation to New Heights

Meta’s newly released 92‑page Movie Gen paper introduces a multimodal LLM that unifies text‑to‑image, text‑to‑video, personalized video, precise video editing, and audio generation, detailing its dual‑model architecture, training pipeline, temporal auto‑encoder design, scaling strategies, evaluation benchmark, and ablation studies.

Deep LearningModel ScalingVideo Generation
0 likes · 34 min read
How Meta’s Movie Gen Pushes Text‑to‑Video Generation to New Heights
Bilibili Tech
Bilibili Tech
Sep 18, 2024 · Artificial Intelligence

Index-1.9B-32K: A 2% GPT-Size Model with Powerful Long-Context Capabilities

Index-1.9B-32K is a 1.9B-parameter model with a 32K token context window, achieving strong long‑text performance comparable to larger models while using only about 2% of GPT‑4’s compute, trained via long pre‑training and supervised fine‑tuning, with a trade‑off of reduced short‑context ability.

AIFine-tuningevaluation
0 likes · 12 min read
Index-1.9B-32K: A 2% GPT-Size Model with Powerful Long-Context Capabilities
Architect
Architect
Jul 13, 2024 · Artificial Intelligence

Practical Guide to Building LLM Products: Prompt Engineering, RAG, Evaluation, and Operations

This article provides a comprehensive, step‑by‑step guide for developing large‑language‑model (LLM) applications, covering prompt design techniques, n‑shot and chain‑of‑thought strategies, retrieval‑augmented generation, structured I/O, workflow optimization, evaluation pipelines, operational best practices, and team organization to create reliable, scalable AI products.

AI OperationsLLMProduct Development
0 likes · 54 min read
Practical Guide to Building LLM Products: Prompt Engineering, RAG, Evaluation, and Operations
DataFunTalk
DataFunTalk
Jul 7, 2024 · Artificial Intelligence

Large Model Application Development: Architecture, Lifecycle, and Prompt Engineering

This article presents a comprehensive knowledge map for developing large‑model applications, covering a four‑layer technical architecture, the full development lifecycle, core elements such as prompt engineering and model fine‑tuning, evaluation methods, and practical case studies, offering guidance for both enterprises and startups.

AI application developmentLarge ModelPrompt engineering
0 likes · 15 min read
Large Model Application Development: Architecture, Lifecycle, and Prompt Engineering
AI Large Model Application Practice
AI Large Model Application Practice
Jul 4, 2024 · Artificial Intelligence

Mastering Multimodal RAG: From PDF Parsing to Advanced Query Rewriting

This article explains how to handle complex multimodal PDFs in RAG systems, outlines extraction, indexing, and multimodal model integration, details four query‑rewriting strategies (HyDE, stepwise, sub‑question, backward), and presents key evaluation metrics and tools for assessing RAG performance.

Document ParsingQuery RewritingRAG
0 likes · 12 min read
Mastering Multimodal RAG: From PDF Parsing to Advanced Query Rewriting
Continuous Delivery 2.0
Continuous Delivery 2.0
Jul 3, 2024 · Artificial Intelligence

Applying Large Language Models to Software Engineering: Challenges, Cross‑File Editing Issues, Bug‑Fixing Evaluation, and SWE‑Bench Results

This article examines the practical challenges of using large language models in software development, including handling long contexts, cross‑file editing, bug‑fixing evaluation methods, and presents benchmark results from SWE‑Bench and its Lite subset to assess model capabilities.

Cross-File EditingLLMSWE-bench
0 likes · 7 min read
Applying Large Language Models to Software Engineering: Challenges, Cross‑File Editing Issues, Bug‑Fixing Evaluation, and SWE‑Bench Results
DataFunSummit
DataFunSummit
Jun 16, 2024 · Artificial Intelligence

Reinforcement Learning in Recommendation Systems: Practice, Challenges, and Industry Advances

This article presents a comprehensive overview of applying reinforcement learning to recommendation systems, covering background challenges, practical exploration, frontier research directions, multi‑agent and inverse RL approaches, evaluation methods, and future outlooks, based on a KDD‑published study and industry experience.

Inverse RLRecommendation Systemsevaluation
0 likes · 24 min read
Reinforcement Learning in Recommendation Systems: Practice, Challenges, and Industry Advances
Bilibili Tech
Bilibili Tech
Jun 14, 2024 · Artificial Intelligence

Technical Report on the Index-1.9B Series: Model Variants, Pre‑training Optimizations, and Alignment Experiments

The report presents the open‑source Index‑1.9B family—base, pure, chat, and character variants—detailing benchmark results, pre‑training optimizations such as a normalized LM‑Head and deeper‑slim architectures, the importance of modest instruction data, alignment via SFT/DPO, role‑play enhancements with RAG, and acknowledges remaining safety and factual limitations.

AlignmentInstruction TuningLLM
0 likes · 15 min read
Technical Report on the Index-1.9B Series: Model Variants, Pre‑training Optimizations, and Alignment Experiments
DataFunSummit
DataFunSummit
Jun 10, 2024 · Artificial Intelligence

Xiaomi Agent Technology: Architecture, Prompt Management, and Evaluation

This article presents Xiaomi's work on LLM‑based Agent technology, covering its perception‑thinking‑action pipeline, technical framework, prompt management, executor and API platform, workflow, optimization strategies, evaluation metrics, and future directions for AI assistants.

AI AssistantAgentLLM
0 likes · 17 min read
Xiaomi Agent Technology: Architecture, Prompt Management, and Evaluation
DevOps
DevOps
May 23, 2024 · Information Security

Guidelines for Evaluating Large Language Models in Cybersecurity Tasks

The article examines the opportunities and risks of applying large language models (LLMs) to cybersecurity, outlines fourteen practical recommendations for assessing their real‑world capabilities, and concludes with an invitation to the upcoming R&D Efficiency Conference covering AI, product management, and related topics.

AI SafetyLLMcybersecurity
0 likes · 11 min read
Guidelines for Evaluating Large Language Models in Cybersecurity Tasks
NewBeeNLP
NewBeeNLP
May 18, 2024 · Artificial Intelligence

How to Detect Test Set Contamination in Black‑Box Language Models

Researchers propose a black‑box method to expose test‑set leakage in large language models by comparing log‑probability shifts when test items are shuffled, using Monte‑Carlo estimation and a sharded likelihood test, and demonstrate its effectiveness on several models including Mistral‑7B.

LLMblack-box detectionevaluation
0 likes · 8 min read
How to Detect Test Set Contamination in Black‑Box Language Models
DataFunTalk
DataFunTalk
May 7, 2024 · Artificial Intelligence

Large Language Models and Knowledge Graphs: Recent Advances, Synergies, and Future Directions

This article reviews the rapid progress of large language models, compares them with knowledge graphs, explores how LLMs can aid knowledge extraction and completion, discusses how knowledge graphs can evaluate and enhance LLMs, and outlines future interactive integration between the two technologies.

AIInformation ExtractionKnowledge Graphs
0 likes · 12 min read
Large Language Models and Knowledge Graphs: Recent Advances, Synergies, and Future Directions
AI Large Model Application Practice
AI Large Model Application Practice
May 3, 2024 · Artificial Intelligence

Can Giant Context LLMs Replace RAG? Exploring the Limits of Long‑Context Retrieval

This article examines whether the rapid growth of large‑language‑model context windows can eliminate the need for retrieval‑augmented generation, presenting experimental needle‑in‑a‑haystack tests, analysis of model performance across token lengths and needle positions, and practical guidance using an open‑source evaluation tool.

AILLMNeedle-in-a-Haystack
0 likes · 13 min read
Can Giant Context LLMs Replace RAG? Exploring the Limits of Long‑Context Retrieval
360 Tech Engineering
360 Tech Engineering
Apr 17, 2024 · Artificial Intelligence

HiCo: A Hierarchical Controllable Diffusion Model for Layout‑to‑Image Generation

The 360 AI Research Institute introduces HiCo, a hierarchical controllable diffusion model that enables fine‑grained layout control across up to eight image regions, integrates seamlessly with existing Stable Diffusion ecosystems, and demonstrates superior performance on the GRIT‑VAL benchmark for layout‑aware image synthesis.

AI drawingControllable GenerationHiCo
0 likes · 8 min read
HiCo: A Hierarchical Controllable Diffusion Model for Layout‑to‑Image Generation
Tech Architecture Stories
Tech Architecture Stories
Jan 29, 2024 · R&D Management

Mastering Tech Promotion Reviews: Proven Strategies to Accelerate Your Career

This guide shares years of promotion‑review experience from major tech firms, outlining company‑specific promotion processes and five essential content elements—systematic design, detailed data, derivation reasoning, upstream/downstream context, and comparative analysis—plus practical presentation and logical techniques to help engineers secure promotions and salary raises.

R&D managementcareer advancementevaluation
0 likes · 8 min read
Mastering Tech Promotion Reviews: Proven Strategies to Accelerate Your Career
DataFunSummit
DataFunSummit
Jan 14, 2024 · Artificial Intelligence

Large Language Model Innovations for the Financial Industry: From General to Finance‑Specific Models, Training Techniques, Evaluation Methods, and Real‑World Applications

This article details how the financial sector is adopting large language models, describing the shift from generic to finance‑specific models, the technical challenges and cost considerations, the XuanYuan model releases, novel training and evaluation approaches, and a range of practical applications such as marketing, service, operations, office assistance, and risk control.

AIApplicationsModel Training
0 likes · 17 min read
Large Language Model Innovations for the Financial Industry: From General to Finance‑Specific Models, Training Techniques, Evaluation Methods, and Real‑World Applications
DataFunTalk
DataFunTalk
Jan 2, 2024 · Artificial Intelligence

Mid‑Stage Reflections on Large‑Model Technology and Its Industry Impact

This article offers a comprehensive mid‑stage analysis of large‑model technology, discussing its rapid development, emerging challenges such as cost and hallucinations, positioning, scenario applications, cost‑value trade‑offs, and strategic pathways for future research and deployment.

AIApplicationsCost
0 likes · 21 min read
Mid‑Stage Reflections on Large‑Model Technology and Its Industry Impact
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Dec 29, 2023 · Artificial Intelligence

Overview of Major Benchmark Datasets for Evaluating Large Language Models

This article provides a comprehensive overview of major benchmark datasets—including CMMLU, MMLU, C‑Eval, GSM8K, Gaokao‑Bench, AGIEval, MATH, BBH, HumanEval, and MBPP—used to evaluate large language models' knowledge, reasoning, and coding abilities, and summarizes related leaderboards and evaluation tools.

DatasetLLMartificial intelligence
0 likes · 14 min read
Overview of Major Benchmark Datasets for Evaluating Large Language Models
Baidu Geek Talk
Baidu Geek Talk
Dec 20, 2023 · Artificial Intelligence

A Unified Platform for Prompt Development, Evaluation, and Iteration in Large Language Model Applications

The proposed unified platform centralizes prompt creation, evaluation, and iteration for large‑model applications, offering one‑stop hosting, metric‑driven testing, seamless resource integration, model switching, fine‑grained traffic control, and an automated data‑flywheel with QEP scoring, cutting optimization cycles from weeks to days while paving the way for advanced fine‑tuning techniques.

AI PlatformAutomationData Flywheel
0 likes · 17 min read
A Unified Platform for Prompt Development, Evaluation, and Iteration in Large Language Model Applications
AntTech
AntTech
Dec 19, 2023 · Artificial Intelligence

RJUA‑QA: A Comprehensive Urology QA Dataset for Large Language Model Evaluation

RJUA‑QA is a newly released, large‑scale urology question‑answer dataset constructed from virtual patient records based on clinical experience, featuring 2,132 QA pairs with extensive context, designed to benchmark and improve large language models’ medical reasoning, diagnosis, and treatment recommendation capabilities.

DatasetQA datasetUrology
0 likes · 12 min read
RJUA‑QA: A Comprehensive Urology QA Dataset for Large Language Model Evaluation
JD Cloud Developers
JD Cloud Developers
Nov 28, 2023 · Backend Development

Choosing the Right Java Expression Engine: Performance, Security, and Community Insights

This article provides a comprehensive overview and comparative analysis of popular Java expression engines—including AviatorScript, MVEL, OGNL, SpEL, QLExpress, JEXL, JUEL, and Janino—covering their features, community support, size, performance benchmarks, security settings, usage cases, and syntax differences to guide developers in selecting the most suitable engine for their projects.

Expression EngineJavaSecurity
0 likes · 23 min read
Choosing the Right Java Expression Engine: Performance, Security, and Community Insights
Ant R&D Efficiency
Ant R&D Efficiency
Nov 24, 2023 · Artificial Intelligence

CodeFuseEval: An Enterprise‑Level Multi‑Task Benchmark for Evaluating Code Large Models

CodeFuseEval is an enterprise‑grade, multi‑task benchmark that evaluates code‑generation large models across six languages and thousands of real‑world tasks using both objective metrics (pass@k, BLEU, CodeBLEU) and expert human review, with an open‑source framework, continuous dataset expansion, and a focus on correctness, efficiency, robustness, and service‑level quality.

AIBenchmarkCode Generation
0 likes · 12 min read
CodeFuseEval: An Enterprise‑Level Multi‑Task Benchmark for Evaluating Code Large Models
Baobao Algorithm Notes
Baobao Algorithm Notes
Oct 23, 2023 · Artificial Intelligence

Why Multimodal AI Agents Could Be the Next Killer App for Large Models

The article recounts a personal test of a multimodal AI agent in Newport Beach and expands into a detailed analysis of current multimodal LLM architectures, memory mechanisms, task planning, tool usage, personality modeling, cost constraints, evaluation challenges, and the broader social and reliability implications of deploying such agents.

AI agentsCostMemory
0 likes · 44 min read
Why Multimodal AI Agents Could Be the Next Killer App for Large Models
Architecture and Beyond
Architecture and Beyond
Sep 3, 2023 · R&D Management

Effective Team Management: Definitions, Development Stages, and Best Practices

This article explains what a team is, describes its open‑system nature and three‑layer composition, outlines the Tuckman development model and leadership growth stages, and provides practical guidance on direction, leadership, roles, systems, communication, relationships, and evaluation for managing high‑performing technical teams.

LeadershipTeam Developmentcommunication
0 likes · 45 min read
Effective Team Management: Definitions, Development Stages, and Best Practices
Baobao Algorithm Notes
Baobao Algorithm Notes
Aug 22, 2023 · Artificial Intelligence

Why Do Large Language Models Hallucinate? Definitions, Causes, and Mitigation Strategies

This article defines hallucination in LLMs as a failure of faithfulness or factualness, explores data‑level and model‑level origins, reviews reference‑based and reference‑free evaluation metrics, and surveys current research on data‑centric and model‑centric mitigation techniques along with future directions.

Mitigationevaluationfactuality
0 likes · 16 min read
Why Do Large Language Models Hallucinate? Definitions, Causes, and Mitigation Strategies
DataFunTalk
DataFunTalk
Aug 11, 2023 · Artificial Intelligence

Multimodal Dialogue Large Model mPLUG-Owl: Technology, Applications, and Evaluation

mPLUG-Owl is a modular multimodal dialogue large model from Alibaba DAMO Academy that builds on the mPLUG series, offering advanced image, video, OCR, and multilingual capabilities, with extensive evaluations showing superior performance over MiniGPT‑4, LLaVA, and other multimodal LLMs across various tasks.

Multimodal AIevaluationmPLUG-Owl
0 likes · 17 min read
Multimodal Dialogue Large Model mPLUG-Owl: Technology, Applications, and Evaluation
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Jul 24, 2023 · Artificial Intelligence

Comprehensive Survey of Large Language Models: History, Key Technologies, Resources, and Future Directions

This article provides a detailed overview of large language models (LLMs), tracing their evolution from statistical and neural language models to modern pre‑trained transformers, discussing scaling, training, adaptation, utilization, evaluation methods, available resources, and outlining current challenges and future research directions.

Model ScalingPre‑trainingPrompt engineering
0 likes · 26 min read
Comprehensive Survey of Large Language Models: History, Key Technologies, Resources, and Future Directions
DataFunSummit
DataFunSummit
May 4, 2023 · Artificial Intelligence

LLM Ranking Arena: Elo‑Based Competitive Evaluation of Open‑Source Chatbots

A recent study by the LMSYS organization introduces an Elo‑rated, 1v1 battle arena for large language models, ranking open‑source chatbots like Vicuna, Koala, and ChatGLM, while discussing the limitations of traditional benchmarks and the advantages of crowd‑sourced, scalable evaluation.

AI benchmarkingChatbot ArenaElo Rating
0 likes · 7 min read
LLM Ranking Arena: Elo‑Based Competitive Evaluation of Open‑Source Chatbots
Architect
Architect
Apr 9, 2023 · Artificial Intelligence

Evaluating the Commonsense Knowledge and Reasoning Capabilities of ChatGPT and Other Large Language Models

This study systematically evaluates ChatGPT and other large language models on their ability to answer commonsense questions, assess their knowledge awareness, and utilize generated knowledge for reasoning, revealing strong QA performance but notable gaps in social and temporal commonsense and in leveraging contextual knowledge.

ChatGPTNLPcommonsense reasoning
0 likes · 20 min read
Evaluating the Commonsense Knowledge and Reasoning Capabilities of ChatGPT and Other Large Language Models
Programmer DD
Programmer DD
Apr 9, 2023 · Artificial Intelligence

How Does Alibaba’s Tongyi Qianwen Compare to ChatGPT? A Hands‑On Evaluation

This article reviews Alibaba’s Tongyi Qianwen large‑language model by testing its self‑introduction, code generation, literary creation, mathematical reasoning, Chinese language understanding, and casual chatting abilities, summarizing strengths, weaknesses, and overall performance compared with other LLMs.

Chinese LanguageCode Generationartificial intelligence
0 likes · 7 min read
How Does Alibaba’s Tongyi Qianwen Compare to ChatGPT? A Hands‑On Evaluation
DataFunSummit
DataFunSummit
Mar 19, 2023 · Artificial Intelligence

Complex Question Answering Evaluation of ChatGPT

This paper presents a large‑scale evaluation of ChatGPT on knowledge‑base complex question answering, introducing a feature‑driven multi‑label annotation framework and CheckList‑based functional, robustness, and controllability tests, and comparing its performance with other LLMs across multiple English and multilingual datasets.

ChatGPTComplex QAchain-of-thought
0 likes · 25 min read
Complex Question Answering Evaluation of ChatGPT
Model Perspective
Model Perspective
Nov 6, 2022 · Fundamentals

Unlock Objective Decision-Making with the Entropy Weight Method

The Entropy Weight Method (EWM) offers an objective, data‑driven way to calculate indicator weights by measuring information entropy, avoiding subjective bias and improving the reliability of multi‑criteria evaluations across fields such as water quality and resource management.

decision makingentropy weight methodevaluation
0 likes · 4 min read
Unlock Objective Decision-Making with the Entropy Weight Method
DataFunSummit
DataFunSummit
Sep 5, 2022 · Artificial Intelligence

Comprehensive Evaluation of Long‑Audio Speech‑to‑Text Services from Major Cloud Providers

This article presents a systematic, multi‑dimensional benchmark of six leading cloud speech‑recognition platforms—Alibaba Cloud, Tencent Cloud, iFlytek, Baidu Cloud, Huawei Cloud, and Microsoft Azure—using a 22.6‑hour, 81‑file Mandarin dataset, scoring with the CORR metric and SCTK tool, and discusses each provider's workflow, strengths, pitfalls, and cost.

AICloud ServicesSCTK
0 likes · 15 min read
Comprehensive Evaluation of Long‑Audio Speech‑to‑Text Services from Major Cloud Providers
DataFunSummit
DataFunSummit
Aug 20, 2022 · Information Security

Content Risk Control Industry Overview and Evaluation System

The article reviews the development background of the digital economy‑driven content risk control industry, examines current content moderation technologies and challenges, describes the establishment of a content technology promotion alliance, outlines its research directions and evaluation standards, and includes a Q&A on regulatory collaboration.

Standardsartificial intelligencecontent moderation
0 likes · 16 min read
Content Risk Control Industry Overview and Evaluation System
Model Perspective
Model Perspective
Jul 2, 2022 · Operations

Top Resources for Evaluation & Optimization Models – A Curated Guide

This article compiles and categorizes recent model‑related publications, offering a comprehensive list of evaluation‑model resources—including concepts, preprocessing techniques, weighting methods, and various algorithms—and optimization‑model references covering linear and integer programming, graph theory, network flows, and meta‑heuristics.

Linear ProgrammingModelingOperations
0 likes · 4 min read
Top Resources for Evaluation & Optimization Models – A Curated Guide
Architecture and Beyond
Architecture and Beyond
May 1, 2022 · R&D Management

Effective Questioning Techniques for Promotion Review Panels

The article outlines systematic questioning strategies for judges in corporate promotion defenses, detailing how to clarify definitions, probe processes, assess difficulty, evaluate big‑picture thinking, explore methodology, and link technical work to business value, thereby ensuring fair and insightful evaluations.

Career DevelopmentR&D managementevaluation
0 likes · 13 min read
Effective Questioning Techniques for Promotion Review Panels
DataFunTalk
DataFunTalk
Oct 5, 2021 · Artificial Intelligence

From Technology to Experience: Vivo Machine Translation Deployment Practice

This article presents a comprehensive guide to deploying machine translation at Vivo, covering business analysis, algorithm choices beyond standard NMT, language detection challenges, data collection and cleaning, scientific evaluation methods, and engineering optimizations to deliver a seamless user experience.

AIEngineeringNMT
0 likes · 20 min read
From Technology to Experience: Vivo Machine Translation Deployment Practice
IT Architects Alliance
IT Architects Alliance
Jul 26, 2021 · R&D Management

How to Conduct a Comprehensive Architecture Evaluation: A Step-by-Step Guide

This article outlines a thorough methodology for evaluating software, hardware, and overall system architectures, detailing assessment criteria, a five‑stage evaluation process, quality‑assurance measures, and best‑practice checkpoints to ensure high availability, scalability, security, and cost‑effectiveness of complex engineering projects.

System Designarchitectureassessment
0 likes · 12 min read
How to Conduct a Comprehensive Architecture Evaluation: A Step-by-Step Guide
Liulishuo Tech Team
Liulishuo Tech Team
Jul 7, 2021 · Frontend Development

Evaluation and Evolution of Mini‑Program Development Frameworks for Frontend Teams

This article reviews the background, key considerations, architectural principles, evolution, performance comparison, and a customized solution for building mini‑programs using frameworks such as WePY, Taro, and UniApp, highlighting cross‑platform support, TypeScript integration, and development experience improvements.

Frameworkevaluationperformance
0 likes · 12 min read
Evaluation and Evolution of Mini‑Program Development Frameworks for Frontend Teams
Efficient Ops
Efficient Ops
Apr 16, 2021 · Operations

How Anxin Securities Achieved Top RPA Maturity: Insights from China’s First RPA Standard Evaluation

Anxin Securities’ RPA Unified Management Platform earned the highest 3+ maturity rating at China’s inaugural RPA standard assessment, showcasing extensive automation across finance, operations, and disaster recovery, while outlining future SmartRPA initiatives and AI‑driven enhancements for digital transformation.

AI integrationRPAevaluation
0 likes · 10 min read
How Anxin Securities Achieved Top RPA Maturity: Insights from China’s First RPA Standard Evaluation
21CTO
21CTO
Feb 26, 2021 · Artificial Intelligence

Why One Metric Isn't Enough: Multi‑Dimensional Evaluation of Recommendation Systems

The article explains why relying on a single metric like click‑through rate is insufficient for recommendation systems, and outlines a comprehensive, multi‑dimensional evaluation framework that combines business indicators, user behavior metrics, and algorithmic performance measures such as recall, precision, and AUC.

AB testingAIAUC
0 likes · 10 min read
Why One Metric Isn't Enough: Multi‑Dimensional Evaluation of Recommendation Systems
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Feb 26, 2021 · Artificial Intelligence

Inside Toutiao's Transparent Real-Time Recommendation Engine

This article details how Toutiao's senior algorithm architect designs a transparent recommendation system, covering system overview, three-dimensional feature modeling, real-time training pipelines, recall strategies, content analysis, user tagging, evaluation methods, and content safety measures.

Content SafetyReal-time Trainingcontent analysis
0 likes · 17 min read
Inside Toutiao's Transparent Real-Time Recommendation Engine
21CTO
21CTO
Jan 11, 2021 · Artificial Intelligence

How to Build a Recommendation System from Scratch: Key Concepts and Strategies

This article explains the fundamentals of recommendation systems, covering data collection, user and content profiling, system architecture, algorithmic pipelines such as recall, filtering, ranking, and evaluation metrics, while also discussing practical challenges like echo chambers and long‑term user value.

algorithmevaluationmachine learning
0 likes · 16 min read
How to Build a Recommendation System from Scratch: Key Concepts and Strategies
NetEase Yanxuan Technology Product Team
NetEase Yanxuan Technology Product Team
Nov 27, 2020 · Product Management

How to Build Effective Decision‑Making Products: A Practical Blueprint

This article outlines a comprehensive framework for designing decision‑type products, covering their evolution stages, core elements of model‑data‑strategy, domain modeling techniques, data‑to‑knowledge transformation, business and process value, and a feedback‑driven decision loop with evaluation and simulation.

Business AnalyticsDecision Productsdata modeling
0 likes · 20 min read
How to Build Effective Decision‑Making Products: A Practical Blueprint
Programmer DD
Programmer DD
Oct 24, 2020 · Cloud Native

Should You Switch to Microservices? Evaluation Tips and Migration Steps

This article examines the fundamentals of monolithic and microservice architectures, outlines the advantages and drawbacks of each, provides criteria for deciding when to adopt microservices, and offers practical guidance on technical, talent, and organizational considerations for a successful migration.

architecturecloud-nativeevaluation
0 likes · 16 min read
Should You Switch to Microservices? Evaluation Tips and Migration Steps
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Oct 1, 2020 · Cloud Native

When Should You Adopt Microservices? A Practical Evaluation Guide

This article explores the fundamentals of monolithic and microservice architectures, assesses the benefits, costs, and risks of adopting microservices, and provides practical criteria—including business complexity, team size, and technical readiness—to help decide the optimal moment for migration.

BackendMicroservicescloud-native
0 likes · 16 min read
When Should You Adopt Microservices? A Practical Evaluation Guide
Top Architect
Top Architect
Sep 19, 2020 · Artificial Intelligence

Architecture and Evaluation of Toutiao's Large-Scale Recommendation System

The article details the end‑to‑end architecture of Toutiao's massive recommendation platform, covering system overview, content and user feature extraction, model training, recall strategies, evaluation methodology, and content safety mechanisms, while highlighting practical challenges and engineering solutions.

Content SafetyModel Trainingcontent analysis
0 likes · 18 min read
Architecture and Evaluation of Toutiao's Large-Scale Recommendation System
Sohu Tech Products
Sohu Tech Products
Sep 16, 2020 · Artificial Intelligence

Open-Domain Dialogue Systems: Current State, Challenges, and Future Directions

This article reviews the latest advances in open-domain dialogue systems, covering classification, end‑to‑end generation challenges, knowledge‑controlled generation, automated evaluation, large‑scale latent‑space models such as PLATO, and outlines future research directions for building more coherent and controllable conversational AI.

Dialogue Systemsevaluationknowledge grounding
0 likes · 14 min read
Open-Domain Dialogue Systems: Current State, Challenges, and Future Directions
21CTO
21CTO
Feb 18, 2020 · Artificial Intelligence

Inside Toutiao’s Real‑Time Recommendation Engine: Architecture, Features, and Evaluation

This article details Toutiao’s large‑scale recommendation system, explaining how it models content, user, and environment features, the variety of algorithms and real‑time training pipelines used, feature engineering categories, recall strategies, content analysis, user tagging, evaluation methods, and content‑safety mechanisms.

Content SafetyReal-time Trainingevaluation
0 likes · 18 min read
Inside Toutiao’s Real‑Time Recommendation Engine: Architecture, Features, and Evaluation
DataFunTalk
DataFunTalk
Aug 30, 2019 · Artificial Intelligence

TransFM: Integrating Translation-based Recommendation and Factorization Machines for Sequential Recommendation

This article reviews the TransFM model, which combines the translation‑based sequential recommendation approach (TransRec) with factorization machines (FM), explains its formulation, optimization via sequential Bayesian personalized ranking, and demonstrates its superior performance on Amazon and Google Local datasets compared with several baselines.

evaluationfactorization machinesmachine learning
0 likes · 8 min read
TransFM: Integrating Translation-based Recommendation and Factorization Machines for Sequential Recommendation
iQIYI Technical Product Team
iQIYI Technical Product Team
Jul 12, 2019 · Artificial Intelligence

Real-Time Evaluation System for Adaptive Bitrate (ABR) Algorithms and Controlled Bitrate Distribution

RESA is a real‑time evaluation platform that continuously tests multiple Adaptive Bitrate (ABR) algorithms on live user traffic, introduces a multi‑user QoE metric derived from viewing behavior, reveals trade‑offs between clarity and bandwidth, and proposes the RL‑based ABSbc algorithm to steer bitrate distribution and balance user experience with network cost.

ABRBandwidth ControlQoE
0 likes · 23 min read
Real-Time Evaluation System for Adaptive Bitrate (ABR) Algorithms and Controlled Bitrate Distribution
21CTO
21CTO
Jan 16, 2019 · Artificial Intelligence

Inside Toutiao’s Recommendation Engine: Architecture, Features, and Evaluation

This article provides a comprehensive overview of Toutiao’s recommendation system, detailing its three‑dimensional modeling of content, user, and context, the feature extraction pipeline, real‑time training infrastructure, user‑tag generation, evaluation methodology, and content‑safety mechanisms.

Content SafetyReal-time Trainingevaluation
0 likes · 18 min read
Inside Toutiao’s Recommendation Engine: Architecture, Features, and Evaluation
DataFunTalk
DataFunTalk
Jan 3, 2019 · Artificial Intelligence

Machine Learning and Recommendation System Practice

This article presents a comprehensive overview of applying machine learning to recommendation systems, covering fundamental challenges such as user cold‑start, precise interest modeling, collaborative filtering, and both offline and online evaluation methods, while illustrating concepts with numerous diagrams.

AIRecommendation Systemscold start
0 likes · 9 min read
Machine Learning and Recommendation System Practice
360 Quality & Efficiency
360 Quality & Efficiency
May 11, 2018 · Artificial Intelligence

Common Engineering Algorithms and Their Testing Methods

This article introduces the most commonly used algorithms in engineering—recommendation, optimization, estimation, and classification—explains their typical application scenarios, and discusses various testing methods and evaluation metrics such as offline experiments, user surveys, A/B testing, and performance indicators like accuracy, coverage, diversity, and robustness.

algorithmevaluationmachine learning
0 likes · 12 min read
Common Engineering Algorithms and Their Testing Methods
Efficient Ops
Efficient Ops
Feb 25, 2018 · Cloud Computing

Why Multi-Cloud Management Platforms Need Standards: Key Insights & Evaluation

Amid the rise of multi‑cloud strategies, China’s nascent multi‑cloud management platform market faces a lack of standards, prompting TrustCloud to launch the first domestic evaluation framework that assesses information authenticity, platform quality, and service completeness, with results to be revealed at the 2018 Cloud Computing Open‑Source Industry Conference.

Cloud ManagementIndustry standardscloud computing
0 likes · 6 min read
Why Multi-Cloud Management Platforms Need Standards: Key Insights & Evaluation
Architecture Digest
Architecture Digest
Jan 30, 2018 · Artificial Intelligence

Overview of Toutiao's Recommendation System: Architecture, Content Analysis, User Tagging, Evaluation, and Content Safety

This article presents a comprehensive overview of Toutiao's recommendation system, detailing its three‑dimensional modeling approach, real‑time training pipeline, feature engineering, content and user analysis techniques, evaluation methodology, and the extensive content‑safety mechanisms employed to ensure reliable and responsible information distribution.

Content Safetycontent analysisevaluation
0 likes · 19 min read
Overview of Toutiao's Recommendation System: Architecture, Content Analysis, User Tagging, Evaluation, and Content Safety
21CTO
21CTO
Jan 16, 2018 · Artificial Intelligence

Inside Toutiao’s Recommendation Engine: Architecture, Features, and Evaluation

This article provides a comprehensive overview of Toutiao's recommendation system, covering its three‑dimensional modeling approach, feature engineering, real‑time training pipeline, recall strategies, user‑tag generation, evaluation methodology, and content‑safety mechanisms.

Content SafetyReal-time Trainingevaluation
0 likes · 18 min read
Inside Toutiao’s Recommendation Engine: Architecture, Features, and Evaluation
Architecture Digest
Architecture Digest
Sep 15, 2017 · Artificial Intelligence

Overview of Recommendation Systems: Goals, Methods, Architecture, and Practical Considerations

This article explains the objectives of recommendation systems, compares popular recommendation approaches, details the components and algorithms of personalized recommendation pipelines, and discusses practical challenges such as real‑time processing, freshness, cold‑start, diversity, content quality, and surprise handling.

Real-Timecold startdata pipeline
0 likes · 15 min read
Overview of Recommendation Systems: Goals, Methods, Architecture, and Practical Considerations
Baidu Intelligent Testing
Baidu Intelligent Testing
Sep 6, 2017 · Product Management

Understanding User Satisfaction Models and How to Build Them

The article explains what a user satisfaction model is, why it matters for product evaluation, and outlines a step‑by‑step methodology—including defining dimensions, collecting questionnaire data, applying statistical techniques, creating a two‑dimensional evaluation matrix, and deriving actionable improvement plans—to quantitatively assess and enhance user experience.

ModelingUX Researchevaluation
0 likes · 6 min read
Understanding User Satisfaction Models and How to Build Them
21CTO
21CTO
Mar 18, 2016 · Artificial Intelligence

10 Essential Tips for Building High‑Performance Intelligent Recommendation Systems

This article outlines ten practical key points—including leveraging explicit and implicit feedback, hybridizing algorithms, handling temporal and geographic factors, exploiting social ties, solving cold‑start issues, optimizing presentation, defining clear metrics, ensuring real‑time updates, and scaling big‑data processing—to help engineers design effective intelligent recommendation systems.

cold startdata miningevaluation
0 likes · 18 min read
10 Essential Tips for Building High‑Performance Intelligent Recommendation Systems