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#Recommendation System

共 5 篇
tags Deep Reading 33 Paper Reading 24 Code Reading 16 Computer Vision 12 Generative AI 5 Recommendation System 5 3D Generation 4 Agentic RL 3
还有 96 个标签 →
Deep Learning 3 Diffusion Models 3 Engineering 3 Image-to-3D 3 Knowledge Graph 3 Reinforcement Learning 3 Text-to-3D 3 3D Scene Generation 2 3D Scene Synthesis 2 Asynchronous RL 2 Computer Graphics 2 Graphics 2 NeRF 2 Optimization 2 RAG 2 Ranking 2 Systems 2 Two-Tower 2 Workflow 2 YouTube 2 3D Assets 1 3D Gaussian Splatting 1 3D Reconstruction 1 3D Scene Editing 1 3D Scene Modeling 1 3D Vision 1 Agent Memory 1 AI 1 AI Agents 1 Alibaba 1 ANN 1 Authorization 1 CAD Alignment 1 CAD Retrieval 1 Claude Code 1 Codex 1 Cold Start 1 Content Provenance 1 Context Engineering 1 Credit Assignment 1 CTR Prediction 1 Cypher 1 Database Internals 1 DeepSeek 1 Einops 1 Fourier Convolution 1 Generative Models 1 Generative Recommenders 1 Git 1 Graph Database 1 Graphiti 1 HSTU 1 Hybrid Search 1 Image Inpainting 1 Image Watermarking 1 Knowledge Augmented Generation 1 LLM Inference 1 LLM Post-Training 1 LLM Reliability 1 Long-Horizon RL 1 Loss Landscape 1 Machine Learning 1 Meta 1 Multi-Task Learning 1 Multimodal LLM 1 Multitask Learning 1 Neo4j 1 Notes 1 OpenFGA 1 OpenSPG 1 Pose Estimation 1 Python 1 Qwen 1 ReBAC 1 Rectified Flow 1 Referring Segmentation 1 Search 1 Search Engine 1 Security 1 Semi-Autoregressive Generation 1 Sequential Recommendation 1 Single-view Reconstruction 1 Speculative Decoding 1 Survey 1 System Design 1 Tensor Programming 1 Theory 1 Training Systems 1 Tutorial 1 User Interest Modeling 1 Vector Search 1 Vespa 1 Visual Grounding 1 Works 1 Zanzibar 1 Zep 1

2026

2026.07

  1. SIM 论文精读：搜索式用户兴趣建模、终身行为序列与工业 CTR 预测

    精读阿里 SIM 如何通过两级搜索、用户行为树、长序列检索和实时预测系统改造，在 CTR 预测中建模最长 54000 的终身用户行为序列

    Deep ReadingPaper ReadingRecommendation System +4
2026.06

  1. Generative Recommenders 论文精读：HSTU、M-FALCON 与万亿参数推荐序列建模

    精读 Meta ICML 2024 Generative Recommenders 如何将推荐系统重构为序列生成问题，并通过 HSTU、Stochastic Length、M-FALCON 和 scaling law 支撑工业级部署

    Deep ReadingPaper ReadingRecommendation System +4

  2. Clippy 论文精读：多任务推荐排序模型的训练稳定性、损失发散与自适应更新裁剪

    精读 KDD 2023 Clippy 如何分析 YouTube 多任务排序模型训练不稳定问题，并用 Adagrad 更新裁剪提升大规模推荐模型稳定性

    Deep ReadingPaper ReadingRecommendation System +4

  3. YouTube DNN 推荐系统论文精读：双阶段召回排序、候选生成与观看时长优化

    精读 RecSys 2016 YouTube DNN 推荐系统如何用深度候选生成、排序模型、样本构造、特征工程和观看时长目标支撑大规模推荐

    Deep ReadingPaper ReadingRecommendation System +4

  4. 简单推荐算法实施指南：从冷启动弱监督到真实反馈闭环

    系统梳理推荐系统在缺少样本时如何通过内容先验、规则蒸馏、受控探索、曝光日志和双塔召回逐步建立稳定训练闭环

    Deep ReadingRecommendation SystemCold Start +4