HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

GBBS: Graph Based Benchmark Suite

Embedding billion-scale networks accurately in one hour (TKDE paper 2023)

Must-read papers on graph neural networks (GNN)

A curated list of papers and resources based on "Large Language Models on Graphs: A Comprehensive Survey" (TKDE)

A collection of AWESOME things about Graph-Related LLMs.

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

Generate embeddings from large-scale graph-structured data.

LeetCode刷题记录与面试整理

Explore the web in parallel on thousands of machines

URL shortening service written in Go and React

👁 Vision : Model 4: GoogLeNet : Image Classification