Popular GitHub Repositories for Diverse Recsys

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

LightSeq: A High Performance Library for Sequence Processing and Generation

AGiXT is a dynamic AI Agent Automation Platform that seamlessly orchestrates instruction management and complex task execution across diverse AI providers. Combining adaptive memory, smart features, and a versatile plugin system, AGiXT delivers efficient and comprehensive AI solutions.

Large-scale, Informative, and Diverse Multi-round Chat Data (and Models)

Mastering Diverse Domains through World Models

A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

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.

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation (NeurIPS 2023 Spotlight)

Survey: A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.

HumanML3D: A large and diverse 3d human motion-language dataset.

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

[ICLR24] Official implementation of the paper “MagicDrive: Street View Generation with Diverse 3D Geometry Control”

Next RecSys Library

Collective Knowledge (CK), Collective Mind (CM) and Common Metadata eXchange (CMX): community-driven projects to facilitate collaborative and reproducible research and to learn how to run AI, ML, and other emerging workloads more efficiently and cost-effectively across diverse models, datasets, software, and hardware using MLPerf.

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

[ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the diverse strengths of multiple open-source LLMs. LLM-Blender cut the weaknesses through ranking and integrate the strengths through fusing generation to enhance the capability of LLMs.

RTP-LLM: Alibaba's high-performance LLM inference engine for diverse applications.

key Deep Learning engineering tricks in recsys

[ICCV 2021 Oral] PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers