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The implementation of paper "Preference Diffusion for Recommendation" published in ICLR 2025.
TorchCFM: a Conditional Flow Matching library
A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.
Diffusion Models, Recommender Systems, Recommendation, Diff4Rec
个人实现pytorch高级编程，包括基本知识、卷积神经网络、循环神经网络、生成对抗、模型部署和分布式训练（2022)
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
[KDD'24] Official PyTorch implementation for "Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation".
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Repo for Pre-trained Recommender Systems: A Causal Debias Perspective in The 17th ACM International Conference on Web Search and Data Mining (WSDM)
Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".
A unified, comprehensive and efficient recommendation library
This is a library built upon RecBole for cross-domain recommendation algorithms
Pytorch implementation of Transfusion, "Predict the Next Token and Diffuse Images with One Multi-Modal Model", from MetaAI
A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputatio…
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention, AAAI-24
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程
Retrieval and Retrieval-augmented LLMs
This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily a…
Overcoming catastrophic forgetting with hard attention to the task