zhanglangJD

Pinned Repositories

AdaTask
AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning. AAAI, 2023.
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adv_hsc_moe
code for the paper "Adversarial Mixture Of Experts with Category Hierarchy Soft Constraint"
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aes_msl_mtl
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AI-RecommenderSystem
该仓库尝试整理推荐系统领域的一些经典算法模型
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AIM
AIM: Automatic Interaction Machine for Click-Through Rate Prediction
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AITM-torch
Pytorch implementation of Adaptive Information Transfer Multi-task (AITM)
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AlgorithmMarkdown
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Awesome-AIGC
AIGC资料汇总学习，持续更新......
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Awesome-Chinese-LLM
整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。
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ConcreteDropout
Concrete Dropout implementation for Tensorflow 2.0 and PyTorch
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zhanglangJD's Repositories

zhanglangJD/AdaTask
AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning. AAAI, 2023.
Language:Python00
zhanglangJD/Awesome-AIGC
AIGC资料汇总学习，持续更新......
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zhanglangJD/Awesome-Chinese-LLM
整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。
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zhanglangJD/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
zhanglangJD/Awesome-LLM
Awesome-LLM: a curated list of Large Language Model
zhanglangJD/Awesome-Multi-Task-Learning
An up-to-date list of works on Multi-Task Learning
zhanglangJD/awesome-pretrained-chinese-nlp-models
Awesome Pretrained Chinese NLP Models，高质量中文预训练模型&大模型&多模态模型&大语言模型集合
zhanglangJD/ChatSD
ChatSD is designed to make image generation tasks easily
zhanglangJD/DecryptPrompt
总结Prompt&LLM论文，开源数据&模型，AIGC应用
zhanglangJD/Deep-Learning-for-Causal-Inference
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.
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zhanglangJD/DeepMatch
A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.
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zhanglangJD/EasyRec
A framework for large scale recommendation algorithms.
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zhanglangJD/FDN
Source code for paper: Feature Decomposition for Reducing Negative Transfer: A Novel Multi-task Learning Method for Recommender System
zhanglangJD/fun-rec
推荐系统中文教程
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zhanglangJD/FuxiCTR
A configurable, tunable, and reproducible library for CTR prediction
Language:Python
zhanglangJD/generative-recommenders
Repository hosting code used to reproduce results in "Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152).
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zhanglangJD/HAMUR
Code implementation of HAMUR: Hyper Adapter for Multi-Domain Recommendation in CIKM‘2023
zhanglangJD/HiNet
Source code for paper: HiNet: Novel Multi-Scenario & Multi-Task Learning with Hierarchical Information Extraction
zhanglangJD/LLMsPracticalGuide
A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)
zhanglangJD/mmn
Masked Multi-Domain Network
zhanglangJD/nann
A flexible, high-performance framework for large-scale retrieval problems based on TensorFlow.
zhanglangJD/PracticalGuidetoRecSys
《互联网大厂推荐算法实战》资料库
zhanglangJD/rec_now
recommend now (rec_now) 是一个推荐算法的基础库，目的在于简化推荐模型的开发。本项目基于tensorflow2和python3实现，兼容使用tensorflow1.x API的[无量训练框架](https://git.woa.com/deep_learning_framework/NumerousTensorFlow)，并在生产环境中得到了充分验证。其中，基于in-batch方式计算pairwise的方式，已经在QQ浏览器信息流的精排、粗排、召回排序等环节得到了广泛应用，并使得在线GAUC指标提升1%以上。
Language:Python
zhanglangJD/RecSysPapers
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.
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zhanglangJD/reginx
Build a recommendation system from scratch
zhanglangJD/SATrans
The source code for our paper "Scenario-Adaptive Feature Interaction for Click-Through Rate Prediction" (accepted by KDD2023 Applied Science Track), which proposes a model for Multi-Scenario/Multi-Domain Recommendation.
zhanglangJD/stable-diffusion-webui
Stable Diffusion web UI
zhanglangJD/the-algorithm
Source code for Twitter's Recommendation Algorithm
zhanglangJD/torch-rechub
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
zhanglangJD/tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.