negative-sampling

🎯 Task-oriented embedding tuning for BERT, CLIP, etc.

基于Pytorch和torchtext的自然语言处理深度学习框架。

This repository collects 100 papers related to negative sampling methods.

Extremely simple and fast word2vec implementation with Negative Sampling + Sub-sampling

Reinforced Negative Sampling over Knowledge Graph for Recommendation, WWW2020

SimXNS is a research project for information retrieval. This repo contains official implementations by MSRA NLC team.

MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021

⚡️ Implementation of TRON: Transformer Recommender using Optimized Negative-sampling, accepted at ACM RecSys 2023.

Embedding模型代码和学习笔记总结

[Paper][LREC-COLING 2024] Unleashing the Power of Imbalanced Modality Information for Multi-modal Knowledge Graph Completion

Implements various negative sampling techniques for learning knowledge graph embeddings

"SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation", WSDM 2025

Implementation of paper "Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval"

Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction

A PyTorch Implementation of the Skipgram Negative Sampling Word2Vec Model as Described in Mikolov et al.

This Machine Learning project deals with Coupon Recommendations based on Revenue Uplift

Course Materials (along with assignments) for Intro to NLP, done as a part for requirement of the course "Introduction to NLP" (course-code: CS7.401.S22) @ IIITH. Note: If you are cloning this or taking help of this repo, try to star the repo.

A Jax implementation of word2vec's skip-gram model with negative sampling as described in Mikolov et al., 2013

PyTorch implementation for " Conditional Negative Sampling for Contrastive Learning of Visual Representations" (https://arxiv.org/abs/2010.02037).

Cooperation of Retriever and Ranker Framework.