Pinned Repositories
Awesome-Graph-LLM
A collection of AWESOME things about Graph-Related LLMs.
Awesome-LLMs-in-Graph-tasks
A curated collection of research papers exploring the utilization of LLMs for graph-related tasks.
CQA_EntityLinking
Code for IJCAI2022 "Community Question Answering Entity Linking via Leveraging Auxiliary Data"
CQAEL_MindSpore
MindSpore framework implementation for CQA Entity Linking
fact_triple_extraction
使用句法依存分析抽取事实三元组
gitexamples
ML-NLP
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
nlp-competitions-list-review
复盘所有NLP比赛的TOP方案，只关注NLP比赛，持续更新中！
OneForAll
A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.
yhLeeee.github.io
homepage
yhLeeee's Repositories
yhLeeee/Awesome-LLMs-in-Graph-tasks
A curated collection of research papers exploring the utilization of LLMs for graph-related tasks.
yhLeeee/CQA_EntityLinking
Code for IJCAI2022 "Community Question Answering Entity Linking via Leveraging Auxiliary Data"
yhLeeee/Awesome-Graph-LLM
A collection of AWESOME things about Graph-Related LLMs.
yhLeeee/nlp-competitions-list-review
复盘所有NLP比赛的TOP方案，只关注NLP比赛，持续更新中！
yhLeeee/OneForAll
A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.
yhLeeee/PysparkTest
借助pv、uv，即网页点击数据中的点击量和用户访问量来练习spark
yhLeeee/CQAEL_MindSpore
MindSpore framework implementation for CQA Entity Linking
yhLeeee/fact_triple_extraction
使用句法依存分析抽取事实三元组
yhLeeee/gitexamples
yhLeeee/ML-NLP
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
yhLeeee/yhLeeee.github.io
homepage
yhLeeee/Knowledge-Graph-Tutorials-and-Papers
Insightful Tutorials and Papers about Knowledge Graphs
yhLeeee/LaTeX-template-phd-thesis-proposal
LaTeX Template for OIST PhD Thesis Proposal
yhLeeee/LLaMA2-Accessory
An Open-source Toolkit for LLM Development
yhLeeee/lyh-homework
yhLeeee/Machine-Learning-Lab---6CS4-22
Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers the theory and practical algorithms for machine learning from a variety of perspectives. We cover topics such as FIND-S, Candidate Elimination Algorithm, Decision tree (ID3 Algorithm), Backpropagation Algorithm, Naïve Bayesian classifier, Bayesian Network, k-Means Algorithm, k-Nearest Neighbour Algorithm, Locally Weighted Regression Algorithm.
yhLeeee/NKThesis
南开大学硕士毕业论文/博士论文模板 (Latex Template for Nankai University)
yhLeeee/PURE
NAACL'2021: A Frustratingly Easy Approach for Entity and Relation Extraction https://arxiv.org/abs/2010.12812
yhLeeee/research-proposal-template
LaTeX template to outline and draft academic papers (or theses) in Computer Science (in English and German language)
yhLeeee/rng-kbqa
yhLeeee/scala-java-maven1
基于maven依赖，利用scala编写spark，打包jar
yhLeeee/tensorflow_practice
tensorflow实战练习，包括强化学习、推荐系统、nlp等