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jboru's Projects

freebase-setup icon freebase-setup

The last data dump of Freebase with introductory explanation of its schema

gnn4nlp-papers icon gnn4nlp-papers

A list of recent papers about Graph Neural Network methods applied in NLP areas.

gpt4all icon gpt4all

gpt4all: a chatbot trained on a massive collection of clean assistant data including code, stories and dialogue

graph4nlp icon graph4nlp

Graph4nlp is the library for the easy use of Graph Neural Networks for NLP

graph_neural_net icon graph_neural_net

Graph Convolutional Networks, Graph Attention Networks, Gated Graph Neural Net, Mixhop

greaselm icon greaselm

GreaseLM: Graph REASoning Enhanced Language Models

hdsa-dialog icon hdsa-dialog

Code and Data for ACL 2019 "Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention"

homemade-machine-learning icon homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

hykas-cskg icon hykas-cskg

Code for the paper "Knowledge-driven Data Construction for Zero-shot Evaluation in Commonsense Question Answering" (AAAI 2021)

intro_dgm icon intro_dgm

An Introduction to Deep Generative Modeling: Examples

ioi icon ioi

Tensorflow implementation for IOI model

jointgt icon jointgt

Codes for our paper "JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs" (ACL 2021 Findings)

k-bert icon k-bert

Source code of K-BERT (AAAI2020)

kbqa icon kbqa

Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals. WSDM 2021.

keras-bert-kbqa icon keras-bert-kbqa

Keras solution of simple Knowledge-Based QA task with Pretrained Language Model: supporting BERT/RoBERTa/ALBERT

kgpt icon kgpt

Code and Data for EMNLP2020 Paper "KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation"

leaderboard icon leaderboard

You can find the most recent KGQA benchmark numbers from publications here.

leeml-notes icon leeml-notes

李宏毅《机器学习》笔记,在线阅读地址:https://datawhalechina.github.io/leeml-notes

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