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Jinqing Lee's Projects

abstractive-summarization icon abstractive-summarization

Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.

albert_pytorch icon albert_pytorch

A Lite Bert For Self-Supervised Learning Language Representations

albert_zh icon albert_zh

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型

articlepairmatching icon articlepairmatching

The code of ACL 2019 paper: Matching Article Pairs with Graphical Decomposition and Convolutions

bert icon bert

TensorFlow code and pre-trained models for BERT

chineseglue icon chineseglue

Language Understanding Evaluation benchmark for Chinese: datasets, baselines, pre-trained models,corpus and leaderboard

co-teaching icon co-teaching

NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

daily-paper-reading-record icon daily-paper-reading-record

This repository is created for recording the paper I read every day, so as to facilitate my review and push myself to learn.

fastbert icon fastbert

对ACL2020 FastBERT论文的复现,论文地址:https://arxiv.org/pdf/2004.02178.pdf

figer icon figer

Fine-Grained Entity Recognizer

hierarchical-typing icon hierarchical-typing

Code and Data for all experiments from our ACL 2018 paper "Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking"

ifetel icon ifetel

Improving Fine-grained Entity Typing with Entity Linking

knet icon knet

Neural Entity Typing with Knowledge Attention

mt-dnn icon mt-dnn

Multi-Task Deep Neural Networks for Natural Language Understanding

paper-reading icon paper-reading

Paper reading list in natural language processing, including dialogue system, text summarization, topic modeling, etc.

pygat icon pygat

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

teamviewer-5min icon teamviewer-5min

Mac/Windows TeamViewer 破解版,解除被检测出商业用途限制(5 min)

transformers icon transformers

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

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