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Essen's Projects

active-ner icon active-ner

Bayesian Deep Active Learning for Named entity recognition (NER)

articlepairmatching icon articlepairmatching

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

cnn-dailymail icon cnn-dailymail

Code to obtain the CNN / Daily Mail dataset (non-anonymized) for summarization

docred icon docred

Dataset and codes for ACL 2019 DocRED: A Large-Scale Document-Level Relation Extraction Dataset.

docunet icon docunet

Source code and dataset for the IJCAI 2021 paper "Document-level Relation Extraction as Semantic Segmentation".

fast_abs_rl icon fast_abs_rl

Code for ACL 2018 paper: "Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting. Chen and Bansal"

gain icon gain

Source code for EMNLP 2020 paper: Double Graph Based Reasoning for Document-level Relation Extraction

hice icon hice

Pytorch Code for ACL'19 "Few-Shot Representation Learning for Out-Of-Vocabulary Words"

lace icon lace

The official implementation of the paper "Document-Level Relation Extraction with Relation Correlation Enhancement" (ICONIP 2023)

lsan icon lsan

Label-Specific Document Representation for Multi-Label Text Classification

lsr icon lsr

Pytorch Implementation of our ACL 2020 Paper "Reasoning with Latent Structure Refinement for Document-Level Relation Extraction"

mega icon mega

Code for ACM MM 2021 Paper "Multimodal Relation Extraction with Efficient Graph Alignment".

ml-gcn icon ml-gcn

PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.

ml_decoder icon ml_decoder

Official PyTorch implementation of "ML-Decoder: Scalable and Versatile Classification Head" (2021)

ncrl icon ncrl

Implementation of None Class Ranking Loss for Document-Level Relation Extraction

opennmt-py icon opennmt-py

Open Source Neural Machine Translation in PyTorch

presumm icon presumm

code for EMNLP 2019 paper Text Summarization with Pretrained Encoders

pygcn icon pygcn

Graph Convolutional Networks in PyTorch

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