Git Product home page Git Product logo

HuiyongLv's Projects

aggcn icon aggcn

Attention Guided Graph Convolutional Networks for Relation Extraction (authors' PyTorch implementation for the ACL19 paper)

attention-rank-collapse icon attention-rank-collapse

[ICML 2021 Oral] We show pure attention suffers rank collapse, and how different mechanisms combat it.

bert icon bert

TensorFlow code and pre-trained models for BERT

bert-bilstm-crf-ner icon bert-bilstm-crf-ner

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

casrel icon casrel

A Novel Cascade Binary Tagging Framework for Relational Triple Extraction. Accepted by ACL 2020.

conmask icon conmask

ConMask model described in paper Open-world Knowledge Graph Completion.

curriculum_learning icon curriculum_learning

Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Weinshall (ICML 2019)

dev-sidecar icon dev-sidecar

开发者边车,github打不开,github加速,git clone加速,git release下载加速,stackoverflow加速

dgl icon dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

docred icon docred

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

dsner icon dsner

Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning

gain icon gain

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

gp-gnn icon gp-gnn

Code and dataset of ACL2019 Paper: Graph Neural Networks with Generated Parameters for Relation Extraction.

hrl-re icon hrl-re

Joint Relation Extraction with Hierarchical Reinforcement Learning

mega icon mega

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

mkgformer icon mkgformer

Code for the SIGIR 2022 paper "Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion."

multihead_joint_entity_relation_extraction icon multihead_joint_entity_relation_extraction

Implementation of our papers Joint entity recognition and relation extraction as a multi-head selection problem (Expert Syst. Appl, 2018) and Adversarial training for multi-context joint entity and relation extraction (EMNLP, 2018).

nary-grn icon nary-grn

Code regarding to our paper "N-ary Relation Extraction using Graph State LSTM"

onerel icon onerel

The source code of the paper "OneRel: Joint Entity and Relation Extraction with One Module in One Step"

pcnn-nmar icon pcnn-nmar

NAACL 2019 "Structured Minimally Supervised Learning for Neural Relation Extraction"

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.