WSDM2022 "A Simple but Effective Bidirectional Extraction Framework for Relational Triple Extraction"

Last update: Dec 27, 2022

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Deep Learning BiRTE

Overview

BiRTE

WSDM2022 "A Simple but Effective Bidirectional Extraction Framework for Relational Triple Extraction"

Requirements

The main requirements are:

python 3.6
torch 1.4.0
tqdm
transformers == 2.8.0

Usage

Train and select the model

python run.py --dataset=WebNLG --train=train --batch_size=6

python run.py --dataset=WebNLG_star --train=train --batch_size=6

python run.py --dataset=NYT --train=train --batch_size=18

python run.py --dataset=NYT_star --train=train --batch_size=18

python run.py --dataset=NYT10 --train=train --batch_size=18

python run.py --dataset=NYT11 --train=train --batch_size=18

Evaluate on the test set

python run.py --dataset=WebNLG --train=test

python run.py --dataset=WebNLG_star --train=test

python run.py --dataset=NYT --train=test

python run.py --dataset=NYT_star --train=test

python run.py --dataset=NYT10 --train=test

python run.py --dataset=NYT11 --train=test

Owner

GitHub Repository

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WSDM2022 "A Simple but Effective Bidirectional Extraction Framework for Relational Triple Extraction"

Related tags

Overview

BiRTE

Requirements

Usage

Owner

Official PyTorch repo for JoJoGAN: One Shot Face Stylization

An interpreter for RASP as described in the ICML 2021 paper "Thinking Like Transformers"

It is an open dataset for object detection in remote sensing images.

Born-Infeld (BI) for AI: Energy-Conserving Descent (ECD) for Optimization

Build a small, 3 domain internet using Github pages and Wikipedia and construct a crawler to crawl, render, and index.

Implementation for Panoptic-PolarNet (CVPR 2021)

BED: A Real-Time Object Detection System for Edge Devices

Space Ship Simulator using python

A Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Training Data》

PyTorch implementation of the Value Iteration Networks (VIN) (NIPS '16 best paper)

EMNLP 2021 Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections

Road Crack Detection Using Deep Learning Methods

Code for "Hierarchical Skills for Efficient Exploration" HSD-3 Algorithm and Baselines

MassiveSumm: a very large-scale, very multilingual, news summarisation dataset

Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption

MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.

[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"

Object Database for Super Mario Galaxy 1/2.

[TOG 2021] PyTorch implementation for the paper: SofGAN: A Portrait Image Generator with Dynamic Styling.

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