Pytorch implementation of Supporting Clustering with Contrastive Learning, NAACL 2021

Related tags

Deep Learningsccl
Overview

Supporting Clustering with Contrastive Learning

SCCL (NAACL 2021) Dejiao Zhang, Feng Nan, Xiaokai Wei, Shangwen Li, Henghui Zhu, Kathleen McKeown, Ramesh Nallapati, Andrew Arnold, and Bing Xiang.

Requirements

Datasets:

In additional to the original data, SCCL requires a pair of augmented data for each instance. See our paper for details.

Dependencies:

python==3.6. 
pytorch==1.6.0. 
sentence-transformers==0.3.8. 
transformers==3.3.0. 
tensorboardX==2.1.  

To run the code:

1. put your dataset in the folder "./datasamples"  # for some license issue, we are not able to release the dataset now, we'll release the datasets asap
2. bash ./scripts/run.sh # you need change the dataset info and results path accordingly

Citation:

@inproceedings{zhang-etal-2021-supporting,
title = "Supporting Clustering with Contrastive Learning",
author = "Zhang, Dejiao  and Nan, Feng  and Wei, Xiaokai  and
  Li, Shang-Wen  and Zhu, Henghui  and McKeown, Kathleen  and
  Nallapati, Ramesh  and Arnold, Andrew O.  and Xiang, Bing",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.naacl-main.427",
pages = "5419--5430",
abstract = " ",}
An atmospheric growth and evolution model based on the EVo degassing model and FastChem 2.0

EVolve Linking planetary mantles to atmospheric chemistry through volcanism using EVo and FastChem. Overview EVolve is a linked mantle degassing and a

Pip Liggins 2 Jan 17, 2022
Unofficial PyTorch Implementation of Multi-Singer

Multi-Singer Unofficial PyTorch Implementation of Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale Corpus. Requirements See re

SunMail-hub 123 Dec 28, 2022
X-modaler is a versatile and high-performance codebase for cross-modal analytics.

X-modaler X-modaler is a versatile and high-performance codebase for cross-modal analytics. This codebase unifies comprehensive high-quality modules i

910 Dec 28, 2022
Compare outputs between layers written in Tensorflow and layers written in Pytorch

Compare outputs of Wasserstein GANs between TensorFlow vs Pytorch This is our testing module for the implementation of improved WGAN in Pytorch Prereq

Hung Nguyen 72 Dec 20, 2022
🐦 Quickly annotate data from the comfort of your Jupyter notebook

🐦 pigeon - Quickly annotate data on Jupyter Pigeon is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort

Anastasis Germanidis 647 Jan 05, 2023
SigOpt wrappers for scikit-learn methods

SigOpt + scikit-learn Interfacing This package implements useful interfaces and wrappers for using SigOpt and scikit-learn together Getting Started In

SigOpt 73 Sep 30, 2022
EgGateWayGetShell py脚本

EgGateWayGetShell_py 免责声明 由于传播、利用此文所提供的信息而造成的任何直接或者间接的后果及损失,均由使用者本人负责,作者不为此承担任何责任。 使用 python3 eg.py urls.txt 目标 title:锐捷网络-EWEB网管系统 port:4430 漏洞成因 ?p

榆木 61 Nov 09, 2022
Simple Tensorflow implementation of "Adaptive Convolutions for Structure-Aware Style Transfer" (CVPR 2021)

AdaConv — Simple TensorFlow Implementation [Paper] : Adaptive Convolutions for Structure-Aware Style Transfer (CVPR 2021) Note This repository does no

Junho Kim 26 Nov 18, 2022
Hierarchical Time Series Forecasting with a familiar API

scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work

Carlo Mazzaferro 204 Dec 17, 2022
Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)

To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/

32 Dec 26, 2022
Official implementation of EdiTTS: Score-based Editing for Controllable Text-to-Speech

EdiTTS: Score-based Editing for Controllable Text-to-Speech Official implementation of EdiTTS: Score-based Editing for Controllable Text-to-Speech. Au

Neosapience 98 Dec 25, 2022
Incorporating Transformer and LSTM to Kalman Filter with EM algorithm

Deep learning based state estimation: incorporating Transformer and LSTM to Kalman Filter with EM algorithm Overview Kalman Filter requires the true p

zshicode 57 Dec 27, 2022
Aircraft design optimization made fast through modern automatic differentiation

Aircraft design optimization made fast through modern automatic differentiation. Plug-and-play analysis tools for aerodynamics, propulsion, structures, trajectory design, and much more.

Peter Sharpe 394 Dec 23, 2022
LibFewShot: A Comprehensive Library for Few-shot Learning.

LibFewShot Make few-shot learning easy. Supported Methods Meta MAML(ICML'17) ANIL(ICLR'20) R2D2(ICLR'19) Versa(NeurIPS'18) LEO(ICLR'19) MTL(CVPR'19) M

<a href=[email protected]&L"> 603 Jan 05, 2023
FindFunc is an IDA PRO plugin to find code functions that contain a certain assembly or byte pattern, reference a certain name or string, or conform to various other constraints.

FindFunc: Advanced Filtering/Finding of Functions in IDA Pro FindFunc is an IDA Pro plugin to find code functions that contain a certain assembly or b

213 Dec 17, 2022
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

Utkarsh Agiwal 1 Feb 03, 2022
Distributing reference energies for SMIRNOFF implementations

Warning: This code is currently experimental and under active development. Is it not yet suitable for distribution or use as reference implementation.

Open Force Field Initiative 1 Dec 07, 2021
Group project for MFIN7036. Our goal is to predict firm profitability with text-based competition measures.

NLP_0-project Group project for MFIN7036. Our goal is to predict firm profitability with text-based competition measures1. We are a "democratic" and c

3 Mar 16, 2022
CondenseNet V2: Sparse Feature Reactivation for Deep Networks

CondenseNetV2 This repository is the official Pytorch implementation for "CondenseNet V2: Sparse Feature Reactivation for Deep Networks" paper by Le Y

Haojun Jiang 74 Dec 12, 2022
The official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness.

This repository is the official implementation of A Unified Game-Theoretic Interpretation of Adversarial Robustness. Requirements pip install -r requi

Jie Ren 17 Dec 12, 2022