Data augmentation for NLP, accepted at EMNLP 2021 Findings

Related tags

Deep Learningaeda_nlp
Overview

AEDA: An Easier Data Augmentation Technique for Text Classification

This is the code for the EMNLP 2021 paper AEDA: An Easier Data Augmentation Technique for Text Classification

The baseline code is for EDA: Easy Data Augmentation techniques for boosting performance on text classification tasks

Our augmentation code can be found in the code folder titled aeda.py. In addition, we also make available our train and test data which is in the data folder.

alt text

Citation

@misc{karimi2021aeda,
      title={AEDA: An Easier Data Augmentation Technique for Text Classification},
      author={Akbar Karimi and Leonardo Rossi and Andrea Prati},
      year={2021},
      eprint={2108.13230},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Model parallel transformers in Jax and Haiku

Mesh Transformer Jax A haiku library using the new(ly documented) xmap operator in Jax for model parallelism of transformers. See enwik8_example.py fo

Ben Wang 4.8k Jan 01, 2023
Datasets for new state-of-the-art challenge in disentanglement learning

High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co

NVIDIA Research Projects 37 May 26, 2022
IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL.

IJON SPACE EXPLORER IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL. Using only a small (usually one line) annotati

Chair for Sys­tems Se­cu­ri­ty 146 Dec 16, 2022
[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang

BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat

VITA 40 Dec 30, 2022
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021)

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

DavidHuang 126 Dec 30, 2022
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning (NeurIPS 2020) Introduction AdaShare is a novel and differentiable approach fo

94 Dec 22, 2022
This repository contains the implementation of the paper Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans

Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans This repository contains the implementation of the pap

Photogrammetry & Robotics Bonn 40 Dec 01, 2022
An implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks in PyTorch.

Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep

Yige-Li 84 Jan 04, 2023
NAACL'2021: Factual Probing Is [MASK]: Learning vs. Learning to Recall

OptiPrompt This is the PyTorch implementation of the paper Factual Probing Is [MASK]: Learning vs. Learning to Recall. We propose OptiPrompt, a simple

Princeton Natural Language Processing 150 Dec 20, 2022
Code release for "Making a Bird AI Expert Work for You and Me".

Making-a-Bird-AI-Expert-Work-for-You-and-Me Code release for "Making a Bird AI Expert Work for You and Me". arxiv (Coming soon...) Changelog 2021/12/6

PRIS-CV: Computer Vision Group 11 Dec 11, 2022
AI-generated-characters for Learning and Wellbeing

AI-generated-characters for Learning and Wellbeing Click here for the full project page. This repository contains the source code for the paper AI-gen

MIT Media Lab 214 Jan 01, 2023
KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

KDD CUP 2020: AutoGraph Team: aister Members: Jianqiang Huang, Xingyuan Tang, Mingjian Chen, Jin Xu, Bohang Zheng, Yi Qi, Ke Hu, Jun Lei Team Introduc

96 May 30, 2022
Add gui for YoloV5 using PyQt5

HEAD 更新2021.08.16 **添加图片和视频保存功能: 1.图片和视频按照当前系统时间进行命名 2.各自检测结果存放入output文件夹 3.摄像头检测的默认设备序号更改为0,减少调试报错 温馨提示: 1.项目放置在全英文路径下,防止项目报错 2.默认使用cpu进行检测,自

Ruihao Wang 65 Dec 27, 2022
duralava is a neural network which can simulate a lava lamp in an infinite loop.

duralava duralava is a neural network which can simulate a lava lamp in an infinite loop. Example This is not a real lava lamp but a "fake" one genera

Maximilian Bachl 87 Dec 20, 2022
Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch

Image Super-Resolution via Iterative Refinement Paper | Project Brief This is a unoffical implementation about Image Super-Resolution via Iterative Re

LiangWei Jiang 2.5k Jan 02, 2023
OcclusionFusion: realtime dynamic 3D reconstruction based on single-view RGB-D

OcclusionFusion (CVPR'2022) Project Page | Paper | Video Overview This repository contains the code for the CVPR 2022 paper OcclusionFusion, where we

Wenbin Lin 193 Dec 15, 2022
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation

STCN Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [a

Rex Cheng 456 Dec 12, 2022
Tensorflow Implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (ICML 2017 workshop)

tf-SNDCGAN Tensorflow implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (https://www.researchgate.net/publicati

Nhat M. Nguyen 248 Nov 25, 2022
Get 2D point positions (e.g., facial landmarks) projected on 3D mesh

points2d_projection_mesh Input 2D points (e.g. facial landmarks) on an image Camera parameters (extrinsic and intrinsic) of the image Aligned 3D mesh

5 Dec 08, 2022
An algorithm study of the 6th iOS 10 set of Boost Camp Web Mobile

알고리즘 스터디 🔥 부스트캠프 웹모바일 6기 iOS 10조의 알고리즘 스터디 입니다. 개인적인 사정 등으로 S034, S055만 참가하였습니다. 스터디 목적 상진: 코테 합격 + 부캠끝나고 아침에 일어나기 위해 필요한 사이클 기완: 꾸준하게 자리에 앉아 공부하기 +

2 Jan 11, 2022