[ICML 2021] Towards Understanding and Mitigating Social Biases in Language Models

Overview

Towards Understanding and Mitigating Social Biases in Language Models

This repo contains code and data for evaluating and mitigating bias from generation models.

Paper

Towards Understanding and Mitigating Social Biases in Language Models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, and Ruslan Salakhutdinov
ICML 2021

If you find this repository useful, please cite our paper:

@inproceedings{liang2021towards,
  title={Towards Understanding and Mitigating Social Biases in Language Models},
  author={Liang, Paul Pu and Wu, Chiyu and Morency, Louis-Philippe and Salakhutdinov, Ruslan},
  booktitle={International Conference on Machine Learning},
  pages={6565--6576},
  year={2021},
  organization={PMLR}
}

1. Identify bias-sensitive tokens, obtain bias subspace and create the dataset to train the bias classifier

python data_preprocess.py --embed_source glove --by_pca True --num_components 5 --save_subspace False

Glove embedding and gpt2 embedding are large files, you can download or extract them by yourself. We also provide the google drive link.

2. Train the bias classifier and learn the projection matrix P

python context_nullspace_projection.py

The code of nullspace projection is from INLP. Thanks for their great work!

To run the INLP experiments, you need to git clone https://github.com/shauli-ravfogel/nullspace_projection first, and put it under the root directory of this repo.

3. Evaluate Bias existing in the gpt2

Local Bias

cd src/local_bias
python measure_local_bias.py

It will take long time to run the evaluation script on the full data. Here we provide the subset of our evaluation data now. Full data will be uploaded via google drive soon.

Global Bias

We use the regard score difference as the metric for global bias. The evaluation code is from https://github.com/ewsheng/nlg-bias. Thanks for their great work!

git clone https://github.com/ewsheng/nlg-bias.git
cd src/global_bias
python generate_full_sentence.py --algorithm INLP

After full sentences are generated, you need to use the regard classifier to measure the global bias.

To reproduce the result in our paper, we also provide the projection matrix P for the gender bias test in data/saved_P/P_gender_test_79.npy

Acknowledgements

Owner
Paul Liang
Machine Learning Department, CMU
Paul Liang
An implementation of the BADGE batch active learning algorithm.

Batch Active learning by Diverse Gradient Embeddings (BADGE) An implementation of the BADGE batch active learning algorithm. Details are provided in o

125 Dec 24, 2022
Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.

SAFA: Structure Aware Face Animation (3DV2021) Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation. Getting Started

QiulinW 122 Dec 23, 2022
ElasticFace: Elastic Margin Loss for Deep Face Recognition

This is the official repository of the paper: ElasticFace: Elastic Margin Loss for Deep Face Recognition Paper on arxiv: arxiv Model Log file Pretrain

Fadi Boutros 113 Dec 14, 2022
This is the code for CVPR 2021 oral paper: Jigsaw Clustering for Unsupervised Visual Representation Learning

JigsawClustering Jigsaw Clustering for Unsupervised Visual Representation Learning Pengguang Chen, Shu Liu, Jiaya Jia Introduction This project provid

DV Lab 73 Sep 18, 2022
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models

Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery

MOSES 656 Dec 29, 2022
Pytorch implementation of Hinton's Dynamic Routing Between Capsules

pytorch-capsule A Pytorch implementation of Hinton's "Dynamic Routing Between Capsules". https://arxiv.org/pdf/1710.09829.pdf Thanks to @naturomics fo

Tim Omernick 625 Oct 27, 2022
Project of 'TBEFN: A Two-branch Exposure-fusion Network for Low-light Image Enhancement '

TBEFN: A Two-branch Exposure-fusion Network for Low-light Image Enhancement Codes for TMM20 paper "TBEFN: A Two-branch Exposure-fusion Network for Low

KUN LU 31 Nov 06, 2022
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items

A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband Items This repository co

Taimur Hassan 3 Mar 16, 2022
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression

Patch-Based Deep Autoencoder for Point Cloud Geometry Compression Overview The ever-increasing 3D application makes the point cloud compression unprec

17 Dec 05, 2022
Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.

Video Representation Learning by Recognizing Temporal Transformations [Project Page] Simon Jenni, Givi Meishvili, and Paolo Favaro. In ECCV, 2020. Thi

Simon Jenni 46 Nov 14, 2022
Code in conjunction with the publication 'Contrastive Representation Learning for Hand Shape Estimation'

HanCo Dataset & Contrastive Representation Learning for Hand Shape Estimation Code in conjunction with the publication: Contrastive Representation Lea

Computer Vision Group, Albert-Ludwigs-Universität Freiburg 38 Dec 13, 2022
TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition

TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition Xue, Wenyuan, et al. "TGRNet: A Table Graph Reconstruction Network for Ta

Wenyuan 68 Jan 04, 2023
Python package for covariance matrices manipulation and Biosignal classification with application in Brain Computer interface

pyRiemann pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry. The primary target is cla

447 Jan 05, 2023
Source code for CAST - Crisis Domain Adaptation Using Sequence-to-sequence Transformers (Accepted to ISCRAM 2021, CorePaper).

Source code for CAST: Crisis Domain Adaptation UsingSequence-to-sequenceTransformers (Paper, BibTeX, Accepted to ISCRAM 2021, CorePaper) Quick start D

Congcong Wang 0 Jul 14, 2021
Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation

VT-UNet This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. Environmen

Himashi Amanda Peiris 114 Dec 20, 2022
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)

Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology Self-Supervised Vision Transformers Learn Visual Concepts in Histopatholog

Richard Chen 95 Dec 24, 2022
PyTorch implementation of Rethinking Positional Encoding in Language Pre-training

TUPE PyTorch implementation of Rethinking Positional Encoding in Language Pre-training. Quickstart Clone this repository. git clone https://github.com

Jake Tae 5 Jan 27, 2022
Code release for our paper, "SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo"

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan

68 Dec 14, 2022
Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”

RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L

37 Dec 08, 2022