HanXudong/COMP90042_Workshops

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HanXudong/COMP90042_Workshops

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fairlib

A framework for assessing and improving classification fairness.

Jupyter Notebook

COMP90051_Workshops

Jupyter Notebook

COMP90051_2020_S1

Materials for SML 2020 S1

Jupyter Notebook

Diverse_Adversaries_for_Mitigating_Bias_in_Training

Source codes for EACL 2021 paper "Diverse Adversaries for Mitigating Bias in Training"

Jupyter Notebook

Fair_Dataset_Distillation

Source codes for SustaiNLP@EMNLP 2022 paper "Towards Fair Supervised Dataset Distillation for Text Classification"

Fair_Enough

Source codes for EACL 2023 paper "Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP"

Jupyter Notebook

An_Unsupervised_Locality-based_Method_for_Bias_Mitigation

Source codes for ICLR 2023 paper "Everybody Needs Good Neighbours: An Unsupervised Locality-based Method for Bias Mitigation"

GLoM

Source codes for EMNLP 2019 paper "Grounding learning of modifier dynamics: An application to color naming"

Jupyter Notebook

Systematic_Evaluation_of_Predictive_Fairness

Source codes for AACL 2022 paper "Systematic Evaluation of Predictive Fairness"

ReImplementation_Robust_and_Privacy_preserving_Text_Representations

PyTorch ReImplementations for ''Towards Robust and Privacy-preserving Text Representations''

Jupyter Notebook

Brute-Force-Attacks-Detection