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Gender Bias Detection

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Investigating Subtler Biases in LLMs: Ageism, Beauty, Institutional, and Nationality Bias in Generative Models

M. Kamruzzaman, M. I. Shovon, Gene Louis Kim•Fri Sep 15 2023

This paper asks whether LLMs hold wide-reaching biases of positive or negative sentiment for specific social groups similar to the "what is beautiful is good" bias found in people in experimental psychology, and investigates bias along less-studied but still consequential, dimensions, such as age and beauty.

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Measuring Gender Bias in Word Embeddings across Domains and Discovering New Gender Bias Word Categories

K. Chaloner, Alfredo Maldonado•Mon Dec 31 2018

This paper applies the WEAT bias detection method to four sets of word embeddings trained on corpora from four different domains: news, social networking, biomedical and a gender-balanced corpus extracted from Wikipedia, and finds that some domains are definitely more prone to gender bias than others.

54 0

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Matched sample selection with GANs for mitigating attribute confounding

Guha Balakrishnan, P. Perona, Chandan Singh•Tue Mar 23 2021

This work proposes a matching approach that selects a subset of images from the full dataset with balanced attribute distributions across protected attributes, and demonstrates its work in the context of gender bias in multiple open-source facial-recognition classifiers and finds that bias persists after removing key confounders via matching.

7 0

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Benchmarking Bias Mitigation Algorithms in Representation Learning through Fairness Metrics

Soroush Mehri, Charan Reddy, Deepak Sharma, Adriana Romero-Soriano, Samira Shabanian, Sina Honari•Thu Dec 31 2020

The results show that the bias of models increase as datasets become more imbalanced or datasets attributes become more correlated, the level of dominance of correlated sensitive dataset features impact bias, and the sensitive information remains in the latent representation even when bias-mitigation algorithms are applied.

36 0

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Quantifying gender biases towards politicians on Reddit

Sara Vera Marjanović, Isabelle Augenstein, Karolina Stańczak•Tue Dec 21 2021

It is found that, contrary to previous research, coverage and sentiment biases suggest equal public interest in female politicians, however, the results of the nominal and lexical analyses suggest this interest is not as professional or respectful as that expressed about male politicians.

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Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection

Eike Petersen, Aasa Feragen, Maria Luise da Costa Zemsch, A. Henriksen, Oskar Eiler Wiese Christensen, M. Ganz•Sun Apr 03 2022

In this paper, a simple logistic regression model using manually selected volumetric features and a convolutional neural network trained on 3D MRI data are compared, finding that CNN performance is generally improved for both male and female subjects when including more female subjects in the training dataset.

30 0

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Towards Algorithmic Fairness by means of Instance-level Data Re-weighting based on Shapley Values

Adrián Arnaiz-Rodríguez, F. Escolano, Nuria Oliver•Thu Mar 02 2023

This paper proposes FairShap, a novel instance-level data re-weighting method for fair algorithmic decision-making through data valuation by means of Shapley Values, which is model-agnostic and easily interpretable.

6 0

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Gender Bias Detection in Court Decisions: A Brazilian Case Study

Raysa Benatti, F. Severi, Sandra Avila, Esther Colombini•Fri May 31 2024

An experimental framework developed to automatically detect gender biases in court decisions issued in Brazilian Portuguese is presented and features identified to be critical in such a technology are described to be critical in such a technology, given its proposed use as a support tool for research and assessment of court activity.

4 0

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Gender Bias Detection | State-of-the-Art