Latest Articles for Bias

Exploring the key ethical concerns in AI development and usage.

This research focuses on reducing multiple biases in language models simultaneously.

Analysis shows demographic disparities in brain age prediction accuracy.

A new method to improve language model behavior by reducing bias and toxic output.

This article examines bias in language models and their emotional alignment with different social groups.

Examining solutions to improve accuracy in location-based population statistics.

This article examines how language models can adopt ideological biases from training data.

An analysis of bias and incivility in Indian television debates.

This article discusses new methods to enhance redshift calibration for better distance measurements in astronomy.

This study reveals biases in language models based on names related to race and gender.

This study examines biases in masked language models and their implications.

Delving into biochemical networks and their interactions using mathematical models.

Partnerships aim to develop fair AI tools for global healthcare improvement.

Strategies to reduce bias in ML, focusing on continuous sensitive attributes.

Examining bias in deep learning for MRI image reconstruction across gender and age.

The study reveals disparities in UAD models impacting healthcare fairness.

Examining performance gaps in speech recognition across different genders.

This article examines the reliability of political views in large language models.

A new tool assesses bias in ML-based early-warning systems for better patient care.

Methods for predicting unseen data based on observed samples.

Examining the impact of diversity and access in AI development.

Model editing can amplify biases and misinformation in language models.

NOVA helps users evaluate their media beliefs against actual reports.

Methods to minimize bias in large language models for fairer outcomes.

Evaluating how biases in language models affect real-world applications.

This study examines communities sharing low-credibility news on social media.

A new approach reduces bias in machine learning models with class imbalance.

Study reveals how language models learn gender features from few examples.

Examining the ethical concerns of Large Language Models in medicine.

A new approach to reduce bias in AI models and improve predictions.

HEAL-ViT combines Vision Transformers and spherical meshes for improved weather predictions.

A study on the performance and evaluation methods of large language models.

Learn how feature attribution explains ranking decisions in automated systems.

New shrinkage methods enhance Hessian estimation for machine learning optimization tasks.

Study highlights biases in fMRI data analysis methods.

Examining biases in next-token prediction and their impact on model performance.

A study on bias in Russian language models using a new dataset.

A study that measures political bias in large language models through stance and framing.

Research investigates gender bias by evaluating statistical and causal fairness in NLP models.

Examining bias issues in large language models and efforts to improve equity.