Latest Articles for Bias

A new method addresses feedback biases in recommendation systems for two-sided interactions.

A new method improves fairness in medical imaging predictions.

A framework to identify and reduce bias in textual data for fairer outcomes.

A study investigates fairness in Yelp's recommendation and ranking systems.

This study evaluates how neuron patterns relate to brain function and behavior.

How variability affects average estimates in line graphs.

A program addresses provider burnout and bias to enhance maternal care quality.

Teams competed to create efficient face recognition systems during the EFaR 2023 event.

A novel approach to reduce bias in image recognition models using synthetic data.

This study introduces a method to reduce bias in machine learning models.

CDR strategy improves recommendations by filtering out harmful data imputation.

Examining how human feedback shapes decision-making reward systems.

Exploring the impact of real-world data on health technology assessments.

A new method improves fairness in generative models without requiring original datasets.

New interventions seek to reduce bias in GNNs while maintaining accuracy in predictions.

New method tackles multiple biases in image classification to improve fairness.

This study explores bias in audio models used for instrument recognition.

A new model aims to reduce health disparities in electronic records.

A new dataset provides insights into bias in language technology.

A new method minimizes bias while maintaining privacy in machine learning.

This study reviews new methods for analyzing ancient DNA effectively.

MedCheckLLM improves medical record evaluations using established guidelines.

Examining how feedback affects economic forecasts and decision-making.

Exploring the ethical implications of AI in healthcare and the need for fairness.

This article examines bias in hate speech detection tools and their impact.

This article discusses the impact of biases in code generated by large language models.

UniSA framework unifies tasks in sentiment analysis for better emotion recognition.

Exploring the rise of decentralized language models and their benefits over centralized systems.

A new method enhances estimates for recommendation system performance.

New strategies enhance neural networks' learning in real-world conditions.

Exploring the need for fairness in personalized recommendation systems.

Using prototypes to enhance dataset comparison in computer vision.

Advancements in geolocation tools enhance humanitarian aid accuracy and reduce biases.

Examining the unique testing challenges of generative AI applications.

A look into donut RD designs and their implications in research.

A study reveals gender bias in AI across different cultures.

Research highlights bias in AI affecting underrepresented groups in New Zealand.

New methods aim to improve inclusivity in AI-generated images.

This study investigates biases in language models using prompt-based learning.

A new method improves model fairness and accuracy without extensive group data.