Latest Articles for Bias

Exploring AI advancements in weather forecasting amid climate change.

This approach helps AI systems learn better without needing human labels.

Examining the importance of fairness in record matching techniques.

Explore the impact of shortcut learning on language models and their real-world applications.

This paper discusses creating safe, fair guidelines for AI development.

Two methods enhance the accuracy of AI-generated text evaluations.

This article discusses fairness issues in Graph Neural Networks and introduces a new method.

This study explores how different cultures interpret hate speech in memes.

A study reveals biases in measuring dark matter during galaxy cluster collisions.

Exploring how genes and environment interact to influence human traits.

A look at similarity networks to improve fairness in machine learning.

Methods to create fair summaries from diverse social media voices.

Examining how Language Models influence communication and ethical challenges.

A look at the ethical challenges in Natural Language Processing technology.

A new method enhances how AI handles pronouns for better representation.

Examining how bias affects language models and their interpretation of offensive language.

A guide to understanding multilevel and fixed effects models in data analysis.

LLMs speed up qualitative research, providing fresh insights from large volumes of text.

A new method improves fairness and accuracy in medical imaging AI systems.

A look at how researchers protect privacy in survey data while sharing insights.

Researchers tackle bias in language models using a new approach.

A closer look at gender bias in large language models and its implications.

A look at bias in AI and how to tackle it fairly.

An overview of how LLMs enhance evaluation processes while addressing key challenges.

A closer look at the benefits and challenges of Propensity Score Matching.

Exploring how AI can assess language quality and the challenges involved.

Examining biases in AI language models and potential solutions.

Learn how Importance Sampling and IMH estimate distributions in statistics.

Fairer-NMF aims to ensure equitable data representation for all groups.

Exploring how LLMs enhance software creation while maintaining trust.

Examining bias in content moderation and improving toxicity detection methods.

Investigating how biases affect language models and proposing new ways to measure them.

Exploring the role of LLMs in extracting procedural knowledge from text.

Learn how to measure bias in biomedical studies for reliable healthcare data.

A new method to measure biases in decisions without clear standards.

Examining treatment effects through adaptive methods in existing data.

A new method improves evaluation of generative models with limited labeled data.

Understanding data biases in machine learning for effective cyberbullying detection.

Examining the challenges and biases of LLMs in healthcare applications.

How LLMs are changing political processes and citizen engagement.