Cultural Competence

Metamorphic Testing for Fairness Evaluation in Large Language Models: Identifying Intersectional Bias in LLaMA and GPT

Large Language Models (LLMs) have made significant strides in Natural Language Processing but remain vulnerable to fairness-related issues, often reflecting biases inherent in their training data. These biases pose risks, particularly when LLMs are deployed in sensitive areas such as healthcare, finance, and law. This paper introduces a metamorphic testing approach to systematically identify fai...

Bias in Large Language Models Across Clinical Applications: A Systematic Review

Background: Large language models (LLMs) are rapidly being integrated into healthcare, promising to enhance various clinical tasks. However, concerns exist regarding their potential for bias, which could compromise patient care and exacerbate health inequities. This systematic review investigates the prevalence, sources, manifestations, and clinical implications of bias in LLMs. Methods: We cond...

Language Models reach higher Agreement than Humans in Historical Interpretation

This paper compares historical annotations by humans and Large Language Models. The findings reveal that both exhibit some cultural bias, but Large ...

Semantic segmentation of forest stands using deep learning

Forest stands are the fundamental units in forest management inventories, silviculture, and financial analysis within operational forestry. Over the...

Implicit Bias Injection Attacks against Text-to-Image Diffusion Models

The proliferation of text-to-image diffusion models (T2I DMs) has led to an increased presence of AI-generated images in daily life. However, biased...

Using complex prompts to identify fine-grained biases in image generation through ChatGPT-4o

There are not one but two dimensions of bias that can be revealed through the study of large AI models: not only bias in training data or the produc...

Beyond a Single Mode: GAN Ensembles for Diverse Medical Data Generation

The advancement of generative AI, particularly in medical imaging, confronts the trilemma of ensuring high fidelity, diversity, and efficiency in sy...

Boosting MLLM Reasoning with Text-Debiased Hint-GRPO

MLLM reasoning has drawn widespread research for its excellent problem-solving capability. Current reasoning methods fall into two types: PRM, which...

MuseFace: Text-driven Face Editing via Diffusion-based Mask Generation Approach

Face editing modifies the appearance of face, which plays a key role in customization and enhancement of personal images. Although much work have ac...

Evolutionary Prompt Optimization Discovers Emergent Multimodal Reasoning Strategies in Vision-Language Models

We present a framework for optimizing prompts in vision-language models to elicit multimodal reasoning without model retraining. Using an evolutiona...

A Large Scale Analysis of Gender Biases in Text-to-Image Generative Models

With the increasing use of image generation technology, understanding its social biases, including gender bias, is essential. This paper presents th...

Multi-Objective Quality-Diversity in Unstructured and Unbounded Spaces

Quality-Diversity algorithms are powerful tools for discovering diverse, high-performing solutions. Recently, Multi-Objective Quality-Diversity (MOQ...

A Multi-Site Study on AI-Driven Pathology Detection and Osteoarthritis Grading from Knee X-Ray

Introduction: Bone health disorders like osteoarthritis and osteoporosis pose major global health challenges, often leading to delayed diagnoses due...

NeuroLIP: Interpretable and Fair Cross-Modal Alignment of fMRI and Phenotypic Text

Integrating functional magnetic resonance imaging (fMRI) connectivity data with phenotypic textual descriptors (e.g., disease label, demographic dat...

Sacred or Secular? Religious Bias in AI-Generated Financial Advice

This study examines religious biases in AI-generated financial advice, focusing on ChatGPT's responses to financial queries. Using a prompt-based me...

Dissecting and Mitigating Diffusion Bias via Mechanistic Interpretability

Diffusion models have demonstrated impressive capabilities in synthesizing diverse content. However, despite their high-quality outputs, these model...

Dynamics of Algorithmic Content Amplification on TikTok

Intelligent algorithms increasingly shape the content we encounter and engage with online. TikTok's For You feed exemplifies extreme algorithm-drive...

Reflections on Diversity: A Real-time Virtual Mirror for Inclusive 3D Face Transformations

Real-time 3D face manipulation has significant applications in virtual reality, social media and human-computer interaction. This paper introduces a...

Zero-Shot Human-Object Interaction Synthesis with Multimodal Priors

Human-object interaction (HOI) synthesis is important for various applications, ranging from virtual reality to robotics. However, acquiring 3D HOI ...

Beyond Relevance: An Adaptive Exploration-Based Framework for Personalized Recommendations

Recommender systems must balance personalization, diversity, and robustness to cold-start scenarios to remain effective in dynamic content environme...