Cultural Competence

Photovoltaic Defect Image Generator with Boundary Alignment Smoothing Constraint for Domain Shift Mitigation

Accurate defect detection of photovoltaic (PV) cells is critical for ensuring quality and efficiency in intelligent PV manufacturing systems. However, the scarcity of rich defect data poses substantial challenges for effective model training. While existing methods have explored generative models to augment datasets, they often suffer from instability, limited diversity, and domain shifts. To ad...

3D Scene Generation: A Survey

3D scene generation seeks to synthesize spatially structured, semantically meaningful, and photorealistic environments for applications such as immersive media, robotics, autonomous driving, and embodied AI. Early methods based on procedural rules offered scalability but limited diversity. Recent advances in deep generative models (e.g., GANs, diffusion models) and 3D representations (e.g., NeRF...

Prompt-Based LLMs for Position Bias-Aware Reranking in Personalized Recommendations

Recommender systems are essential for delivering personalized content across digital platforms by modeling user preferences and behaviors. Recently,...

A Large Language Model for Feasible and Diverse Population Synthesis

Generating a synthetic population that is both feasible and diverse is crucial for ensuring the validity of downstream activity schedule simulation ...

Synthline: A Product Line Approach for Synthetic Requirements Engineering Data Generation using Large Language Models

While modern Requirements Engineering (RE) heavily relies on natural language processing and Machine Learning (ML) techniques, their effectiveness i...

The Multimodal Paradox: How Added and Missing Modalities Shape Bias and Performance in Multimodal AI

Multimodal learning, which integrates diverse data sources such as images, text, and structured data, has proven superior to unimodal counterparts i...

Gone With the Bits: Revealing Racial Bias in Low-Rate Neural Compression for Facial Images

Neural compression methods are gaining popularity due to their superior rate-distortion performance over traditional methods, even at extremely low ...

Token Coordinated Prompt Attention is Needed for Visual Prompting

Visual prompting techniques are widely used to efficiently fine-tune pretrained Vision Transformers (ViT) by learning a small set of shared prompts ...

Cognitive bias in generative AI influences religious education.

This study explores the transformative role of generative artificial intelligence (AI) in shaping religious cognition, with particular emphasis on its...

Personalisation or Prejudice? Addressing Geographic Bias in Hate Speech Detection using Debias Tuning in Large Language Models

Commercial Large Language Models (LLMs) have recently incorporated memory features to deliver personalised responses. This memory retains details su...

Mitigating Group-Level Fairness Disparities in Federated Visual Language Models

Visual language models (VLMs) have shown remarkable capabilities in multimodal tasks but face challenges in maintaining fairness across demographic ...

Component-Based Fairness in Face Attribute Classification with Bayesian Network-informed Meta Learning

The widespread integration of face recognition technologies into various applications (e.g., access control and personalized advertising) necessitat...

SOTA: Spike-Navigated Optimal TrAnsport Saliency Region Detection in Composite-bias Videos

Existing saliency detection methods struggle in real-world scenarios due to motion blur and occlusions. In contrast, spike cameras, with their high ...

Artificial Intelligence Applications in Obstetric Risk Prediction: A Systematic Review of Machine Learning Models for Preeclampsia.

Preeclampsia remains a leading cause of maternal and perinatal morbidity and mortality worldwide. While traditional prediction models have shown limit...

Generative AI mitigates representation bias and improves model fairness through synthetic health data.

Representation bias in health data can lead to unfair decisions and compromise the generalisability of research findings. As a consequence, underrepre...

Pitfalls and Best Practices in Evaluation of AI Algorithmic Biases in Radiology.

Despite growing awareness of problems with fairness in artificial intelligence (AI) models in radiology, evaluation of algorithmic biases, or AI biase...

LightCTL: lightweight contrastive TCR-pMHC specificity learning with context-aware prompt.

Identification of T cell receptor (TCR) specificities for antigens from large-scale single-cell or bulk TCR repertoire data plays a vital role in dise...

Artificial Intelligence and Workforce Diversity in Nuclear Medicine.

Artificial intelligence (AI) has rapidly reshaped the global practice of nuclear medicine. Through this shift, the integration of AI into nuclear medi...

Assessing online chat-based artificial intelligence models for weight loss recommendation appropriateness and bias in the presence of guideline incongruence.

BACKGROUND AND AIM: Managing obesity requires a comprehensive approach that involves therapeutic lifestyle changes, medications, or metabolic surgery....

Unveiling Public Stigma for Borderline Personality Disorder: A Comparative Study of Artificial Intelligence and Mental Health Care Providers.

Generative artificial intelligence (GAI) programs can identify symptoms and make recommendations for treatment for mental disorders, including borderl...