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Cultural Competence

Latest AI and machine learning research in cultural competence for healthcare professionals.

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f-statistics-based ancestry profiling and convolutional neural network phenotyping shed new light on the structure of genetic and spike shape diversity in Aegilops tauschii Coss.

Aegilops tauschii Coss., a progenitor of bread wheat, is an important wild genetic resource for breeding. The species comprises three genetically defined lineages (TauL1, TauL2, and TauL3), each displaying valuable phenotypes in agronomic traits, including spike shape. In the present work, we studied the relationship between population structure and spike shape variation patterns using a collectio...

Jun 11 2025 40399064

Flow Diverse and Efficient: Learning Momentum Flow Matching via Stochastic Velocity Field Sampling

Recently, the rectified flow (RF) has emerged as the new state-of-the-art among flow-based diffusion models due to its high efficiency advantage in straight path sampling, especially with the amazing images generated by a series of RF models such as Flux 1.0 and SD 3.0. Although a straight-line connection between the noisy and natural data distributions is intuitive, fast, and easy to optimize, ...

Adultification Bias in LLMs and Text-to-Image Models

The rapid adoption of generative AI models in domains such as education, policing, and social media raises significant concerns about potential bias...

Cultural Bias Matters: A Cross-Cultural Benchmark Dataset and Sentiment-Enriched Model for Understanding Multimodal Metaphors

Metaphors are pervasive in communication, making them crucial for natural language processing (NLP). Previous research on automatic metaphor process...

A Deep Learning Approach for Facial Attribute Manipulation and Reconstruction in Surveillance and Reconnaissance

Surveillance systems play a critical role in security and reconnaissance, but their performance is often compromised by low-quality images and video...

Biases Propagate in Encoder-based Vision-Language Models: A Systematic Analysis From Intrinsic Measures to Zero-shot Retrieval Outcomes

To build fair AI systems we need to understand how social-group biases intrinsic to foundational encoder-based vision-language models (VLMs) manifes...

Noise Consistency Regularization for Improved Subject-Driven Image Synthesis

Fine-tuning Stable Diffusion enables subject-driven image synthesis by adapting the model to generate images containing specific subjects. However, ...

Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias

Diagnosing deep neural networks (DNNs) through the eigenspectrum of weight matrices has been an active area of research in recent years. At a high l...

DIMCIM: A Quantitative Evaluation Framework for Default-mode Diversity and Generalization in Text-to-Image Generative Models

Recent advances in text-to-image (T2I) models have achieved impressive quality and consistency. However, this has come at the cost of representation...

Subjective Perspectives within Learned Representations Predict High-Impact Innovation

Existing studies of innovation emphasize the power of social structures to shape innovation capacity. Emerging machine learning approaches, however,...

The mutual exclusivity bias of bilingual visually grounded speech models

Mutual exclusivity (ME) is a strategy where a novel word is associated with a novel object rather than a familiar one, facilitating language learnin...

More or Less Wrong: A Benchmark for Directional Bias in LLM Comparative Reasoning

Large language models (LLMs) are known to be sensitive to input phrasing, but the mechanisms by which semantic cues shape reasoning remain poorly un...

EmoArt: A Multidimensional Dataset for Emotion-Aware Artistic Generation

With the rapid advancement of diffusion models, text-to-image generation has achieved significant progress in image resolution, detail fidelity, and...

CogniPair: From LLM Chatbots to Conscious AI Agents -- GNWT-Based Multi-Agent Digital Twins for Social Pairing -- Dating & Hiring Applications

Current large language model (LLM) agents lack authentic human psychological processes necessary for genuine digital twins and social AI application...

DFBench: Benchmarking Deepfake Image Detection Capability of Large Multimodal Models

With the rapid advancement of generative models, the realism of AI-generated images has significantly improved, posing critical challenges for verif...

Hanfu-Bench: A Multimodal Benchmark on Cross-Temporal Cultural Understanding and Transcreation

Culture is a rich and dynamic domain that evolves across both geography and time. However, existing studies on cultural understanding with vision-la...

Efficiency without Compromise: CLIP-aided Text-to-Image GANs with Increased Diversity

Recently, Generative Adversarial Networks (GANs) have been successfully scaled to billion-scale large text-to-image datasets. However, training such...

AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning

The recent progress of large language model agents has opened new possibilities for automating tasks through graphical user interfaces (GUIs), espec...

DeepSeek in Healthcare: A Survey of Capabilities, Risks, and Clinical Applications of Open-Source Large Language Models

DeepSeek-R1 is a cutting-edge open-source large language model (LLM) developed by DeepSeek, showcasing advanced reasoning capabilities through a hyb...

Data Heterogeneity Modeling for Trustworthy Machine Learning

Data heterogeneity plays a pivotal role in determining the performance of machine learning (ML) systems. Traditional algorithms, which are typically...

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