Cultural Competence

Exploring Textual Semantics Diversity for Image Transmission in Semantic Communication Systems using Visual Language Model

In recent years, the rapid development of machine learning has brought reforms and challenges to traditional communication systems. Semantic communication has appeared as an effective strategy to effectively extract relevant semantic signals semantic segmentation labels and image features for image transmission. However, the insufficient number of extracted semantic features of images will poten...

HingeRLC-GAN: Combating Mode Collapse with Hinge Loss and RLC Regularization

Recent advances in Generative Adversarial Networks (GANs) have demonstrated their capability for producing high-quality images. However, a significant challenge remains mode collapse, which occurs when the generator produces a limited number of data patterns that do not reflect the diversity of the training dataset. This study addresses this issue by proposing a number of architectural changes a...

LakotaBERT: A Transformer-based Model for Low Resource Lakota Language

Lakota, a critically endangered language of the Sioux people in North America, faces significant challenges due to declining fluency among younger g...

MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection

Mathematical error detection in educational settings presents a significant challenge for Multimodal Large Language Models (MLLMs), requiring a soph...

Unseen from Seen: Rewriting Observation-Instruction Using Foundation Models for Augmenting Vision-Language Navigation

Data scarcity is a long-standing challenge in the Vision-Language Navigation (VLN) field, which extremely hinders the generalization of agents to un...

Bayesian generative models can flag performance loss, bias, and out-of-distribution image content

Generative models are popular for medical imaging tasks such as anomaly detection, feature extraction, data visualization, or image generation. Sinc...

Align Your Rhythm: Generating Highly Aligned Dance Poses with Gating-Enhanced Rhythm-Aware Feature Representation

Automatically generating natural, diverse and rhythmic human dance movements driven by music is vital for virtual reality and film industries. Howev...

Does a Rising Tide Lift All Boats? Bias Mitigation for AI-based CMR Segmentation

Artificial intelligence (AI) is increasingly being used for medical imaging tasks. However, there can be biases in the resulting models, particularl...

When Tom Eats Kimchi: Evaluating Cultural Bias of Multimodal Large Language Models in Cultural Mixture Contexts

In a highly globalized world, it is important for multi-modal large language models (MLLMs) to recognize and respond correctly to mixed-cultural inp...

Chain of Functions: A Programmatic Pipeline for Fine-Grained Chart Reasoning Data

Visual reasoning is crucial for multimodal large language models (MLLMs) to address complex chart queries, yet high-quality rationale data remains s...

Probabilistic Prompt Distribution Learning for Animal Pose Estimation

Multi-species animal pose estimation has emerged as a challenging yet critical task, hindered by substantial visual diversity and uncertainty. This ...

Bias Evaluation and Mitigation in Retrieval-Augmented Medical Question-Answering Systems

Medical Question Answering systems based on Retrieval Augmented Generation is promising for clinical decision support because they can integrate ext...

Exploring Disparity-Accuracy Trade-offs in Face Recognition Systems: The Role of Datasets, Architectures, and Loss Functions

Automated Face Recognition Systems (FRSs), developed using deep learning models, are deployed worldwide for identity verification and facial attribu...

Boosting Semi-Supervised Medical Image Segmentation via Masked Image Consistency and Discrepancy Learning

Semi-supervised learning is of great significance in medical image segmentation by exploiting unlabeled data. Among its strategies, the co-training ...

Identifying and Mitigating Position Bias of Multi-image Vision-Language Models

The evolution of Large Vision-Language Models (LVLMs) has progressed from single to multi-image reasoning. Despite this advancement, our findings in...

Concept-as-Tree: Synthetic Data is All You Need for VLM Personalization

Vision-Language Models (VLMs) have demonstrated exceptional performance in various multi-modal tasks. Recently, there has been an increasing interes...

Unlock Pose Diversity: Accurate and Efficient Implicit Keypoint-based Spatiotemporal Diffusion for Audio-driven Talking Portrait

Audio-driven single-image talking portrait generation plays a crucial role in virtual reality, digital human creation, and filmmaking. Existing appr...

DivCon-NeRF: Generating Augmented Rays with Diversity and Consistency for Few-shot View Synthesis

Neural Radiance Field (NeRF) has shown remarkable performance in novel view synthesis but requires many multiview images, making it impractical for ...

Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model

Image generative models, particularly diffusion-based models, have surged in popularity due to their remarkable ability to synthesize highly realist...

A Plug-and-Play Learning-based IMU Bias Factor for Robust Visual-Inertial Odometry

The bias of low-cost Inertial Measurement Units (IMU) is a critical factor affecting the performance of Visual-Inertial Odometry (VIO). In particula...