Work Force

DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning

Explainable artificial intelligence (XAI) has become increasingly important in decision-critical domains such as healthcare, finance, and law. Counterfactual (CF) explanations, a key approach in XAI, provide users with actionable insights by suggesting minimal modifications to input features that lead to different model outcomes. Despite significant advancements, existing CF generation methods o...

[Medical text classification model integrating medical entity label semantics].

Automatic classification of medical questions is of great significance in improving the quality and efficiency of online medical services, and belongs to the task of intent recognition. Joint entity recognition and intent recognition perform better than single task models. Currently, most publicly available medical text intent recognition datasets lack entity annotation, and manual annotation of t...

Gaussian Splatting is an Effective Data Generator for 3D Object Detection

We investigate data augmentation for 3D object detection in autonomous driving. We utilize recent advancements in 3D reconstruction based on Gaussia...

Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions

The exponential growth of Large Language Models (LLMs) continues to highlight the need for efficient strategies to meet ever-expanding computational...

A Multimodal Recaptioning Framework to Account for Perceptual Diversity in Multilingual Vision-Language Modeling

There are many ways to describe, name, and group objects when captioning an image. Differences are evident when speakers come from diverse cultures ...

Adaptation Method for Misinformation Identification

Multimodal fake news detection plays a crucial role in combating online misinformation. Unfortunately, effective detection methods rely on annotated...

DeepPD: Joint Phase and Object Estimation from Phase Diversity with Neural Calibration of a Deformable Mirror

Sample-induced aberrations and optical imperfections limit the resolution of fluorescence microscopy. Phase diversity is a powerful technique that l...

Exploring Language Patterns of Prompts in Text-to-Image Generation and Their Impact on Visual Diversity

Following the initial excitement, Text-to-Image (TTI) models are now being examined more critically. While much of the discourse has focused on bias...

Entropy Rectifying Guidance for Diffusion and Flow Models

Guidance techniques are commonly used in diffusion and flow models to improve image quality and consistency for conditional generative tasks such as...

Real-World Depth Recovery via Structure Uncertainty Modeling and Inaccurate GT Depth Fitting

The low-quality structure in raw depth maps is prevalent in real-world RGB-D datasets, which makes real-world depth recovery a critical task in rece...

Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets

Medical Visual Question Answering (MVQA) systems can interpret medical images in response to natural language queries. However, linguistic variabili...

Towards contrast- and pathology-agnostic clinical fetal brain MRI segmentation using SynthSeg

Magnetic resonance imaging (MRI) has played a crucial role in fetal neurodevelopmental research. Structural annotations of MR images are an importan...

Early-Bird Diffusion: Investigating and Leveraging Timestep-Aware Early-Bird Tickets in Diffusion Models for Efficient Training

Training diffusion models (DMs) requires substantial computational resources due to multiple forward and backward passes across numerous timesteps, ...

Mixture of Group Experts for Learning Invariant Representations

Sparsely activated Mixture-of-Experts (MoE) models effectively increase the number of parameters while maintaining consistent computational costs pe...

ELSA: A Style Aligned Dataset for Emotionally Intelligent Language Generation

Advancements in emotion aware language processing increasingly shape vital NLP applications ranging from conversational AI and affective computing t...

Echo: An Open-Source, Low-Cost Teleoperation System with Force Feedback for Dataset Collection in Robot Learning

In this article, we propose Echo, a novel joint-matching teleoperation system designed to enhance the collection of datasets for manual and bimanual...

DiverseFlow: Sample-Efficient Diverse Mode Coverage in Flows

Many real-world applications of flow-based generative models desire a diverse set of samples that cover multiple modes of the target distribution. H...

ID-Booth: Identity-consistent Face Generation with Diffusion Models

Recent advances in generative modeling have enabled the generation of high-quality synthetic data that is applicable in a variety of domains, includ...

A Multi-Phase Analysis of Blood Culture Stewardship: Machine Learning Prediction, Expert Recommendation Assessment, and LLM Automation

Blood cultures are often over ordered without clear justification, straining healthcare resources and contributing to inappropriate antibiotic use p...

WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care

Chronic wounds affect a large population, particularly the elderly and diabetic patients, who often exhibit limited mobility and co-existing health ...