Cultural Competence

Spatial Organellomics Maps Cell State Diversity and Metabolic Adaptation in Tissues

Cell state diversity drives tissue adaptability, repair, and disease resilience, but fully capturing this cellular complexity remains a challenge. Most current approaches rely on transcriptional profiling and often overlook functional insights embedded in organelle structure, key indicators of cellular metabolism and stress. Here, we introduce spatial Organellomics (sOrganellomics), an imaging wor...

WUTDet: A 100K-Scale Ship Detection Dataset and Benchmarks with Dense Small Objects

Ship detection for navigation is a fundamental perception task in intelligent waterway transportation systems. However, existing public ship detection datasets remain limited in terms of scale, the proportion of small-object instances, and scene diversity, which hinders the systematic evaluation and generalization study of detection algorithms in complex maritime environments. To this end, we cons...

Tarot-SAM3: Training-free SAM3 for Any Referring Expression Segmentation

Referring Expression Segmentation (RES) aims to segment image regions described by natural-language expressions, serving as a bridge between vision an...

CAFP: A Post-Processing Framework for Group Fairness via Counterfactual Model Averaging

Ensuring fairness in machine learning predictions is a critical challenge, especially when models are deployed in sensitive domains such as credit sco...

RAGEN-2: Reasoning Collapse in Agentic RL

RL training of multi-turn LLM agents is inherently unstable, and reasoning quality directly determines task performance. Entropy is widely used to tra...

Is CLIP Cross-Eyed? Revealing and Mitigating Center Bias in the CLIP Family

Recent research has shown that contrastive vision-language models such as CLIP often lack fine-grained understanding of visual content. While a growin...

Few-Shot Distribution-Aligned Flow Matching for Data Synthesis in Medical Image Segmentation

Data heterogeneity hinders clinical deployment of medical image analysis models, and generative data augmentation helps mitigate this issue. However, ...

CLOP-DiT: Structured-Metadata-Conditioned Single-Cell Latent Generation via Contrastive Language-Omics Pretraining and Diffusion Transformers

Generating realistic single-cell transcriptomic profiles from structured biological descriptions would enable controlled simulation, data augmentation...

On-the-fly Repulsion in the Contextual Space for Rich Diversity in Diffusion Transformers

Modern Text-to-Image (T2I) diffusion models have achieved remarkable semantic alignment, yet they often suffer from a significant lack of variety, con...

Customized Visual Storytelling with Unified Multimodal LLMs

Multimodal story customization aims to generate coherent story flows conditioned on textual descriptions, reference identity images, and shot types. W...

Diversity Matters: Dataset Diversification and Dual-Branch Network for Generalized AI-Generated Image Detection

The rapid proliferation of AI-generated images, powered by generative adversarial networks (GANs), diffusion models, and other synthesis techniques, h...

Data Diversity vs. Model Complexity in the Prediction of Pediatric Bipolar Disorder: Evidence from Academic and Community Clinical Samples

Pediatric bipolar disorder is challenging to diagnose accurately due to symptom heterogeneity. More standardized and data-driven approaches are needed...

Diagnostic Accuracy of Large Language Models for Rare Diseases: A Systematic Review and Meta-Analysis

Background: Large language models (LLMs) have been evaluated as tools to assist rare disease diagnosis, yet evidence on their accuracy remains fragmen...

THEMIS: Towards Holistic Evaluation of MLLMs for Scientific Paper Fraud Forensics

We present THEMIS, a novel multi-task benchmark designed to comprehensively evaluate multimodal large language models (MLLMs) on visual fraud reasonin...

Demographic Fairness in Multimodal LLMs: A Benchmark of Gender and Ethnicity Bias in Face Verification

Multimodal Large Language Models (MLLMs) have recently been explored as face verification systems that determine whether two face images are of the sa...

ReDiPrune: Relevance-Diversity Pre-Projection Token Pruning for Efficient Multimodal LLMs

Recent multimodal large language models are computationally expensive because Transformers must process a large number of visual tokens. We present \t...

Latent Bias Alignment for High-Fidelity Diffusion Inversion in Real-World Image Reconstruction and Manipulation

Recent research has shown that text-to-image diffusion models are capable of generating high-quality images guided by text prompts. But can they be us...

VERIA: Verification-Centric Multimodal Instance Augmentation for Long-Tailed 3D Object Detection

Long-tail distributions in driving datasets pose a fundamental challenge for 3D perception, as rare classes exhibit substantial intra-class diversity ...

DAK-UCB: Diversity-Aware Prompt Routing for LLMs and Generative Models

The expansion of generative AI and LLM services underscores the growing need for adaptive mechanisms to select an appropriate available model to respo...

Policy-based Tuning of Autoregressive Image Models with Instance- and Distribution-Level Rewards

Autoregressive (AR) models are highly effective for image generation, yet their standard maximum-likelihood estimation training lacks direct optimizat...