Mohamed bin Zayed University of Artificial Intelligence

Gaussian-LIC2: LiDAR-Inertial-Camera Gaussian Splatting SLAM

This paper presents a photo-realistic LiDAR-Inertial-Camera Gaussian Splatting SLAM system that simultaneously addresses visual quality, geometric accuracy, and real-time performance. The proposed method performs robust and accurate pose estimation within a continuous-time trajec...

Large language models for digital mental health: an HCI-centered scoping review

Large language models (LLMs) are rapidly reshaping digital mental health, yet how these systems are designed, used, and evaluated remains poorly characterized. We conducted an HCI-centered scoping review of 84 studies examining mental health tasks, stakeholders, interaction parad...

Mapping the RAG landscape: a four-axis taxonomy of efficiency, defense, interactivity, and reasoning

Large Language Models (LLMs) have demonstrated remarkable fluency across many tasks but remain limited by their static, parameter-bound knowledge and their susceptibility to hallucinating information. Retrieval-Augmented Generation (RAG) addresses these issues by incorporating ex...

An expert-level generalist AI for abdominal CT diagnosis

Artificial intelligence (AI) in radiology aspires to deliver expert-level diagnosis across diverse clinical tasks, yet existing supervised strategies remain limited in scope. We developed RADAR, a generalist vision-language model trained on more than 400,000 contrast-enhanced abd...

Uncovering pan-cancer signatures of chemoresistance

Abstract Background Chemotherapy resistance remains a formidable challenge in cancer treatment, driving high mortality rates worldwide. Despite significant advancements, it remains unclear whether conserved molecular programs underpin therapy resistance across cancer types. Metho...

Large-scale benchmarking of prokaryotic annotation tools across thousands of species

Abstract Background Genome annotation is an important step in deriving functional meaning from prokaryotic sequencing data, yet systematic evaluations guiding tool selection are lacking. We present the first large-scale investigation of four prominent open-source annotation tools...

MedKGent: a large language model agent framework for constructing temporally evolving medical knowledge graph

The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet current construction methods lack generalizability and ignore the temporal dynamics of evolving knowledge. To address this, we introduce...

Generalizable prediction of biological contaminants across aerobic and anaerobic membrane bioreactors

Predicting the concentrations of biological agents, such as bacterial cells and viral particles in water resource recovery facilities (WRRFs) is essential for monitoring emerging contaminants. Such predictive capabilities support efforts to protect public health and promote envir...