Institute of Automation

Cloud‐Native and Distributed Systems for Efficient and Scalable Large Language Models—A Research Agenda

ABSTRACT Objective Large Language Models (LLMs) are rapidly transforming artificial intelligence applications, but their unprecedented computational, memory, communication, and data‐management demands pose significant challenges to existing computing infrastructures. Traditional...

A generalizable biopsychosocial risk score for stratifying disease vulnerability in healthy populations

Prospective risk stratification of future adverse health outcomes before clinical onset among ostensibly healthy individuals is an important goal of preventive and precision medicine, yet current tools remain largely disease-specific and do not provide an integrated measure of he...

Plug-and-Play Dramaturge: A Divide-and-Conquer Approach for Iterative Narrative Script Refinement via Collaborative LLM Agents

Although LLMs have been widely adopted for creative content generation, a single-pass process often struggles to produce high-quality long narratives. How to effectively revise and improve long narrative scripts like scriptwriters remains a significant challenge, as it demands a...

Adaptive graph structure learning for skeleton-based gait recognition

Gait recognition, which identifies individuals based on their walking patterns, offers a contactless and robust biometric approach. Skeleton-based gait recognition using graph convolutional networks (GCNs) is favored for its robustness against external variations, such as clothin...

Microrobots for Precision Diagnosis and Treatment in the Digestive System: A Review of Actuation Mechanisms, Structural Design, Preclinical and Translational Applications

Because lesions associated with digestive system diseases are often deeply seated, embedded within complex luminal milieus, and protected by substantial local delivery barriers, conventional diagnostic and therapeutic modalities remain constrained in their targeting capability, m...