The present and future of blended care: current research and introduction to the B-FIT framework

Depression subtype classification from social media posts: few-shot prompting vs. fine-tuning of large language models

BackgroundSocial media provides timely proxy signals of mental health, but reliable tweet-level classification of depression subtypes remains challenging due to short, noisy text, overlapping symptomatology,

MOSS-VoiceGenerator: Create Realistic Voices with Natural Language Descriptions

arXiv:2603.28086v1 Announce Type: cross Abstract: Voice design from natural language aims to generate speaker timbres directly from free-form textual descriptions, allowing users to create voices

Pre-Deployment Complexity Estimation for Federated Perception Systems

arXiv:2603.28282v1 Announce Type: cross Abstract: Edge AI systems increasingly rely on federated learning to train perception models in distributed, privacy-preserving, and resource-constrained environments. Yet, before

Robust Batch-Level Query Routing for Large Language Models under Cost and Capacity Constraints

arXiv:2603.26796v1 Announce Type: cross Abstract: We study the problem of routing queries to large language models (LLMs) under cost, GPU resources, and concurrency constraints. Prior

PiCSRL: Physics-Informed Contextual Spectral Reinforcement Learning

arXiv:2603.26816v1 Announce Type: cross Abstract: High-dimensional low-sample-size (HDLSS) datasets constrain reliable environmental model development, where labeled data remain sparse. Reinforcement learning (RL)-based adaptive sensing methods