arXiv:2603.24402v2 Announce Type: new Abstract: Existing automated research systems operate as stateless, linear pipelines — generating outputs without maintaining any persistent understanding of the research landscape they navigate. They process papers sequentially, propose ideas without structured gap analysis, and lack mechanisms for agents to verify, challenge, or refine each other’s findings. We present textbfAI-Supervisor, a […]
Environment Maps: Structured Environmental Representations for Long-Horizon Agents
arXiv:2603.23610v2 Announce Type: new Abstract: Although large language models (LLMs) have advanced rapidly, robust automation of complex software workflows remains an open problem. In long-horizon settings, agents frequently suffer from cascading errors and environmental stochasticity; a single misstep in a dynamic interface can lead to task failure, resulting in hallucinations or trial-and-error. This paper introduces […]
AI-Supervisor: Autonomous AI Research Supervision via a Persistent Research World Model
arXiv:2603.24402v2 Announce Type: new Abstract: Existing automated research systems operate as stateless, linear pipelines — generating outputs without maintaining any persistent understanding of the research landscape they navigate. They process papers sequentially, propose ideas without structured gap analysis, and lack mechanisms for agents to verify, challenge, or refine each other’s findings. We present textbfAI-Supervisor, a […]
Deep learning-based precision phenotyping of spine curvature identifies novel genetic risk loci for scoliosis in the UK Biobank
npj Digital Medicine, Published online: 26 March 2026; doi:10.1038/s41746-026-02540-6 Deep learning-based precision phenotyping of spine curvature identifies novel genetic risk loci for scoliosis in the UK Biobank
The present and future of blended care: current research and introduction to the B-FIT framework
npj Digital Medicine, Published online: 26 March 2026; doi:10.1038/s41746-026-02526-4 The present and future of blended care: current research and introduction to the B-FIT framework
Machine learning predicts sepsis deterioration trajectories
npj Digital Medicine, Published online: 26 March 2026; doi:10.1038/s41746-026-02565-x Machine learning predicts sepsis deterioration trajectories
Reimagining atrial fibrillation screening beyond age-based thresholds using AI
npj Digital Medicine, Published online: 26 March 2026; doi:10.1038/s41746-026-02485-w Atrial fibrillation (AF) affects over 50 million people worldwide and carries substantial downstream morbidity, mortality, and cost. Yet many contemporary screening programs rely primarily on age thresholds—an approach that is operationally simple but can be imprecise for identifying near-term risk. AI applied to handheld single-lead ECGs […]