arXiv:2602.03730v2 Announce Type: replace
Abstract: Generative foundation models trained on tokenized electronic health record (EHR) timelines show promise for clinical outcome prediction via Monte Carlo sampling of simulated future trajectories. Howe…
arXiv:2605.13318v1 Announce Type: new
Abstract: Chatbot usage has increased, including in fields for which they were never developed for–notably mental health support. To that end, we introduce Validations of Ethical and Responsible AI in Mental Heal…
arXiv:2605.08935v2 Announce Type: replace
Abstract: Coupled spatiotemporal forecasting is important for predicting the future evolution of multiple interacting dynamical systems, such as in climate models. However, existing methods are severely constr…
arXiv:2605.12977v1 Announce Type: cross
Abstract: Estimating the covariance of asset returns, i.e., the risk model, is a key component of financial portfolio construction and evaluation. Most risk modeling approaches produce a factor model that decomp…
arXiv:2602.11202v3 Announce Type: replace-cross
Abstract: Reasoning models produce long traces of intermediate decisions and tool calls, making test-time verification important for ensuring correctness. Existing approaches either verify only the final…
arXiv:2605.13542v1 Announce Type: new
Abstract: Intensive care units (ICU) generate long, dense and evolving streams of clinical information, where physicians must repeatedly reassess patient states under time pressure, underscoring a clear need for r…
arXiv:2605.13625v1 Announce Type: new
Abstract: Autonomous agents such as Claude Code and Codex now operate for hours or even days. Understanding their runtime behavior has become critical for downstream tasks such as diagnosing inefficiencies, fixing…
arXiv:2605.13725v1 Announce Type: new
Abstract: Large language model (LLM)-based multi-agent simulation offers a powerful testbed for studying social opinion dynamics. Yet current approaches often adopt two contrasting methods: either relying on fixed…
arXiv:2605.12570v1 Announce Type: new
Abstract: The accurate classification of benign and malignant pulmonary nodules in CT scans is critical for early lung cancer screening, yet remains challenging due to the multi-scale and heterogeneous nature of p…
arXiv:2605.13821v1 Announce Type: new
Abstract: Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, evaluating them, and using feedback to guide future …