HEARTS: Benchmarking LLM Reasoning on Health Time Series
arXiv:2603.06638v1 Announce Type: new Abstract: The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing …
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arXiv:2603.06638v1 Announce Type: new Abstract: The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing …
arXiv:2603.06642v1 Announce Type: new Abstract: Test-Time Training (TTT) language models achieve theoretically infinite context windows with an O(1) memory footprint by replacing the standard exact-attention …
arXiv:2603.06646v1 Announce Type: new Abstract: This paper presents a trust aware federated learning (FL) framework for interpreting bone healing stages using spectral features derived from …
arXiv:2603.06649v1 Announce Type: new Abstract: The coastal regions of the eastern and southern United States are impacted by severe storm events, leading to significant loss …
arXiv:2603.06651v1 Announce Type: new Abstract: Euclidean gradient descent algorithms barely capture the geometry of objective function-induced hypersurfaces and risk driving update trajectories off the hypersurfaces. …
arXiv:2603.06671v1 Announce Type: new Abstract: Financial risk detection in Enterprise Resource Planning (ERP) systems is an important but underexplored application of machine learning. Published studies …
arXiv:2603.06685v1 Announce Type: new Abstract: Stochastic differential equation (SDE)-based generative models have achieved substantial progress in conditional generation via training-free differentiable loss-guided approaches. However, existing …
arXiv:2603.06713v1 Announce Type: new Abstract: Agentic systems operating over large tool ecosystems must plan and execute long-horizon workflows under weak or non-verifiable supervision. While frontier …
arXiv:2603.06720v1 Announce Type: new Abstract: Access to electronic health records (EHRs) for digital health research is often limited by privacy regulations and institutional barriers. Synthetic …
arXiv:2603.06722v1 Announce Type: new Abstract: Protein language models often take into consideration the alignment between a protein sequence and its textual description. However, they do …
arXiv:2603.06724v1 Announce Type: new Abstract: Indoor air quality (IAQ) forecasting plays a critical role in safeguarding occupant health, ensuring thermal comfort, and supporting intelligent building …
arXiv:2603.06726v1 Announce Type: new Abstract: Electricity market prices exhibit extreme volatility, nonlinearity, and non-stationarity, making accurate forecasting a significant challenge. While cutting-edge time series foundation …