arXiv:2605.02317v1 Announce Type: new
Abstract: Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However, they often generalize worse than non-adaptive methods…
arXiv:2510.15949v4 Announce Type: replace-cross
Abstract: Large language models show promise for financial decision-making, yet deploying them as autonomous trading agents raises fundamental challenges: how to adapt instructions when rewards arrive la…
arXiv:2512.09169v2 Announce Type: replace-cross
Abstract: We present a novel multi-stage workflow for computational materials discovery that achieves a 99% success rate in identifying compounds within 100 meV/atom of thermodynamic stability, with a th…
arXiv:2602.00074v2 Announce Type: replace-cross
Abstract: While large language models (LLMs) can support clinical documentation needs, standalone tools struggle with “workflow friction” from manual data entry. We developed ChatEHR, a system that enabl…
arXiv:2605.02438v1 Announce Type: cross
Abstract: Open-set supervised anomaly detection (OSAD) aims to identify unseen anomalies using limited anomalous supervision. However, existing prototype-based methods typically model normal data via a unimodal …
arXiv:2605.00197v1 Announce Type: cross
Abstract: Studies attempting to simulate human behavior with $\textit{Silicon Societies}$ grow in numbers while LLM-only social networks have started appearing outside of controlled settings. However, the design…
arXiv:2605.02500v1 Announce Type: cross
Abstract: Sleep foundation models have recently demonstrated strong performance on in-domain polysomnography tasks, including sleep staging, apnea detection, and disease risk prediction. In this work, we investi…
arXiv:2605.02589v1 Announce Type: cross
Abstract: Optical Coherence Tomography (OCT) has become one of the most used imaging modality in ophthalmology. It provides high-resolution, non-invasive visualization of retinal microarchitecture. The automated…
arXiv:2605.00254v1 Announce Type: cross
Abstract: Mixture-of-experts (MoE) architectures have turned LLM serving into a cluster-scale workload in which communication consumes a considerable portion of LLM serving runtime. This has prompted industry to…
arXiv:2605.02651v1 Announce Type: cross
Abstract: Scientific peer review increasingly struggles to assess reproducibility at the scale and complexity of modern research output. Evaluating reproducibility requires reconstructing experimental dependenci…