arXiv:2604.23385v1 Announce Type: new
Abstract: Transthoracic echocardiography is the reference standard for confirming structural heart disease (SHD), but first-line screening is limited by cost, workflow burden, and specialist availability. We evalu…
arXiv:2512.11367v2 Announce Type: replace-cross
Abstract: Illegal, unreported, and unregulated (IUU) fishing causes global economic losses of 10-25 billion USD annually and undermines marine sustainability and governance. Synthetic Aperture Radar (SAR…
arXiv:2604.23465v1 Announce Type: new
Abstract: Single-arm trials accelerate study timelines by reducing the number of patients that must be recruited for a concurrent control group. However, these designs require an alternative comparator to estimate…
arXiv:2604.24634v1 Announce Type: cross
Abstract: Light-activated drugs are a promising way to treat localized diseases for which existing treatments have severe side effects. However, their development is complicated by the set of photophysical and b…
arXiv:2604.23758v1 Announce Type: new
Abstract: The discovery of novel materials is critical for global energy and quantum technology transitions. While deep learning has fundamentally reshaped this landscape, existing predictive or generative models …
arXiv:2505.02922v3 Announce Type: replace
Abstract: Recent large language models (LLMs) are rapidly extending their context windows, yet inference throughput lags due to increasing GPU memory and bandwidth demands. This is because the key-value (KV) c…
arXiv:2604.23838v1 Announce Type: new
Abstract: We present JigsawRL, a cost-efficient framework that explores Pipeline Multiplexing as a new dimension of RL parallelism. JigsawRL decomposes each pipeline into a Sub-Stage Graph that exposes the intra-s…
arXiv:2602.06542v3 Announce Type: replace
Abstract: Deep knowledge tracing models have achieved significant breakthroughs in modeling student learning trajectories. However, these architectures require substantial training time and are prone to overfi…
arXiv:2604.23933v1 Announce Type: new
Abstract: Developing robust and clinically reliable EEG biomarkers requires evaluation frameworks that explicitly address cross population generalization in multi site settings such as Parkinsons disease (PD) dete…
arXiv:2509.00747v2 Announce Type: replace-cross
Abstract: Learning with physical systems is an emerging paradigm that seeks to harness the intrinsic nonlinear dynamics of physical substrates for learning. The impetus for a paradigm shift in how hardwa…