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arXiv:2603.19331v1 Announce Type: new Abstract: Boundary condition tuning is a fundamental step in patient-specific cardiovascular modeling. Despite an increase in offline training cost, recent methods …
arXiv:2603.19335v1 Announce Type: new Abstract: Post-training alignment has produced dozens of competing algorithms -- DPO, SimPO, KTO, GRPO, and others -- yet practitioners lack controlled …
arXiv:2603.19338v1 Announce Type: new Abstract: Non-linear activation functions play a pivotal role in on-device inference and training, as they not only consume substantial hardware resources …
arXiv:2603.19344v1 Announce Type: new Abstract: Weighted summation has remained the default input aggregation mechanism in artificial neurons since the earliest neural network models. While computationally …
arXiv:2603.19348v1 Announce Type: new Abstract: Current transformer language models are trained with uniform computational budgets across all layers, implicitly assuming layer homogeneity. We challenge this …
arXiv:2603.19349v1 Announce Type: new Abstract: Generative AI has transformed the economics of information production, making explanations, proofs, examples, and analyses available at very low cost. …
arXiv:2603.19360v1 Announce Type: new Abstract: Current auto-regressive (AR) LLMs, diffusion-based text/image generative models, and recent flow matching (FM) algorithms are capable of generating premium quality …
arXiv:2603.19397v1 Announce Type: new Abstract: Non-pharmaceutical interventions (NPIs), such as diagnostic testing and quarantine, are crucial for controlling infectious disease outbreaks but are often constrained …
arXiv:2603.19460v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance, but they often lack transparency. We introduce GeoLAN, a training framework that treats …
arXiv:2603.19463v1 Announce Type: new Abstract: We develop deep learning-based approximation methods for fully nonlinear second-order PDEs on separable Hilbert spaces, such as HJB equations for …
arXiv:2603.19465v1 Announce Type: new Abstract: We analyze a fixed-point iteration $v \leftarrow \phi(v)$ arising in the optimization of a regularized nuclear norm objective involving the …
arXiv:2603.19470v1 Announce Type: new Abstract: Off-policy problems such as policy staleness and training-inference mismatch, has become a major bottleneck for training stability and further exploration …