Quality follows upgrading
Category
arXiv:2604.01411v1 Announce Type: new Abstract: Modern LLMs scale at test-time, e.g. via repeated sampling, where inference cost grows with model size and the number of …
arXiv:2604.01378v1 Announce Type: new Abstract: Offline reinforcement learning (RL) has received increasing attention for learning policies from previously collected data without interaction with the real …
arXiv:2604.01349v1 Announce Type: new Abstract: Reservoir simulation workflows face a fundamental data asymmetry: input parameter fields (geostatistical permeability realizations, porosity distributions) are free to generate …
arXiv:2604.01345v1 Announce Type: new Abstract: Inverse reinforcement learning (IRL) recovers the loss function of a forward learner from its observed responses adaptive IRL aims to …
arXiv:2604.01342v1 Announce Type: new Abstract: Multivariate Hawkes processes are a widely used class of self-exciting point processes, but maximum likelihood estimation naively scales as $O(N^2)$ …
arXiv:2604.01337v1 Announce Type: new Abstract: While deep learning has significantly advanced accident anticipation, the robustness of these safety-critical systems against real-world perturbations remains a major …
arXiv:2604.01329v1 Announce Type: new Abstract: Model merging provides a way of cheaply combining individual models to produce a model that inherits each individual's capabilities. While …
arXiv:2604.01328v1 Announce Type: new Abstract: Traditional scientific discovery relies on an iterative hypothesise-experiment-refine cycle that has driven progress for centuries, but its intuitive, ad-hoc implementation …
arXiv:2604.01315v1 Announce Type: new Abstract: Money launderers take advantage of limitations in existing detection approaches by hiding their financial footprints in a deceitful manner. They …
arXiv:2604.01313v1 Announce Type: new Abstract: High-fidelity Monte Carlo simulations and complex inverse problems, such as mapping smeared experimental observations to ground-truth states, are computationally intensive …
arXiv:2604.01308v1 Announce Type: new Abstract: Designing reliable integrated energy systems for industrial processes requires optimization and verification models across multiple fidelities, from architecture-level sizing to …
arXiv:2604.01305v1 Announce Type: new Abstract: Reconstructing high-dimensional spatiotemporal fields from sparse sensor measurements is critical in a wide range of scientific applications. The SHallow REcurrent …
