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arXiv:2603.22525v1 Announce Type: new Abstract: Operator learning models are rapidly emerging as the predictive core of digital twins for nuclear and energy systems, promising real-time …
arXiv:2603.22530v1 Announce Type: new Abstract: Unstructured Electronic Health Record (EHR) data, such as clinical notes, contain clinical contextual observations that are not directly reflected in …
arXiv:2603.22586v1 Announce Type: new Abstract: In-context learning (ICL) allows a model to adapt at inference time by conditioning on examples rather than updating parameters. Existing …
Abstract The governance of emerging technologies with increased autonomy in the military has become a topical issue in recent years, especially considering the rapid advances …
arXiv:2603.20505v1 Announce Type: new Abstract: Probabilistic Logic Programming (PLP) languages, like ProbLog, naturally support reasoning under uncertainty, while maintaining a declarative and interpretable framework. Meanwhile, …
arXiv:2603.20988v1 Announce Type: new Abstract: The cognitive sciences aim to understand intelligence by formalizing underlying operations as computational models. Traditionally, this follows a cycle of …
arXiv:2603.20224v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate exceptional performance across diverse tasks but come with substantial energy and computational costs, particularly in …
arXiv:2603.21250v1 Announce Type: new Abstract: Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former two, abductive …
arXiv:2603.20210v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) provide an efficient non-causal alternative to autoregressive generation but often struggle with token dependencies and semantic …
arXiv:2603.20578v1 Announce Type: new Abstract: The prevailing approach to improving large language model (LLM) reasoning has centered on expanding context windows, implicitly assuming that more …
arXiv:2603.20537v1 Announce Type: new Abstract: Industrial process control demands policies that are interpretable and auditable, requirements that black-box neural policies struggle to meet. We study …
arXiv:2603.21029v1 Announce Type: new Abstract: Autonomous driving requires reliable reasoning over fine-grained 3D scene facts. Fine-grained question answering over multi-modal driving observations provides a natural …