arXiv:2603.28987v1 Announce Type: cross
Abstract: Aircraft design relies heavily on solving challenging and computationally expensive Multidisciplinary Design Optimization problems. In this context, there has been growing interest in multi-fidelity mo…
arXiv:2603.29889v1 Announce Type: cross
Abstract: This paper develops a penalized GMM (PGMM) framework for automatic debiased inference on functionals of nonparametric instrumental variable estimators. We derive convergence rates for the PGMM estimato…
arXiv:2504.15543v3 Announce Type: replace-cross
Abstract: Computer Adaptive Testing (CAT) aims to accurately estimate an individual’s ability using only a subset of an Item Response Theory (IRT) instrument. Many applications also require diverse item …
arXiv:2603.29957v1 Announce Type: cross
Abstract: Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answer. However, this approach suffers from critical limitations…
arXiv:2603.28336v2 Announce Type: replace-cross
Abstract: Systematic literature reviews in the social sciences overwhelmingly follow arborescent logics — hierarchical keyword filtering, linear screening, and taxonomic classification — that suppress …
arXiv:2603.26782v2 Announce Type: replace-cross
Abstract: Text-to-level generation aims to translate natural language descriptions into structured game levels, enabling intuitive control over procedural content generation. While prior text-to-level ge…
arXiv:2603.24436v3 Announce Type: replace-cross
Abstract: Enes The proposed architecture is a mixture of experts, which allows for the model entities, such as the causal relationships, to be further parameterized. More specifically, an attempt is made…
arXiv:2603.29915v1 Announce Type: cross
Abstract: Post-hoc explanation methods are widely used to interpret black-box predictions, but their generation is often computationally expensive and their reliability is not guaranteed. We propose epistemic un…
arXiv:2603.22779v2 Announce Type: replace-cross
Abstract: Large Language Models (LLMs) are equipped with profound semantic knowledge, making them a natural choice for injecting semantic generalization into personalized search systems. However, in prac…
arXiv:2603.29905v1 Announce Type: cross
Abstract: We propose a new frame work of $p$-adic neural network. Unlike the original $p$-adic neural network by S.\ Albeverio, A.\ Khrennikov, and B.\ Tirrozi using a family of characteristic functions indexed …