MOLPAQ is a novel modular quantum-classical generator that creates interpretable molecules from quantum-generated latent patches, achieving 100% RDKit validity and high novelty and diversity. This approach significantly improves property control, such as QED and aromatic motif incidence, over classical generators.
Vision-Language Models (VLMs) can exhibit catastrophic failures in real-world situations despite their broad reasoning capabilities. REVELIO is introduced as a framework to systematically uncover interpretable failure modes in VLMs by combining diversity-aware beam search and Gaussian-process Thompson Sampling to map the failure landscape.
O artigo aborda a aplicação de Aprendizado por Reforço Profundo interpretável para a otimização do ciclo de vida de pontes em nível de elemento. Ele busca oferecer transparência e eficiência na gestão da infraestrutura.
This paper proposes a novel method called forecast-necessity testing for interpretable causal discovery in nonlinear time-series models. It aims to move beyond traditional coefficients to better understand complex causal relationships.