25 citations · 29 across the 9 of their papers we have counts for
10 papers
A Computational Framework for Cross-Domain Mission Design and Onboard Cognitive Decision Support
J. de Curtò, Adrianne Schneider, Ricardo Yanez +18
The design of distributed autonomous systems for operation beyond reliable ground contact presents a fundamental tension: as round-trip communication latency grows, the set of deci…
Semantic Invariance in Agentic AI
I. de Zarzà, J. de Curtò, Jordi Cabot +2
Large Language Models (LLMs) increasingly serve as autonomous reasoning agents in decision support, scientific problem-solving, and multi-agent coordination systems. However, deplo…
LLM Constitutional Multi-Agent Governance
J. de Curtò, I. de Zarzà
Large Language Models (LLMs) can generate persuasive influence strategies that shift cooperative behavior in multi-agent populations, but a critical question remains: does the resu…
Cross-Platform Evaluation of Reasoning Capabilities in Foundation Models
J. de Curtò, I. de Zarzà, Pablo García +1
This paper presents a comprehensive cross-platform evaluation of reasoning capabilities in contemporary foundation models, establishing an infrastructure-agnostic benchmark across…
Advanced System Engineering Approaches to Emerging Challenges in Planetary and Deep-Space Exploration
J. de Curtò, Cristina LiCalzi, Julien Tubiana Warin +16
This paper presents innovative solutions to critical challenges in planetary and deep-space exploration electronics. We synthesize findings across diverse mission profiles, highlig…
Learning with Signatures
J. de Curtò, I. de Zarzà, Hong Yan +1
In this work we investigate the use of the Signature Transform in the context of Learning. Under this assumption, we advance a supervised framework that potentially provides state-…
Doctor of Crosswise: Reducing Over-parametrization in Neural Networks
J. D. Curtó, I. C. Zarza, Kris Kitani +2
Dr. of Crosswise proposes a new architecture to reduce over-parametrization in Neural Networks. It introduces an operand for rapid computation in the framework of Deep Learning tha…
High-resolution Deep Convolutional Generative Adversarial Networks
J. D. Curtó, I. C. Zarza, Fernando de la Torre +2
Generative Adversarial Networks (GANs) [Goodfellow et al. 2014] convergence in a high-resolution setting with a computational constrain of GPU memory capacity has been beset with d…
Segmentation of Objects by Hashing
J. D. Curtó, I. C. Zarza, Alex Smola +1
We propose a novel approach to address the problem of Simultaneous Detection and Segmentation introduced in [Hariharan et al 2014]. Using the hierarchical structures first presente…
McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
J. D. Curtó, I. C. Zarza, Feng Yang +4
McKernel introduces a framework to use kernel approximates in the mini-batch setting with Stochastic Gradient Descent (SGD) as an alternative to Deep Learning. Based on Random Kitc…