1 citations · 1 across the 7 of their papers we have counts for
7 papers
Verifier-guided discovery of exact high-order mimetic operators with large language models
J. de Curtò, I. de Zarzà
Designing a high-order structure-preserving discretization is a constrained mathematical search: conservation, a positive discrete inner product, physical spectral behavior, bounda…
Visual Grounding in Zero-Shot Vision-Language Control
J. de Curtò, Dayani Plasencia, Diego Sánchez +1
Vision-language models (VLMs) are increasingly used as zero-shot controllers, but successful trajectories do not necessarily show that decisions are grounded in visual input: simul…
Strategic Evaluation of Planning Strategies for LLM Agents in Cyber-Physical Systems
J. de Curtò, I. de Zarzà
LLM-agent evaluations commonly measure task success or agreement with a declared plan. In strategic cyber-physical systems, an architecture must also remain appropriate after auton…
Collective Intelligence with Foundation Models
J. de Curtò, I. de Zarzà
As foundation models grow in scale and diversity, coordinating multiple models into cooperative reasoning systems offers a path toward safer, more reliable AI. This chapter present…
Foundation Models for Automatic CAD Generation
J de Curtò, Victoria Guillén, I. de Zarzà
Recent advances in Large Language Models (LLMs) and Vision-Language Models (VLMs) enable the automatic generation of parametric 3D designs from natural-language specifications. Thi…
LLM-Mediated Demand Response Coordination in Smart Microgrids
J. de Curtò, I. de Zarzà
Effective demand response in smart microgrids requires prosumers to cooperate voluntarily under strategic self-interest, a coordination problem structurally equivalent to a repeate…
Signature and Log-signature for the Study of Empirical Distributions Generated with GANs
Joaquim de Curtò, Irene de Zarzà, Hong Yan +1
In this paper, we bring forward the use of the recently developed Signature Transform as a way to measure the similarity between image distributions and provide detailed acquaintan…