3 papers
cs.LG2026
CIExplainer++: Generating Causal and Interpretable Explanations for Graph Neural Networks
Francisco Caldas, Sahil Satish Kumar, Ruben Belo +1
Explainable Artificial Intelligence aims to make black-box models more trustworthy by presenting, in a human-understandable manner, the elements that lead to the model's output. Th…
cs.IR2026
A Systematic Evaluation of Retrieval-Augmented Generation and Language Models for Space Operations
Ruben Belo, Marta Guimarães, Cláudia Soares
The rapid expansion of space activities has led to an unprecedented accumulation of technical documentation, operational guidelines, and scientific literature, creating challenges…
cs.LG2025
Keep Calm and Avoid Harmful Content: Concept Alignment and Latent Manipulation Towards Safer Answers
Ruben Belo, Marta Guimaraes, Claudia Soares
Large Language Models are susceptible to jailbreak attacks that bypass built-in safety guardrails (e.g., by tricking the model with adversarial prompts). We propose Concept Alignme…