20 citations · 21 across the 6 of their papers we have counts for
6 papers
Not All Layers Are Created Equal: Adaptive LoRA Ranks for Personalized Image Generation
Donald Shenaj, Federico Errica, Antonio Carta
Low Rank Adaptation (LoRA) is the de facto fine-tuning strategy to generate personalized images from pre-trained diffusion models. Choosing a good rank is extremely critical, since…
Learn to Jump: Adaptive Random Walks for Long-Range Propagation through Graph Hierarchies
Joël Mathys, Federico Errica
Message-passing architectures struggle to sufficiently model long-range dependencies in node and graph prediction tasks. We propose a novel approach exploiting hierarchical graph s…
Variational Kolmogorov-Arnold Network
Francesco Alesiani, Henrik Christiansen, Federico Errica
Kolmogorov-Arnold Networks (KANs) offer a theoretically grounded alternative to multi-layer perceptrons by representing multivariate functions as compositions of univariate basis f…
Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning
Adrian Arnaiz-Rodriguez, Federico Errica
After a renaissance phase in which researchers revisited the message-passing paradigm through the lens of deep learning, the graph machine learning community shifted its attention…
What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering
Federico Errica, Giuseppe Siracusano, Davide Sanvito +1
Large Language Models (LLMs) changed the way we design and interact with software systems. Their ability to process and extract information from text has drastically improved produ…
History repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting
Julia Gastinger, Christian Meilicke, Federico Errica +3
Temporal Knowledge Graph (TKG) Forecasting aims at predicting links in Knowledge Graphs for future timesteps based on a history of Knowledge Graphs. To this day, standardized evalu…