activity
20232026
most citedParameter-Efficient Continual Fine-Tuning: A Survey

7 citations · 10 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Book your room in the Turing Hotel! A symmetric and distributed Turing Test with multiple AIs and humans

Christian Di Maio, Tommaso Guidi, Luigi Quarantiello +4

In this paper, we report our experience with ``TuringHotel'', a novel extension of the Turing Test based on interactions within mixed communities of Large Language Models (LLMs) an…

cs.RO2025

A Compositional Paradigm for Foundation Models: Towards Smarter Robotic Agents

Luigi Quarantiello, Elia Piccoli, Jack Bell +8

The birth of Foundation Models brought unprecedented results in a wide range of tasks, from language to vision, to robotic control. These models are able to process huge quantities…

cs.LG2025

GLAM: Efficient Continual Learning at Scale via Grouped LoRA Adapter Merging

Irene Testa, Luigi Quarantiello, Eric Nuertey Coleman +3

The ability to learn continuously over time remains a major challenge for modern machine learning systems, even in the era of Foundation Models. While the rich representations lear…

cs.LG2025

Task-Agnostic Experts Composition for Continual Learning

Luigi Quarantiello, Andrea Cossu, Vincenzo Lomonaco

Compositionality is one of the fundamental abilities of the human reasoning process, that allows to decompose a complex problem into simpler elements. Such property is crucial also…

cs.LG2025★ 2 cited

The Future of Continual Learning in the Era of Foundation Models: Three Key Directions

Jack Bell, Luigi Quarantiello, Eric Nuertey Coleman +5

Continual learning--the ability to acquire, retain, and refine knowledge over time--has always been fundamental to intelligence, both human and artificial. Historically, different…

cs.LG2025★ 7 cited

Parameter-Efficient Continual Fine-Tuning: A Survey

Eric Nuertey Coleman, Luigi Quarantiello, Ziyue Liu +4

The emergence of large pre-trained networks has revolutionized the AI field, unlocking new possibilities and achieving unprecedented performance. However, these models inherit a fu…

cs.LG2023★ 1 cited

LuckyMera: a Modular AI Framework for Building Hybrid NetHack Agents

Luigi Quarantiello, Simone Marzeddu, Antonio Guzzi +1

In the last few decades we have witnessed a significant development in Artificial Intelligence (AI) thanks to the availability of a variety of testbeds, mostly based on simulated e…