7 citations · 10 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
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…
In-context Interference in Chat-based Large Language Models
Eric Nuertey Coleman, Julio Hurtado, Vincenzo Lomonaco
Large language models (LLMs) have had a huge impact on society due to their impressive capabilities and vast knowledge of the world. Various applications and tools have been create…