48 citations · 140 across the 16 of their papers we have counts for
17 papers
Adaptive Semantic Token Communication for Transformer-based Edge Inference
Alessio Devoto, Jary Pomponi, Mattia Merluzzi +2
This paper presents an adaptive framework for edge inference based on a dynamically configurable transformer-powered deep joint source channel coding (DJSCC) architecture. Motivate…
Goal-oriented Communications based on Recursive Early Exit Neural Networks
Jary Pomponi, Mattia Merluzzi, Alessio Devoto +3
This paper presents a novel framework for goal-oriented semantic communications leveraging recursive early exit models. The proposed approach is built on two key components. First,…
Adaptive Layer Selection for Efficient Vision Transformer Fine-Tuning
Alessio Devoto, Federico Alvetreti, Jary Pomponi +3
Recently, foundation models based on Vision Transformers (ViTs) have become widely available. However, their fine-tuning process is highly resource-intensive, and it hinders their…
How to Train Your Multi-Exit Model? Analyzing the Impact of Training Strategies
Piotr Kubaty, Bartosz Wójcik, Bartłomiej Krzepkowski +4
Early exits enable the network's forward pass to terminate early by attaching trainable internal classifiers to the backbone network. Existing early-exit methods typically adopt ei…
Adaptive Semantic Token Selection for AI-native Goal-oriented Communications
Alessio Devoto, Simone Petruzzi, Jary Pomponi +2
In this paper, we propose a novel design for AI-native goal-oriented communications, exploiting transformer neural networks under dynamic inference constraints on bandwidth and com…
Conditional computation in neural networks: principles and research trends
Simone Scardapane, Alessandro Baiocchi, Alessio Devoto +3
This article summarizes principles and ideas from the emerging area of applying \textit{conditional computation} methods to the design of neural networks. In particular, we focus o…