3 citations · 6 across the 10 of their papers we have counts for
10 papers
Instruction-Directed MAC for Efficient Classical Communication in Scalable Multi-Chip Quantum Systems
Maurizio Palesi, Enrico Russo, Hamaad Rafique +4
Scalable quantum computing requires modular multi-chip architectures integrating multiple quantum cores interconnected through quantum-coherent and classical links. The classical c…
Brain-Language Model Alignment: Insights into the Platonic Hypothesis and Intermediate-Layer Advantage
Ángela López-Cardona, Sebastián Idesis, Mireia Masias-Bruns +2
Do brains and language models converge toward the same internal representations of the world? Recent years have seen a rise in studies of neural activations and model alignment. In…
Quantum Computing for Large-scale Network Optimization: Opportunities and Challenges
Sebastian Macaluso, Giovanni Geraci, Elías F. Combarro +4
The complexity of large-scale 6G-and-beyond networks demands innovative approaches for multi-objective optimization over vast search spaces, a task often intractable. Quantum compu…
Experimental Assessment of Neural 3D Reconstruction for Small UAV-based Applications
Genís Castillo Gómez-Raya, Álmos Veres-Vitályos, Filip Lemic +5
The increasing miniaturization of Unmanned Aerial Vehicles (UAVs) has expanded their deployment potential to indoor and hard-to-reach areas. However, this trend introduces distinct…
Beyond One-Size-Fits-All: A Study of Neural and Behavioural Variability Across Different Recommendation Categories
Georgios Koutroumpas, Sebastian Idesis, Mireia Masias Bruns +4
Traditionally, Recommender Systems (RS) have primarily measured performance based on the accuracy and relevance of their recommendations. However, this algorithmic-centric approach…
TRMAC: A Time-Reversal-based MAC Protocol for Wireless Networks within Computing Packages
Ama Bandara, Abhijit Das, Fatima Rodriguez-Galan +2
As chiplet-based integration and many-core architectures become the norm in high-performance computing, on-chip wireless communication has emerged as a compelling alternative to tr…
OASST-ETC Dataset: Alignment Signals from Eye-tracking Analysis of LLM Responses
Angela Lopez-Cardona, Sebastian Idesis, Miguel Barreda-Ángeles +2
While Large Language Models (LLMs) have significantly advanced natural language processing, aligning them with human preferences remains an open challenge. Although current alignme…
Exploring the Potential of Wireless-enabled Multi-Chip AI Accelerators
Emmanuel Irabor, Mariam Musavi, Abhijit Das +1
The insatiable appetite of Artificial Intelligence (AI) workloads for computing power is pushing the industry to develop faster and more efficient accelerators. The rigidity of cus…
A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference
Pol Puigdemont, Enrico Russo, Axel Wassington +3
Graph Neural Networks (GNNs) have shown significant promise in various domains, such as recommendation systems, bioinformatics, and network analysis. However, the irregularity of g…
Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Models
Angela Lopez-Cardona, Carlos Segura, Alexandros Karatzoglou +2
Advancements in Natural Language Processing (NLP), have led to the emergence of Large Language Models (LLMs) such as GPT, Llama, Claude, and Gemini, which excel across a range of t…