11 papers
NARRAS: Edge-Triggered Distributed Inference for CSI-Based Localization in Vehicular IoT Networks
Rodrigo Oliver, Ricardo Vazquez Alvarez, Alejandro Lancho +1
CSI-based localization with spatially distributed antenna arrays exposes a basic resource trade-off. Each array can provide a rich view of the channel, but forwarding observations…
JGRA: Jacobian Geometry Robustness Assessment in NISQ Noise-Aware Quantum Neural Networks
Gianluca Scanu, Luca Barletta, Stefano Rini
The NISQ era places stringent constraints on quantum computation, where noise and decoherence fundamentally limit performance. In classical deep learning, model robustness and resi…
PolarZero: A Reinforcement Learning Approach for Low-Complexity Polarization Kernel Design
Yi-Ting Hong, Stefano Rini, Luca Barletta
Polar codes with large kernels can achieve improved error exponents but are challenging to design with low decoding complexity. This work investigates kernel construction under rec…
PAUSE: Low-Latency and Privacy-Aware Active User Selection for Federated Learning
Ori Peleg, Natalie Lang, Dan Ben Ami +3
Federated learning (FL) enables multiple edge devices to collaboratively train a machine learning model without the need to share potentially private data. Federated learning proce…
STSM-FiLM: A FiLM-Conditioned Neural Architecture for Time-Scale Modification of Speech
Dyah A. M. G. Wisnu, Ryandhimas E. Zezario, Stefano Rini +4
Time-Scale Modification (TSM) of speech aims to alter the playback rate of audio without changing its pitch. While classical methods like Waveform Similarity-based Overlap-Add (WSO…
Improving Perceptual Audio Aesthetic Assessment via Triplet Loss and Self-Supervised Embeddings
Dyah A. M. G. Wisnu, Ryandhimas E. Zezario, Stefano Rini +2
We present a system for automatic multi-axis perceptual quality prediction of generative audio, developed for Track 2 of the AudioMOS Challenge 2025. The task is to predict four Au…