5 papers · 1 filter
Component-Aware Differential Privacy for Federated Multilingual Speech-LLMs
Jordi Luque, Fernando López, Aleix Sant
Per-layer differential privacy (DP) clipping improves gradient fidelity in federated learning by allocating per-matrix clipping budgets proportional to parameter count. We show tha…
EuroAlpaca: Task-Preserving Localisation of Instruction Data for European Languages
Aleix Sant, Jordi Luque, Carlos Escolano
Machine translation (MT) offers a scalable way to extend English instruction-tuning data to multiple languages, but it can distort task-critical constraints and required outputs, c…
Optimizing Multilingual LLMs via Federated Learning: A Study of Client Language Composition
Aleix Sant, Jordi Luque, Carlos Escolano
Federated Learning (FL) of Large Language Models (LLMs) in multilingual environments presents significant challenges stemming from heterogeneous language distributions across clien…
The power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs
Aleix Sant, Carlos Escolano, Audrey Mash +2
This paper studies gender bias in machine translation through the lens of Large Language Models (LLMs). Four widely-used test sets are employed to benchmark various base LLMs, comp…
SpeechAlign: a Framework for Speech Translation Alignment Evaluation
Belen Alastruey, Aleix Sant, Gerard I. Gállego +2
Speech-to-Speech and Speech-to-Text translation are currently dynamic areas of research. In our commitment to advance these fields, we present SpeechAlign, a framework designed to…