1 citations · 2 across the 5 of their papers we have counts for
5 papers
EAGer: Entropy-Aware GEneRation for Adaptive Inference-Time Scaling
Daniel Scalena, Leonidas Zotos, Elisabetta Fersini +2
With the rise of reasoning language models and test-time scaling methods as a paradigm for improving model performance, substantial computation is often required to generate multip…
Steering Large Language Models for Machine Translation Personalization
Daniel Scalena, Gabriele Sarti, Arianna Bisazza +2
Large language models have simplified the production of personalized translations reflecting predefined stylistic constraints. However, these systems still struggle when stylistic…
A gentle push funziona benissimo: making instructed models in Italian via contrastive activation steering
Daniel Scalena, Elisabetta Fersini, Malvina Nissim
Adapting models to a language that was only partially present in the pre-training data requires fine-tuning, which is expensive in terms of both data and computational resources. A…
Multi-property Steering of Large Language Models with Dynamic Activation Composition
Daniel Scalena, Gabriele Sarti, Malvina Nissim
Activation steering methods were shown to be effective in conditioning language model generation by additively intervening over models' intermediate representations. However, the e…
Let the Models Respond: Interpreting Language Model Detoxification Through the Lens of Prompt Dependence
Daniel Scalena, Gabriele Sarti, Malvina Nissim +1
Due to language models' propensity to generate toxic or hateful responses, several techniques were developed to align model generations with users' preferences. Despite the effecti…