5 papers
Low-Resource Preference Adaptation of LLMs via Activation-Based Label Propagation
Alessio Galatolo, Meriem Beloucif
Adapting large language models to user-specific preferences is often constrained by the cost of human annotation, making preference optimisation impractical in low-resource setting…
SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures
Nedjma Ousidhoum, Junho Myung, Carla Perez-Almendros +27
We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an extended version of our manual…
Beyond Ethical Alignment: Evaluating LLMs as Artificial Moral Assistants
Alessio Galatolo, Luca Alberto Rappuoli, Katie Winkle +1
The recent rise in popularity of large language models (LLMs) has prompted considerable concerns about their moral capabilities. Although considerable effort has been dedicated to…
Visualising Policy-Reward Interplay to Inform Zeroth-Order Preference Optimisation of Large Language Models
Alessio Galatolo, Zhenbang Dai, Katie Winkle +1
Fine-tuning Large Language Models (LLMs) with first-order methods like back-propagation is computationally intensive. Zeroth-Order (ZO) optimisation uses function evaluations inste…
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation
Lia Shahnazaryan, Meriem Beloucif
Recent advancements in neural machine translation (NMT) have revolutionized the field, yet the dependency on extensive parallel corpora limits progress for low-resource languages a…