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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…
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…
DIEKAE: Difference Injection for Efficient Knowledge Augmentation and Editing of Large Language Models
Alessio Galatolo, Meriem Beloucif, Katie Winkle
Pretrained Language Models (PLMs) store extensive knowledge within their weights, enabling them to recall vast amount of information. However, relying on this parametric knowledge…