4 papers
Cluster, Route, Escalate: Cascaded Framework for Cost-Aware LLM Serving
Yasmin Moslem, Magdalena Kacmajor, Vasudevan Nedumpozhimana +11
Efficient deployment of large language models (LLMs) in production forces a trade-off between accuracy and cost. Operators often default to a single model that is either expensive…
Grammar-Guided Evolutionary Search for Discrete Prompt Optimisation
Muzhaffar Hazman, Minh-Khoi Pham, Shweta Soundararajan +10
Prompt engineering has proven to be a crucial step in leveraging pretrained large language models (LLMs) in solving various real-world tasks. Numerous solutions have been proposed…
UCB-driven Utility Function Search for Multi-objective Reinforcement Learning
Yucheng Shi, David Lynch, Alexandros Agapitos
In Multi-objective Reinforcement Learning (MORL) agents are tasked with optimising decision-making behaviours that trade-off between multiple, possibly conflicting, objectives. MOR…
Continual Model-based Reinforcement Learning for Data Efficient Wireless Network Optimisation
Cengis Hasan, Alexandros Agapitos, David Lynch +4
We present a method that addresses the pain point of long lead-time required to deploy cell-level parameter optimisation policies to new wireless network sites. Given a sequence of…