13 papers
Optimising Factual Consistency in Summarisation via Preference Learning from Multiple Imperfect Metrics
Yuxuan Ye, Raul Santos-Rodriguez, Edwin Simpson
Reinforcement learning with evaluation metrics as rewards is widely used to enhance specific capabilities of language models. However, for tasks such as factually consistent summar…
Learning Generation Orders for Masked Discrete Diffusion Models via Variational Inference
David Fox, Sam Bowyer, Song Liu +3
Masked discrete diffusion models (MDMs) are a promising new approach to generative modelling, offering the ability for parallel token generation and therefore greater efficiency th…
Explainable AI for Classifying UTI Risk Groups Using a Real-World Linked EHR and Pathology Lab Dataset
Yujie Dai, Brian Sullivan, Axel Montout +8
The use of machine learning and AI on electronic health records (EHRs) holds substantial potential for clinical insight. However, this approach faces challenges due to data heterog…
Machine Learning for Climate Policy: Understanding Policy Progression in the European Green Deal
Patricia West, Michelle WL Wan, Alexander Hepburn +3
Climate change demands effective legislative action to mitigate its impacts. This study explores the application of machine learning (ML) to understand the progression of climate p…
Uncertainty assessment in satellite-based greenhouse gas emissions estimates using emulated atmospheric transport
Jeffrey N. Clark, Elena Fillola, Nawid Keshtmand +2
Monitoring greenhouse gas emissions and evaluating national inventories require efficient, scalable, and reliable inference methods. Top-down approaches, combined with recent advan…
Evaluating Perceptual Distance Models by Fitting Binomial Distributions to Two-Alternative Forced Choice Data
Alexander Hepburn, Raul Santos-Rodriguez, Javier Portilla
The Two Alternative Forced Choice (2AFC) paradigm offers advantages over the Mean Opinion Score (MOS) paradigm in psychophysics (PF), such as simplicity and robustness. However, wh…