no code implementations • 10 Mar 2024 • Zijun Long, Lipeng Zhuang, George Killick, Richard McCreadie, Gerardo Aragon Camarasa, Paul Henderson
In this paper, we show that human-labelling errors not only differ significantly from synthetic label errors, but also pose unique challenges in SCL, different to those in traditional supervised learning methods.
no code implementations • 23 Feb 2024 • Zijun Long, Xuri Ge, Richard McCreadie, Joemon Jose
Text-to-image retrieval aims to find the relevant images based on a text query, which is important in various use-cases, such as digital libraries, e-commerce, and multimedia databases.
no code implementations • 22 Feb 2024 • Zijun Long, George Killick, Lipeng Zhuang, Gerardo Aragon-Camarasa, Zaiqiao Meng, Richard McCreadie
State-of-the-art pre-trained image models predominantly adopt a two-stage approach: initial unsupervised pre-training on large-scale datasets followed by task-specific fine-tuning using Cross-Entropy loss~(CE).
1 code implementation • 5 Jan 2024 • Zijun Long, Richard McCreadie, Muhammad Imran
We leverage the new Incidents1M crisis image dataset to develop a range of new transformer-based image classification models.
no code implementations • 25 Nov 2023 • Zijun Long, George Killick, Lipeng Zhuang, Richard McCreadie, Gerardo Aragon Camarasa, Paul Henderson
However, while the detrimental effects of noisy labels in supervised learning are well-researched, their influence on SCL remains largely unexplored.
no code implementations • 31 Oct 2023 • Zixuan Yi, Zijun Long, Iadh Ounis, Craig Macdonald, Richard McCreadie
In recent years, the rapid growth of online multimedia services, such as e-commerce platforms, has necessitated the development of personalised recommendation approaches that can encode diverse content about each item.
1 code implementation • 16 Oct 2023 • Zijun Long, George Killick, Richard McCreadie, Gerardo Aragon Camarasa
Robotic vision applications often necessitate a wide range of visual perception tasks, such as object detection, segmentation, and identification.
1 code implementation • 4 Sep 2023 • Zijun Long, George Killick, Richard McCreadie, Gerardo Aragon Camarasa
As Multimodal Large Language Models (MLLMs) grow in size, adapting them to specialized tasks becomes increasingly challenging due to high computational and memory demands.
no code implementations • 28 Aug 2023 • Zijun Long, George Killick, Richard McCreadie, Gerardo Aragon Camarasa, Zaiqiao Meng
State-of-the-art image models predominantly follow a two-stage strategy: pre-training on large datasets and fine-tuning with cross-entropy loss.
1 code implementation • 31 Mar 2023 • Zijun Long, Zaiqiao Meng, Gerardo Aragon Camarasa, Richard McCreadie
Vision Transformers (ViTs) have emerged as popular models in computer vision, demonstrating state-of-the-art performance across various tasks.
no code implementations • 11 Feb 2023 • Alexander Pugantsov, Richard McCreadie
Through experimentation over 58 tasks and over 6, 600 task pair combinations, we demonstrate that statistical measures can distinguish effective task pairs, and the resulting estimates can reduce end-to-end runtime by up to 40%.
no code implementations • 2 Feb 2022 • Alexander J. Hepburn, Richard McCreadie
In this paper, we leverage explainability techniques to effectively predict whether task pairs will be complementary, through comparison of neural network activation between single-task models.
no code implementations • 26 Jul 2020 • Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis
In this paper, we both show that there is no standard splitting strategy and that the selection of splitting strategy can have a strong impact on the ranking of recommender systems.
1 code implementation • 17 Sep 2019 • Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis
We train our VBCAR model based on the Bayesian Skip-gram framework coupled with the amortized variational inference so that it can learn more expressive latent representations that integrate both the non-linearity and Bayesian behaviour.
no code implementations • ACL 2014 • Miles Osborne, Sean Moran, Richard McCreadie, Alex Von Lunen, er, Martin Sykora, Elizabeth Cano, Neil Ireson, Craig Macdonald, Iadh Ounis, Yulan He, Tom Jackson, Fabio Ciravegna, Ann O{'}Brien