7 citations · 25 across the 9 of their papers we have counts for
6 papers · 1 filter
Eliminating Hallucination in Diffusion-Augmented Interactive Text-to-Image Retrieval
Zhuocheng Zhang, Kangheng Liang, Guanxuan Li +3
Diffusion-Augmented Interactive Text-to-Image Retrieval (DAI-TIR) is a promising paradigm that improves retrieval performance by generating query images via diffusion models and us…
Diffusion Augmented Retrieval: A Training-Free Approach to Interactive Text-to-Image Retrieval
Zijun Long, Kangheng Liang, Gerardo Aragon-Camarasa +2
Interactive Text-to-image retrieval (I-TIR) is an important enabler for a wide range of state-of-the-art services in domains such as e-commerce and education. However, current meth…
CFIR: Fast and Effective Long-Text To Image Retrieval for Large Corpora
Zijun Long, Xuri Ge, Richard Mccreadie +1
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 datab…
Large Multi-modal Encoders for Recommendation
Zixuan Yi, Zijun Long, Iadh Ounis +2
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 e…
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models
Zaiqiao Meng, Richard McCreadie, Craig Macdonald +1
Effective methodologies for evaluating recommender systems are critical, so that such systems can be compared in a sound manner. A commonly overlooked aspect of recommender system…
Variational Bayesian Context-aware Representation for Grocery Recommendation
Zaiqiao Meng, Richard McCreadie, Craig Macdonald +1
Grocery recommendation is an important recommendation use-case, which aims to predict which items a user might choose to buy in the future, based on their shopping history. However…