57 citations · 180 across the 49 of their papers we have counts for
6 papers · 1 filter
A Unified Graph Transformer for Overcoming Isolations in Multi-modal Recommendation
Zixuan Yi, Iadh Ounis
With the rapid development of online multimedia services, especially in e-commerce platforms, there is a pressing need for personalised recommendation systems that can effectively…
FusionDTI: Fine-grained Binding Discovery with Token-level Fusion for Drug-Target Interaction
Zhaohan Meng, Zaiqiao Meng, Ke Yuan +1
Predicting drug-target interaction (DTI) is critical in the drug discovery process. Despite remarkable advances in recent DTI models through the integration of representations from…
Generative Relevance Feedback and Convergence of Adaptive Re-Ranking: University of Glasgow Terrier Team at TREC DL 2023
Andrew Parry, Thomas Jaenich, Sean MacAvaney +1
This paper describes our participation in the TREC 2023 Deep Learning Track. We submitted runs that apply generative relevance feedback from a large language model in both a zero-s…
A Directional Diffusion Graph Transformer for Recommendation
Zixuan Yi, Xi Wang, Iadh Ounis
In real-world recommender systems, implicitly collected user feedback, while abundant, often includes noisy false-positive and false-negative interactions. The possible misinterpre…
One size doesn't fit all: Predicting the Number of Examples for In-Context Learning
Manish Chandra, Debasis Ganguly, Iadh Ounis
In-context learning (ICL) refers to the process of adding a small number of localized examples from a training set of labelled data to an LLM's prompt with an objective to effectiv…
Query Exposure Prediction for Groups of Documents in Rankings
Thomas Jaenich, Graham McDonald, Iadh Ounis
The main objective of an Information Retrieval system is to provide a user with the most relevant documents to the user's query. To do this, modern IR systems typically deploy a re…