4 citations · 8 across the 7 of their papers we have counts for
5 papers · 1 filter
RecRankerEval: A Flexible and Extensible Framework for Top-k LLM-based Recommendation
Zeyuan Meng, Zixuan Yi, Iadh Ounis
A recent Large language model (LLM)-based recommendation model, called RecRanker, has demonstrated a superior performance in the top-k recommendation task compared to other models.…
KERAG_R: Knowledge-Enhanced Retrieval-Augmented Generation for Recommendation
Zeyuan Meng, Zixuan Yi, Iadh Ounis
Large Language Models (LLMs) have shown strong potential in recommender systems due to their contextual learning and generalisation capabilities. Existing LLM-based recommendation…
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…
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…
Contrastive Graph Prompt-tuning for Cross-domain Recommendation
Zixuan Yi, Iadh Ounis, Craig Macdonald
Recommender systems are frequently challenged by the data sparsity problem. One approach to mitigate this issue is through cross-domain recommendation techniques. In a cross-domain…