Large language models for recommendation: Progresses and future directions
The powerful large language models (LLMs) have played a pivotal role in advancing
recommender systems. Recently, in both academia and industry, there has been a surge of …
recommender systems. Recently, in both academia and industry, there has been a surge of …
Llmrec: Large language models with graph augmentation for recommendation
The problem of data sparsity has long been a challenge in recommendation systems, and
previous studies have attempted to address this issue by incorporating side information …
previous studies have attempted to address this issue by incorporating side information …
Towards open-world recommendation with knowledge augmentation from large language models
Recommender systems play a vital role in various online services. However, the insulated
nature of training and deploying separately within a specific domain limits their access to …
nature of training and deploying separately within a specific domain limits their access to …
Leveraging large language models for sequential recommendation
J Harte, W Zorgdrager, P Louridas… - Proceedings of the 17th …, 2023 - dl.acm.org
Sequential recommendation problems have received increasing attention in research during
the past few years, leading to the inception of a large variety of algorithmic approaches. In …
the past few years, leading to the inception of a large variety of algorithmic approaches. In …
Representation learning with large language models for recommendation
Recommender systems have seen significant advancements with the influence of deep
learning and graph neural networks, particularly in capturing complex user-item …
learning and graph neural networks, particularly in capturing complex user-item …
Adapting large language models by integrating collaborative semantics for recommendation
Recently, large language models (LLMs) have shown great potential in recommender
systems, either improving existing recommendation models or serving as the backbone …
systems, either improving existing recommendation models or serving as the backbone …
Llara: Large language-recommendation assistant
Sequential recommendation aims to predict users' next interaction with items based on their
past engagement sequence. Recently, the advent of Large Language Models (LLMs) has …
past engagement sequence. Recently, the advent of Large Language Models (LLMs) has …
Prompting large language models for recommender systems: A comprehensive framework and empirical analysis
Recently, large language models such as ChatGPT have showcased remarkable abilities in
solving general tasks, demonstrating the potential for applications in recommender systems …
solving general tasks, demonstrating the potential for applications in recommender systems …
How can recommender systems benefit from large language models: A survey
With the rapid development of online services, recommender systems (RS) have become
increasingly indispensable for mitigating information overload. Despite remarkable …
increasingly indispensable for mitigating information overload. Despite remarkable …
A content-driven micro-video recommendation dataset at scale
Micro-videos have recently gained immense popularity, sparking critical research in micro-
video recommendation with significant implications for the entertainment, advertising, and e …
video recommendation with significant implications for the entertainment, advertising, and e …