Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an important component of our daily life, providing personalized suggestions …
have become an important component of our daily life, providing personalized suggestions …
Self-supervised learning for recommender systems: A survey
In recent years, neural architecture-based recommender systems have achieved
tremendous success, but they still fall short of expectation when dealing with highly sparse …
tremendous success, but they still fall short of expectation when dealing with highly sparse …
Large language models are zero-shot rankers for recommender systems
Recently, large language models (LLMs)(eg, GPT-4) have demonstrated impressive general-
purpose task-solving abilities, including the potential to approach recommendation tasks …
purpose task-solving abilities, including the potential to approach recommendation tasks …
Recommendation as instruction following: A large language model empowered recommendation approach
In the past decades, recommender systems have attracted much attention in both research
and industry communities, and a large number of studies have been devoted to developing …
and industry communities, and a large number of studies have been devoted to developing …
Recommender systems with generative retrieval
Modern recommender systems perform large-scale retrieval by embedding queries and item
candidates in the same unified space, followed by approximate nearest neighbor search to …
candidates in the same unified space, followed by approximate nearest neighbor search to …
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 …
Pre-train, Prompt, and Recommendation: A Comprehensive Survey of Language Modeling Paradigm Adaptations in Recommender Systems
The emergence of Pre-trained Language Models (PLMs) has achieved tremendous success
in the field of Natural Language Processing (NLP) by learning universal representations on …
in the field of Natural Language Processing (NLP) by learning universal representations on …
When large language models meet personalization: Perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …
intelligence. With the unprecedented scale of training and model parameters, the capability …
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 …
Large language models for generative recommendation: A survey and visionary discussions
Recent years have witnessed the wide adoption of large language models (LLM) in different
fields, especially natural language processing and computer vision. Such a trend can also …
fields, especially natural language processing and computer vision. Such a trend can also …