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 …
Tallrec: An effective and efficient tuning framework to align large language model with recommendation
Large Language Models (LLMs) have demonstrated remarkable performance across
diverse domains, thereby prompting researchers to explore their potential for use in …
diverse domains, thereby prompting researchers to explore their potential for use in …
A survey on large language models for recommendation
Abstract Large Language Models (LLMs) have emerged as powerful tools in the field of
Natural Language Processing (NLP) and have recently gained significant attention in the …
Natural Language Processing (NLP) and have recently gained significant attention in the …
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 …
Uncovering chatgpt's capabilities in recommender systems
The debut of ChatGPT has recently attracted significant attention from the natural language
processing (NLP) community and beyond. Existing studies have demonstrated that ChatGPT …
processing (NLP) community and beyond. Existing studies have demonstrated that ChatGPT …
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 …
Text is all you need: Learning language representations for sequential recommendation
Sequential recommendation aims to model dynamic user behavior from historical
interactions. Existing methods rely on either explicit item IDs or general textual features for …
interactions. Existing methods rely on either explicit item IDs or general textual features for …
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 …
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 …