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Evolutionary computation in the era of large language model: Survey and roadmap
Large language models (LLMs) have not only revolutionized natural language processing
but also extended their prowess to various domains, marking a significant stride towards …
but also extended their prowess to various domains, marking a significant stride towards …
User modeling in the era of large language models: Current research and future directions
User modeling (UM) aims to discover patterns or learn representations from user data about
the characteristics of a specific user, such as profile, preference, and personality. The user …
the characteristics of a specific user, such as profile, preference, and personality. The user …
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. Existing recommendation models mainly learn the underlying …
and industry communities. Existing recommendation models mainly learn the underlying …
Towards open-world recommendation with knowledge augmentation from large language models
Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …
nature of training and deploying separately within a specific closed domain limits its access …
Large language models for generative recommendation: A survey and visionary discussions
Large language models (LLM) not only have revolutionized the field of natural language
processing (NLP) but also have the potential to reshape many other fields, eg, recommender …
processing (NLP) but also have the potential to reshape many other fields, eg, recommender …
How can recommender systems benefit from large language models: A survey
With the rapid development of online services and web applications, recommender systems
(RS) have become increasingly indispensable for mitigating information overload and …
(RS) have become increasingly indispensable for mitigating information overload and …
Llm-rec: Personalized recommendation via prompting large language models
Text-based recommendation holds a wide range of practical applications due to its
versatility, as textual descriptions can represent nearly any type of item. However, directly …
versatility, as textual descriptions can represent nearly any type of item. However, directly …
Large language model for multi-objective evolutionary optimization
Multiobjective evolutionary algorithms (MOEAs) are major methods for solving multiobjective
optimization problems (MOPs). Many MOEAs have been proposed in the past decades, of …
optimization problems (MOPs). Many MOEAs have been proposed in the past decades, of …
Up5: Unbiased foundation model for fairness-aware recommendation
Recent advances in Foundation Models such as Large Language Models (LLMs) have
propelled them to the forefront of Recommender Systems (RS). Despite their utility, there is a …
propelled them to the forefront of Recommender Systems (RS). Despite their utility, there is a …