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 …
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 indispensable and important component in our daily lives, providing …
have become an indispensable and important component in our daily lives, providing …
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 …
Data-efficient Fine-tuning for LLM-based Recommendation
Leveraging Large Language Models (LLMs) for recommendation has recently garnered
considerable attention, where fine-tuning plays a key role in LLMs' adaptation. However, the …
considerable attention, where fine-tuning plays a key role in LLMs' adaptation. However, the …
Multimodal pretraining, adaptation, and generation for recommendation: A survey
Personalized recommendation serves as a ubiquitous channel for users to discover
information tailored to their interests. However, traditional recommendation models primarily …
information tailored to their interests. However, traditional recommendation models primarily …
Large language models for recommendation: Past, present, and future
Large language models (LLMs) have significantly influenced recommender systems,
spurring interest across academia and industry in leveraging LLMs for recommendation …
spurring interest across academia and industry in leveraging LLMs for recommendation …
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 …
Large language models are learnable planners for long-term recommendation
Planning for both immediate and long-term benefits becomes increasingly important in
recommendation. Existing methods apply Reinforcement Learning (RL) to learn planning …
recommendation. Existing methods apply Reinforcement Learning (RL) to learn planning …
CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation
Embedding-based retrieval serves as a dominant approach to candidate item matching for
industrial recommender systems. With the success of generative AI, generative retrieval has …
industrial recommender systems. With the success of generative AI, generative retrieval has …
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
Conversational recommender systems (CRSs) aim to capture user preferences and provide
personalized recommendations through multi-round natural language dialogues. However …
personalized recommendations through multi-round natural language dialogues. However …