Large language models as zero-shot conversational recommenders
In this paper, we present empirical studies on conversational recommendation tasks using
representative large language models in a zero-shot setting with three primary …
representative large language models in a zero-shot setting with three primary …
Generative recommendation: Towards next-generation recommender paradigm
Recommender systems typically retrieve items from an item corpus for personalized
recommendations. However, such a retrieval-based recommender paradigm faces two …
recommendations. However, such a retrieval-based recommender paradigm faces two …
Lightgt: A light graph transformer for multimedia recommendation
Multimedia recommendation methods aim to discover the user preference on the multi-
modal information to enhance the collaborative filtering (CF) based recommender system …
modal information to enhance the collaborative filtering (CF) based recommender system …
[HTML][HTML] A survey on fairness-aware recommender systems
As information filtering services, recommender systems have extremely enriched our daily
life by providing personalized suggestions and facilitating people in decision-making, which …
life by providing personalized suggestions and facilitating people in decision-making, which …
A unified multi-task learning framework for multi-goal conversational recommender systems
Recent years witnessed several advances in developing multi-goal conversational
recommender systems (MG-CRS) that can proactively attract users' interests and naturally …
recommender systems (MG-CRS) that can proactively attract users' interests and naturally …
Variational reasoning about user preferences for conversational recommendation
Conversational recommender systems (CRSs) provide recommendations through
interactive conversations. CRSs typically provide recommendations through relatively …
interactive conversations. CRSs typically provide recommendations through relatively …
Broadening the view: Demonstration-augmented prompt learning for conversational recommendation
Conversational Recommender Systems (CRSs) leverage natural language dialogues to
provide tailored recommendations. Traditional methods in this field primarily focus on …
provide tailored recommendations. Traditional methods in this field primarily focus on …
Understanding user intent modeling for conversational recommender systems: a systematic literature review
User intent modeling in natural language processing deciphers user requests to allow for
personalized responses. The substantial volume of research (exceeding 13,000 …
personalized responses. The substantial volume of research (exceeding 13,000 …
Variational reasoning over incomplete knowledge graphs for conversational recommendation
Conversational recommender systems (CRSs) often utilize external knowledge graphs
(KGs) to introduce rich semantic information and recommend relevant items through natural …
(KGs) to introduce rich semantic information and recommend relevant items through natural …
Strategy-aware bundle recommender system
A bundle is a group of items that provides improved services to users and increased profits
for sellers. However, locating the desired bundles that match the users' tastes still …
for sellers. However, locating the desired bundles that match the users' tastes still …