A review of modern recommender systems using generative models (gen-recsys)
Traditional recommender systems typically use user-item rating histories as their main data
source. However, deep generative models now have the capability to model and sample …
source. However, deep generative models now have the capability to model and sample …
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 …
A survey on rag meeting llms: Towards retrieval-augmented large language models
As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …
Towards unified conversational recommender systems via knowledge-enhanced prompt learning
Conversational recommender systems (CRS) aim to proactively elicit user preference and
recommend high-quality items through natural language conversations. Typically, a CRS …
recommend high-quality items through natural language conversations. Typically, a CRS …
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 …
C²-crs: Coarse-to-fine contrastive learning for conversational recommender system
Conversational recommender systems (CRS) aim to recommend suitable items to users
through natural language conversations. For developing effective CRSs, a major technical …
through natural language conversations. For developing effective CRSs, a major technical …
User-centric conversational recommendation with multi-aspect user modeling
Conversational recommender systems (CRS) aim to provide highquality recommendations
in conversations. However, most conventional CRS models mainly focus on the dialogue …
in conversations. However, most conventional CRS models mainly focus on the dialogue …
Improving conversational recommender system via contextual and time-aware modeling with less domain-specific knowledge
Conversational Recommender Systems (CRS) has become an emerging research topic
seeking to perform recommendations through interactive conversations, which generally …
seeking to perform recommendations through interactive conversations, which generally …
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 …
Improving conversational recommender systems via transformer-based sequential modelling
In Conversational Recommender Systems (CRSs), conversations usually involve a set of
related items and entities eg, attributes of items. These items and entities are mentioned in …
related items and entities eg, attributes of items. These items and entities are mentioned in …