[HTML][HTML] Advances and challenges in conversational recommender systems: A survey
Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …
heavily used in a wide range of industry applications. However, static recommendation …
A survey on conversational recommender systems
Recommender systems are software applications that help users to find items of interest in
situations of information overload. Current research often assumes a one-shot interaction …
situations of information overload. Current research often assumes a one-shot interaction …
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 …
Leveraging large language models in conversational recommender systems
L Friedman, S Ahuja, D Allen, Z Tan… - arXiv preprint arXiv …, 2023 - arxiv.org
A Conversational Recommender System (CRS) offers increased transparency and control to
users by enabling them to engage with the system through a real-time multi-turn dialogue …
users by enabling them to engage with the system through a real-time multi-turn dialogue …
Towards topic-guided conversational recommender system
Conversational recommender systems (CRS) aim to recommend high-quality items to users
through interactive conversations. To develop an effective CRS, the support of high-quality …
through interactive conversations. To develop an effective CRS, the support of high-quality …
Towards conversational recommendation over multi-type dialogs
We propose a new task of conversational recommendation over multi-type dialogs, where
the bots can proactively and naturally lead a conversation from a non-recommendation …
the bots can proactively and naturally lead a conversation from a non-recommendation …
Inspired: Toward sociable recommendation dialog systems
In recommendation dialogs, humans commonly disclose their preference and make
recommendations in a friendly manner. However, this is a challenge when developing a …
recommendations in a friendly manner. However, this is a challenge when developing a …
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 …
Towards teachable reasoning systems: Using a dynamic memory of user feedback for continual system improvement
Our goal is a teachable reasoning system for question-answering (QA), where a user can
interact with faithful answer explanations, and correct its errors so that the system improves …
interact with faithful answer explanations, and correct its errors so that the system improves …
A comprehensive survey on trustworthy recommender systems
As one of the most successful AI-powered applications, recommender systems aim to help
people make appropriate decisions in an effective and efficient way, by providing …
people make appropriate decisions in an effective and efficient way, by providing …