When large language models meet personalization: Perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …
intelligence. With the unprecedented scale of training and model parameters, the capability …
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 …
Rethinking the evaluation for conversational recommendation in the era of large language models
The recent success of large language models (LLMs) has shown great potential to develop
more powerful conversational recommender systems (CRSs), which rely on natural …
more powerful conversational recommender systems (CRSs), which rely on natural …
Recommender ai agent: Integrating large language models for interactive recommendations
Recommender models excel at providing domain-specific item recommendations by
leveraging extensive user behavior data. Despite their ability to act as lightweight domain …
leveraging extensive user behavior data. Despite their ability to act as lightweight domain …
Enhancing conversational recommender systems via multi-level knowledge modeling with semantic relations
Augmenting conversational recommendation systems (CRS) with prior knowledge is crucial
for learning user preferences and understanding contextual semantics. Existing methods are …
for learning user preferences and understanding contextual semantics. Existing methods are …
Improving conversational recommendation systems via counterfactual data simulation
Conversational recommender systems~(CRSs) aim to provide recommendation services via
natural language conversations. Although a number of approaches have been proposed for …
natural language conversations. Although a number of approaches have been proposed for …
Concept--An Evaluation Protocol on Conversation Recommender Systems with System-and User-centric Factors
The conversational recommendation system (CRS) has been criticized regarding its user
experience in real-world scenarios, despite recent significant progress achieved in …
experience in real-world scenarios, despite recent significant progress achieved in …
[HTML][HTML] Multi-grained hypergraph interest modeling for conversational recommendation
Conversational recommender system (CRS) interacts with users through multi-turn
dialogues in natural language, which aims to provide high-quality recommendations for …
dialogues in natural language, which aims to provide high-quality recommendations for …
A multi-agent conversational recommender system
Due to strong capabilities in conducting fluent, multi-turn conversations with users, Large
Language Models (LLMs) have the potential to further improve the performance of …
Language Models (LLMs) have the potential to further improve the performance of …
Unleashing the Retrieval Potential of Large Language Models in Conversational Recommender Systems
T Yang, L Chen - Proceedings of the 18th ACM Conference on …, 2024 - dl.acm.org
Conversational recommender systems (CRSs) aim to capture user preferences and provide
personalized recommendations through interactive natural language interaction. The recent …
personalized recommendations through interactive natural language interaction. The recent …