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 …
Personalized prompt learning for explainable recommendation
Providing user-understandable explanations to justify recommendations could help users
better understand the recommended items, increase the system's ease of use, and gain …
better understand the recommended items, increase the system's ease of use, and gain …
Towards long-term fairness in recommendation
As Recommender Systems (RS) influence more and more people in their daily life, the issue
of fairness in recommendation is becoming more and more important. Most of the prior …
of fairness in recommendation is becoming more and more important. Most of the prior …
Counterfactual explainable recommendation
By providing explanations for users and system designers to facilitate better understanding
and decision making, explainable recommendation has been an important research …
and decision making, explainable recommendation has been an important research …
A survey on trustworthy recommender systems
Recommender systems (RS), serving at the forefront of Human-centered AI, are widely
deployed in almost every corner of the web and facilitate the human decision-making …
deployed in almost every corner of the web and facilitate the human decision-making …
Personalized transformer for explainable recommendation
Personalization of natural language generation plays a vital role in a large spectrum of
tasks, such as explainable recommendation, review summarization and dialog systems. In …
tasks, such as explainable recommendation, review summarization and dialog systems. In …
Multi-level recommendation reasoning over knowledge graphs with reinforcement learning
Knowledge graphs (KGs) have been widely used to improve recommendation accuracy. The
multi-hop paths on KGs also enable recommendation reasoning, which is considered a …
multi-hop paths on KGs also enable recommendation reasoning, which is considered a …
Explainable fairness in recommendation
Existing research on fairness-aware recommendation has mainly focused on the
quantification of fairness and the development of fair recommendation models, neither of …
quantification of fairness and the development of fair recommendation models, neither of …
Path language modeling over knowledge graphsfor explainable recommendation
To facilitate human decisions with credible suggestions, personalized recommender
systems should have the ability to generate corresponding explanations while making …
systems should have the ability to generate corresponding explanations while making …
Toward Pareto efficient fairness-utility trade-off in recommendation through reinforcement learning
The issue of fairness in recommendation is becoming increasingly essential as
Recommender Systems (RS) touch and influence more and more people in their daily lives …
Recommender Systems (RS) touch and influence more and more people in their daily lives …