A survey on neural-symbolic learning systems
D Yu, B Yang, D Liu, H Wang, S Pan - Neural Networks, 2023 - Elsevier
In recent years, neural systems have demonstrated highly effective learning ability and
superior perception intelligence. However, they have been found to lack effective reasoning …
superior perception intelligence. However, they have been found to lack effective reasoning …
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 …
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 …
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning
F Mumuni, A Mumuni - Cognitive Systems Research, 2024 - Elsevier
We review current and emerging knowledge-informed and brain-inspired cognitive systems
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …