Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an important component of our daily life, providing personalized suggestions …
have become an important component of our daily life, providing personalized suggestions …
Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component in our daily lives, providing …
have become an indispensable and important component in our daily lives, providing …
[HTML][HTML] A survey on fairness-aware recommender systems
As information filtering services, recommender systems have extremely enriched our daily
life by providing personalized suggestions and facilitating people in decision-making, which …
life by providing personalized suggestions and facilitating people in decision-making, which …
Generative diffusion models on graphs: Methods and applications
Diffusion models, as a novel generative paradigm, have achieved remarkable success in
various image generation tasks such as image inpainting, image-to-text translation, and …
various image generation tasks such as image inpainting, image-to-text translation, and …
Trustworthy recommender systems
Recommender systems (RSs) aim at helping users to effectively retrieve items of their
interests from a large catalogue. For a quite long time, researchers and practitioners have …
interests from a large catalogue. For a quite long time, researchers and practitioners have …
Fairly adaptive negative sampling for recommendations
Pairwise learning strategies are prevalent for optimizing recommendation models on implicit
feedback data, which usually learns user preference by discriminating between positive (ie …
feedback data, which usually learns user preference by discriminating between positive (ie …
Multi-task deep recommender systems: A survey
Multi-task learning (MTL) aims at learning related tasks in a unified model to achieve mutual
improvement among tasks considering their shared knowledge. It is an important topic in …
improvement among tasks considering their shared knowledge. It is an important topic in …
Adversarial attacks for black-box recommender systems via copying transferable cross-domain user profiles
As widely used in data-driven decision-making, recommender systems have been
recognized for their capabilities to provide users with personalized services in many user …
recognized for their capabilities to provide users with personalized services in many user …
Fairness in recommendation: Foundations, methods, and applications
As one of the most pervasive applications of machine learning, recommender systems are
playing an important role on assisting human decision-making. The satisfaction of users and …
playing an important role on assisting human decision-making. The satisfaction of users and …
Causal inference for recommendation: Foundations, methods and applications
Recommender systems are important and powerful tools for various personalized services.
Traditionally, these systems use data mining and machine learning techniques to make …
Traditionally, these systems use data mining and machine learning techniques to make …