Reinforcement learning based recommender systems: A survey
Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …
help us find our favorite items to purchase, our friends on social networks, and our favorite …
[HTML][HTML] Fairness in recommender systems: research landscape and future directions
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …
On generative agents in recommendation
Recommender systems are the cornerstone of today's information dissemination, yet a
disconnect between offline metrics and online performance greatly hinders their …
disconnect between offline metrics and online performance greatly hinders their …
[HTML][HTML] Deep reinforcement learning in recommender systems: A survey and new perspectives
In light of the emergence of deep reinforcement learning (DRL) in recommender systems
research and several fruitful results in recent years, this survey aims to provide a timely and …
research and several fruitful results in recent years, this survey aims to provide a timely and …
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 …
Self-supervised reinforcement learning for recommender systems
In session-based or sequential recommendation, it is important to consider a number of
factors like long-term user engagement, multiple types of user-item interactions such as …
factors like long-term user engagement, multiple types of user-item interactions such as …
Recsim: A configurable simulation platform for recommender systems
We propose RecSim, a configurable platform for authoring simulation environments for
recommender systems (RSs) that naturally supports sequential interaction with users …
recommender systems (RSs) that naturally supports sequential interaction with users …
KuaiSim: A comprehensive simulator for recommender systems
Reinforcement Learning (RL)-based recommender systems (RSs) have garnered
considerable attention due to their ability to learn optimal recommendation policies and …
considerable attention due to their ability to learn optimal recommendation policies and …
[HTML][HTML] A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization
Abstract The 5th Generation (5G) and beyond networks are expected to offer huge
throughputs, connect large number of devices, support low latency and large numbers of …
throughputs, connect large number of devices, support low latency and large numbers of …
Keeping dataset biases out of the simulation: A debiased simulator for reinforcement learning based recommender systems
Reinforcement learning for recommendation (RL4Rec) methods are increasingly receiving
attention as an effective way to improve long-term user engagement. However, applying …
attention as an effective way to improve long-term user engagement. However, applying …