[HTML][HTML] Deep reinforcement learning in recommender systems: A survey and new perspectives

X Chen, L Yao, J McAuley, G Zhou, X Wang - Knowledge-Based Systems, 2023 - Elsevier
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 …

A survey on reinforcement learning for recommender systems

Y Lin, Y Liu, F Lin, L Zou, P Wu, W Zeng… - … on Neural Networks …, 2023 - ieeexplore.ieee.org
Recommender systems have been widely applied in different real-life scenarios to help us
find useful information. In particular, reinforcement learning (RL)-based recommender …

UaMC: user-augmented conversation recommendation via multi-modal graph learning and context mining

S Fan, Y Wang, X Pang, L Chen, P Han, S Shang - World Wide Web, 2023 - Springer
Abstract Conversation Recommender System (CRS) engage in multi-turn conversations with
users and provide recommendations through responses. As user preferences evolve …

[HTML][HTML] Recommender system: A comprehensive overview of technical challenges and social implications

Y An, Y Tan, X Sun, G Ferrari - IECE Transactions on Sensing …, 2024 - iece.org
The proliferation of Recommender Systems (RecSys), driven by their expanding application
domains, explosive data growth, and exponential advancements in computing capabilities …

Evaluating the Robustness of Conversational Recommender Systems by Adversarial Examples

A Montazeralghaem, J Allan - arXiv preprint arXiv:2303.05575, 2023 - arxiv.org
Conversational recommender systems (CRSs) are improving rapidly, according to the
standard recommendation accuracy metrics. However, it is essential to make sure that these …

Efficient Inference in Open Retrieval Question Answering Systems

MS Rashid - 2024 - search.proquest.com
With the latest advances in conversational agents like Siri and Alexa, and Large Language
Models (LLMs) like ChatGPT and PaLM, Question Answering (QA) systems have become …