With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component, providing personalized …

Abstract Large Language Models (LLMs) have emerged as powerful tools in the field of
Natural Language Processing (NLP) and have recently gained significant attention in the …

In the past decades, recommender systems have attracted much attention in both research
and industry communities. Existing recommendation models mainly learn the underlying …

Recommender system plays a vital role in various online services. However, its insulated
nature of training and deploying separately within a specific closed domain limits its access …

This paper introduces PowerInfer, a high-speed Large Language Model (LLM) inference
engine on a personal computer (PC) equipped with a single consumer-grade GPU. The key …

User modeling (UM) aims to discover patterns or learn representations from user data about
the characteristics of a specific user, such as profile, preference, and personality. The user …

With the rapid development of online services and web applications, recommender systems
(RS) have become increasingly indispensable for mitigating information overload and …

Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …

This paper introduces the MCT Self-Refine (MCTSr) algorithm, an innovative integration of
Large Language Models (LLMs) with Monte Carlo Tree Search (MCTS), designed to …

Large language models (LLMs) have achieved remarkable success across various
domains, but effectively incorporating complex and potentially noisy user timeline data into …