Image de couverture de livre

Can Large Language Models Assess Serendipity in Recommender Systems?

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Tokutake, Yu, Okamoto, Kazushi
Format:	Preprint
Publié:	2024
Sujets:	Information Retrieval
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A Universal Framework for Offline Serendipity Evaluation in Recommender Systems via Large Language Models
par: Tokutake, Yu, et autres
Publié: (2025)

Knowledge-Augmented Relation Learning for Complementary Recommendation with Large Language Models
par: Yamasaki, Chihiro, et autres
Publié: (2025)

Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models
par: Xi, Yunjia, et autres
Publié: (2025)

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
par: Kang, Li, et autres
Publié: (2025)

Enhancing Serendipity Recommendation System by Constructing Dynamic User Knowledge Graphs with Large Language Models
par: Yong, Qian, et autres
Publié: (2025)

Function-based Labels for Complementary Recommendation: Definition, Annotation, and LLM-as-a-Judge
par: Yamasaki, Chihiro, et autres
Publié: (2025)

Hierarchical Matrix Factorization for Interpretable Collaborative Filtering
par: Sugahara, Kai, et autres
Publié: (2023)

The Application of Large Language Models in Recommendation Systems
par: Yu, Peiyang, et autres
Publié: (2025)

Engineering Serendipity through Recommendations of Items with Atypical Aspects
par: Aditya, Ramit, et autres
Publié: (2025)

Collaborative Large Language Model for Recommender Systems
par: Zhu, Yaochen, et autres
Publié: (2023)

Enhancing User Intent for Recommendation Systems via Large Language Models
par: Xu, Xiaochuan, et autres
Publié: (2025)

How Can Recommender Systems Benefit from Large Language Models: A Survey
par: Lin, Jianghao, et autres
Publié: (2023)

Enhancing Recommender Systems with Large Language Model Reasoning Graphs
par: Wang, Yan, et autres
Publié: (2023)

Large Language Model driven Policy Exploration for Recommender Systems
par: Wang, Jie, et autres
Publié: (2025)

Generation and annotation of item usage scenarios in e-commerce using large language models
par: Hagiri, Madoka, et autres
Publié: (2025)

Similarity-Based Supervised User Session Segmentation Method for Behavior Logs
par: Jin, Yongzhi, et autres
Publié: (2025)

Intent Representation Learning with Large Language Model for Recommendation
par: Wang, Yu, et autres
Publié: (2025)

MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
par: Xi, Yunjia, et autres
Publié: (2024)

Towards Fair Large Language Model-based Recommender Systems without Costly Retraining
par: Li, Jin, et autres
Publié: (2026)

One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems
par: Tang, Zuoli, et autres
Publié: (2023)

Item-side Fairness of Large Language Model-based Recommendation System
par: Jiang, Meng, et autres
Publié: (2024)

Collaborative Retrieval for Large Language Model-based Conversational Recommender Systems
par: Zhu, Yaochen, et autres
Publié: (2025)

Harnessing Large Language Models for Group POI Recommendations
par: Long, Jing, et autres
Publié: (2024)

DaRec: A Disentangled Alignment Framework for Large Language Model and Recommender System
par: Yang, Xihong, et autres
Publié: (2024)

Large Language Model Simulator for Cold-Start Recommendation
par: Huang, Feiran, et autres
Publié: (2024)

Large Language Models Make Sample-Efficient Recommender Systems
par: Lin, Jianghao, et autres
Publié: (2024)

Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models
par: Huang, Chengkai, et autres
Publié: (2025)

CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System
par: Deldjoo, Yashar, et autres
Publié: (2024)

Temporal-Aware User Behaviour Simulation with Large Language Models for Recommender Systems
par: Wanyan, Xinye, et autres
Publié: (2025)

Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems
par: Shi, Tianhao, et autres
Publié: (2023)

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems
par: Bao, Keqin, et autres
Publié: (2023)

Coherency Improved Explainable Recommendation via Large Language Model
par: Liu, Shijie, et autres
Publié: (2025)

Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation
par: Zheng, Bowen, et autres
Publié: (2023)

Aligning Large Language Models with Recommendation Knowledge
par: Cao, Yuwei, et autres
Publié: (2024)

Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling
par: Wang, Jie, et autres
Publié: (2024)

Multimodal Large Language Models with Adaptive Preference Optimization for Sequential Recommendation
par: Wang, Yu, et autres
Publié: (2025)

SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems
par: Jia, Pengyue, et autres
Publié: (2024)

Training Large Recommendation Models via Graph-Language Token Alignment
par: Yang, Mingdai, et autres
Publié: (2025)

Trustworthy Recommendation in the Era of Large Language Models: Opportunities and Challenges
par: Wang, Bohao, et autres
Publié: (2026)

LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation
par: Liu, Qidong, et autres
Publié: (2024)