Saved in:
| Main Authors: | Tokutake, Yu, Okamoto, Kazushi, Harada, Kei, Shibata, Atsushi, Karube, Koki |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.17571 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can Large Language Models Assess Serendipity in Recommender Systems?
by: Tokutake, Yu, et al.
Published: (2024)
by: Tokutake, Yu, et al.
Published: (2024)
Generation and annotation of item usage scenarios in e-commerce using large language models
by: Hagiri, Madoka, et al.
Published: (2025)
by: Hagiri, Madoka, et al.
Published: (2025)
Similarity-Based Supervised User Session Segmentation Method for Behavior Logs
by: Jin, Yongzhi, et al.
Published: (2025)
by: Jin, Yongzhi, et al.
Published: (2025)
Knowledge-Augmented Relation Learning for Complementary Recommendation with Large Language Models
by: Yamasaki, Chihiro, et al.
Published: (2025)
by: Yamasaki, Chihiro, et al.
Published: (2025)
Estimation of Fireproof Structure Class and Construction Year for Disaster Risk Assessment
by: Ayabe, Hibiki, et al.
Published: (2025)
by: Ayabe, Hibiki, et al.
Published: (2025)
Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
by: Kang, Li, et al.
Published: (2025)
by: Kang, Li, et al.
Published: (2025)
Bursting Filter Bubble: Enhancing Serendipity Recommendations with Aligned Large Language Models
by: Xi, Yunjia, et al.
Published: (2025)
by: Xi, Yunjia, et al.
Published: (2025)
Enhancing Serendipity Recommendation System by Constructing Dynamic User Knowledge Graphs with Large Language Models
by: Yong, Qian, et al.
Published: (2025)
by: Yong, Qian, et al.
Published: (2025)
Function-based Labels for Complementary Recommendation: Definition, Annotation, and LLM-as-a-Judge
by: Yamasaki, Chihiro, et al.
Published: (2025)
by: Yamasaki, Chihiro, et al.
Published: (2025)
Hierarchical Matrix Factorization for Interpretable Collaborative Filtering
by: Sugahara, Kai, et al.
Published: (2023)
by: Sugahara, Kai, et al.
Published: (2023)
Evaluating Conversational Recommender Systems via Large Language Models: A User-Centric Framework
by: Chen, Nuo, et al.
Published: (2025)
by: Chen, Nuo, et al.
Published: (2025)
Offline Evaluation Measures of Fairness in Recommender Systems
by: Rampisela, Theresia Veronika
Published: (2026)
by: Rampisela, Theresia Veronika
Published: (2026)
Engineering Serendipity through Recommendations of Items with Atypical Aspects
by: Aditya, Ramit, et al.
Published: (2025)
by: Aditya, Ramit, et al.
Published: (2025)
Enhancing User Intent for Recommendation Systems via Large Language Models
by: Xu, Xiaochuan, et al.
Published: (2025)
by: Xu, Xiaochuan, et al.
Published: (2025)
The Application of Large Language Models in Recommendation Systems
by: Yu, Peiyang, et al.
Published: (2025)
by: Yu, Peiyang, et al.
Published: (2025)
DaRec: A Disentangled Alignment Framework for Large Language Model and Recommender System
by: Yang, Xihong, et al.
Published: (2024)
by: Yang, Xihong, et al.
Published: (2024)
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System
by: Deldjoo, Yashar, et al.
Published: (2024)
by: Deldjoo, Yashar, et al.
Published: (2024)
A Serendipitous Recommendation System Considering User Curiosity
by: Xu, Zhelin, et al.
Published: (2025)
by: Xu, Zhelin, et al.
Published: (2025)
Collaborative Large Language Model for Recommender Systems
by: Zhu, Yaochen, et al.
Published: (2023)
by: Zhu, Yaochen, et al.
Published: (2023)
Evaluating Position Bias in Large Language Model Recommendations
by: Bito, Ethan, et al.
Published: (2025)
by: Bito, Ethan, et al.
Published: (2025)
Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis
by: Xu, Lanling, et al.
Published: (2024)
by: Xu, Lanling, et al.
Published: (2024)
Coherency Improved Explainable Recommendation via Large Language Model
by: Liu, Shijie, et al.
Published: (2025)
by: Liu, Shijie, et al.
Published: (2025)
Large Language Model as Universal Retriever in Industrial-Scale Recommender System
by: Jiang, Junguang, et al.
Published: (2025)
by: Jiang, Junguang, et al.
Published: (2025)
ProEx: A Unified Framework Leveraging Large Language Model with Profile Extrapolation for Recommendation
by: Zhang, Yi, et al.
Published: (2025)
by: Zhang, Yi, et al.
Published: (2025)
Training Large Recommendation Models via Graph-Language Token Alignment
by: Yang, Mingdai, et al.
Published: (2025)
by: Yang, Mingdai, et al.
Published: (2025)
On the Reliability of Sampling Strategies in Offline Recommender Evaluation
by: Pereira, Bruno L., et al.
Published: (2025)
by: Pereira, Bruno L., et al.
Published: (2025)
Can Offline Metrics Measure Explanation Goals? A Comparative Survey Analysis of Offline Explanation Metrics in Recommender Systems
by: Zanon, André Levi, et al.
Published: (2023)
by: Zanon, André Levi, et al.
Published: (2023)
Large Language Models as Evaluators for Recommendation Explanations
by: Zhang, Xiaoyu, et al.
Published: (2024)
by: Zhang, Xiaoyu, et al.
Published: (2024)
Large Language Model driven Policy Exploration for Recommender Systems
by: Wang, Jie, et al.
Published: (2025)
by: Wang, Jie, et al.
Published: (2025)
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
by: Wang, Yan, et al.
Published: (2023)
by: Wang, Yan, et al.
Published: (2023)
A Normative Framework for Benchmarking Consumer Fairness in Large Language Model Recommender System
by: Deldjoo, Yashar, et al.
Published: (2024)
by: Deldjoo, Yashar, et al.
Published: (2024)
Intent Representation Learning with Large Language Model for Recommendation
by: Wang, Yu, et al.
Published: (2025)
by: Wang, Yu, et al.
Published: (2025)
Reward Balancing Revisited: Enhancing Offline Reinforcement Learning for Recommender Systems
by: Shu, Wenzheng, et al.
Published: (2025)
by: Shu, Wenzheng, et al.
Published: (2025)
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
by: Xi, Yunjia, et al.
Published: (2024)
by: Xi, Yunjia, et al.
Published: (2024)
Reformulating Conversational Recommender Systems as Tri-Phase Offline Policy Learning
by: Zhang, Gangyi, et al.
Published: (2024)
by: Zhang, Gangyi, et al.
Published: (2024)
Hard Negative Sampling via Large Language Models for Recommendation
by: Zhao, Chu, et al.
Published: (2025)
by: Zhao, Chu, et al.
Published: (2025)
Towards Fair Large Language Model-based Recommender Systems without Costly Retraining
by: Li, Jin, et al.
Published: (2026)
by: Li, Jin, et al.
Published: (2026)
Towards Robust Offline Evaluation: A Causal and Information Theoretic Framework for Debiasing Ranking Systems
by: Khatami, Seyedeh Baharan, et al.
Published: (2025)
by: Khatami, Seyedeh Baharan, et al.
Published: (2025)
A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems
by: Bao, Keqin, et al.
Published: (2023)
by: Bao, Keqin, et al.
Published: (2023)
Beyond Offline A/B Testing: Context-Aware Agent Simulation for Recommender System Evaluation
by: Bougie, Nicolas, et al.
Published: (2026)
by: Bougie, Nicolas, et al.
Published: (2026)
Similar Items
-
Can Large Language Models Assess Serendipity in Recommender Systems?
by: Tokutake, Yu, et al.
Published: (2024) -
Generation and annotation of item usage scenarios in e-commerce using large language models
by: Hagiri, Madoka, et al.
Published: (2025) -
Similarity-Based Supervised User Session Segmentation Method for Behavior Logs
by: Jin, Yongzhi, et al.
Published: (2025) -
Knowledge-Augmented Relation Learning for Complementary Recommendation with Large Language Models
by: Yamasaki, Chihiro, et al.
Published: (2025) -
Estimation of Fireproof Structure Class and Construction Year for Disaster Risk Assessment
by: Ayabe, Hibiki, et al.
Published: (2025)