Cover Image

Understanding the Role of Cross-Entropy Loss in Fairly Evaluating Large Language Model-based Recommendation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Cong, Zhu, Zhangchi, Wang, Jun, Wang, Jianyong, Zhang, Wei
Format:	Preprint
Published:	2024
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Are LLM-based Recommenders Already the Best? Simple Scaled Cross-entropy Unleashes the Potential of Traditional Sequential Recommenders
by: Xu, Cong, et al.
Published: (2024)

Rejuvenating Cross-Entropy Loss in Knowledge Distillation for Recommender Systems
by: Zhu, Zhangchi, et al.
Published: (2025)

Preference-Consistent Knowledge Distillation for Recommender System
by: Zhu, Zhangchi, et al.
Published: (2023)

Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution
by: Xu, Cong, et al.
Published: (2023)

Break the Optimization Barrier of LLM-Enhanced Recommenders: A Theoretical Analysis and Practical Framework
by: Zhu, Zhangchi, et al.
Published: (2026)

Exploring Feature-based Knowledge Distillation for Recommender System: A Frequency Perspective
by: Zhu, Zhangchi, et al.
Published: (2024)

Towards Fair Large Language Model-based Recommender Systems without Costly Retraining
by: Li, Jin, et al.
Published: (2026)

Item-side Fairness of Large Language Model-based Recommendation System
by: Jiang, Meng, et al.
Published: (2024)

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning
by: He, Yunhang, et al.
Published: (2026)

Markovian Pre-Trained Transformer for Next-Item Recommendation
by: Xu, Cong, et al.
Published: (2026)

Scalable Cross-Entropy Loss for Sequential Recommendations with Large Item Catalogs
by: Mezentsev, Gleb, et al.
Published: (2024)

RECE: Reduced Cross-Entropy Loss for Large-Catalogue Sequential Recommenders
by: Gusak, Danil, et al.
Published: (2024)

CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System
by: Deldjoo, Yashar, et al.
Published: (2024)

STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation
by: Xu, Cong, et al.
Published: (2024)

Cross-Domain Recommendation Meets Large Language Models
by: Vajjala, Ajay Krishna, et al.
Published: (2024)

Coherency Improved Explainable Recommendation via Large Language Model
by: Liu, Shijie, et al.
Published: (2025)

Can We Trust Recommender System Fairness Evaluation? The Role of Fairness and Relevance
by: Rampisela, Theresia Veronika, et al.
Published: (2024)

The Application of Large Language Models in Recommendation Systems
by: Yu, Peiyang, et al.
Published: (2025)

Uncovering Cross-Domain Recommendation Ability of Large Language Models
by: Liu, Xinyi, et al.
Published: (2025)

RecGPT-Mobile: On-Device Large Language Models for User Intent Understanding in Taobao Feed Recommendation
by: Zhang, Bin, et al.
Published: (2026)

Understanding the Ranking Loss for Recommendation with Sparse User Feedback
by: Lin, Zhutian, et al.
Published: (2024)

Enhancing New-item Fairness in Dynamic Recommender Systems
by: Guo, Huizhong, et al.
Published: (2025)

Exact and Efficient Unlearning for Large Language Model-based Recommendation
by: Hu, Zhiyu, et al.
Published: (2024)

Large Language Models as Evaluators for Recommendation Explanations
by: Zhang, Xiaoyu, et al.
Published: (2024)

LLMRec: Large Language Models with Graph Augmentation for Recommendation
by: Wei, Wei, et al.
Published: (2023)

Intent Representation Learning with Large Language Model for Recommendation
by: Wang, Yu, et al.
Published: (2025)

Enhancing User Intent for Recommendation Systems via Large Language Models
by: Xu, Xiaochuan, et al.
Published: (2025)

Fine-grained Semantics Integration for Large Language Model-based Recommendation
by: Feng, Jiawei, et al.
Published: (2026)

Order-agnostic Identifier for Large Language Model-based Generative Recommendation
by: Lin, Xinyu, et al.
Published: (2025)

FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval
by: Xu, Chen, et al.
Published: (2024)

RALLRec+: Retrieval Augmented Large Language Model Recommendation with Reasoning
by: Luo, Sichun, et al.
Published: (2025)

Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation
by: Liu, Qidong, et al.
Published: (2025)

Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Model
by: Cui, Yu, et al.
Published: (2024)

Reason4Rec: Large Language Models for Recommendation with Deliberative User Preference Alignment
by: Fang, Yi, et al.
Published: (2025)

Leveraging Large Language Models to Enhance Personalized Recommendations in E-commerce
by: Xu, Wei, et al.
Published: (2024)

Enhancing Recommender Systems with Large Language Model Reasoning Graphs
by: Wang, Yan, et al.
Published: (2023)

Reasoning to Rank: An End-to-End Solution for Exploiting Large Language Models for Recommendation
by: Zheng, Kehan, et al.
Published: (2026)

Regret-aware Re-ranking for Guaranteeing Two-sided Fairness and Accuracy in Recommender Systems
by: Ye, Xiaopeng, et al.
Published: (2025)

Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation
by: Wang, Li, et al.
Published: (2024)

Evaluating Position Bias in Large Language Model Recommendations
by: Bito, Ethan, et al.
Published: (2025)