Cover Image

RecRankerEval: A Flexible and Extensible Framework for Top-k LLM-based Recommendation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Meng, Zeyuan, Yi, Zixuan, Ounis, Iadh
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

KERAG_R: Knowledge-Enhanced Retrieval-Augmented Generation for Recommendation
by: Meng, Zeyuan, et al.
Published: (2025)

A Directional Diffusion Graph Transformer for Recommendation
by: Yi, Zixuan, et al.
Published: (2024)

RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation
by: Luo, Sichun, et al.
Published: (2023)

LURE-RAG: Lightweight Utility-driven Reranking for Efficient RAG
by: Chandra, Manish, et al.
Published: (2026)

Lost in Transliteration: Bridging the Script Gap in Neural IR
by: Chari, Andreas, et al.
Published: (2025)

Document Similarity Enhanced IPS Estimation for Unbiased Learning to Rank
by: Liang, Zeyan, et al.
Published: (2025)

Improving Low-Resource Retrieval Effectiveness using Zero-Shot Linguistic Similarity Transfer
by: Chari, Andreas, et al.
Published: (2025)

Query Exposure Prediction for Groups of Documents in Rankings
by: Jaenich, Thomas, et al.
Published: (2024)

Generative Relevance Feedback and Convergence of Adaptive Re-Ranking: University of Glasgow Terrier Team at TREC DL 2023
by: Parry, Andrew, et al.
Published: (2024)

All Eyes on the Ranker: Participatory Auditing to Surface Blind Spots in Ranked Search Results
by: Rezk, Anna Marie, et al.
Published: (2026)

LLM as Explainable Re-Ranker for Recommendation System
by: Wang, Yaqi, et al.
Published: (2025)

RecCocktail: A Generalizable and Efficient Framework for LLM-Based Recommendation
by: Hou, Min, et al.
Published: (2025)

Temporal Fact Conflicts in LLMs: Reproducibility Insights from Unifying DYNAMICQA and MULAN
by: Dey, Ritajit, et al.
Published: (2026)

RecNextEval: A Reference Implementation for Temporal Next-Batch Recommendation Evaluation
by: Ng, Tze-Kean, et al.
Published: (2026)

HyMiRec: A Hybrid Multi-interest Learning Framework for LLM-based Sequential Recommendation
by: Zhou, Jingyi, et al.
Published: (2025)

MiniRec: Data-Efficient Reinforcement Learning for LLM-based Recommendation
by: Wang, Lin, et al.
Published: (2026)

RA-Rec: An Efficient ID Representation Alignment Framework for LLM-based Recommendation
by: Yu, Xiaohan, et al.
Published: (2024)

Quantifying Query Fairness Under Unawareness
by: Jaenich, Thomas, et al.
Published: (2025)

Transformers4NewsRec: A Transformer-based News Recommendation Framework
by: Liu, Dairui, et al.
Published: (2024)

A Unified Graph Transformer for Overcoming Isolations in Multi-modal Recommendation
by: Yi, Zixuan, et al.
Published: (2024)

WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging
by: Hou, Min, et al.
Published: (2025)

LRanker: LLM Ranker for Massive Candidates
by: Feng, Tao, et al.
Published: (2026)

WebRec: Enhancing LLM-based Recommendations with Attention-guided RAG from Web
by: Zhao, Zihuai, et al.
Published: (2025)

LLMDiRec: LLM-Enhanced Intent Diffusion for Sequential Recommendation
by: Chen, Bo-Chian, et al.
Published: (2025)

UniRec: Unified Multimodal Encoding for LLM-Based Recommendations
by: Lei, Zijie, et al.
Published: (2026)

OneRanker: Unified Generation and Ranking with One Model in Industrial Advertising Recommendation
by: Sun, Dekai, et al.
Published: (2026)

RecThinker: An Agentic Framework for Tool-Augmented Reasoning in Recommendation
by: Zhang, Haobo, et al.
Published: (2026)

MultiSlot ReRanker: A Generic Model-based Re-Ranking Framework in Recommendation Systems
by: Xiao, Qiang Charles, et al.
Published: (2024)

RaSeRec: Retrieval-Augmented Sequential Recommendation
by: Zhao, Xinping, et al.
Published: (2024)

Guiding Retrieval using LLM-based Listwise Rankers
by: Rathee, Mandeep, et al.
Published: (2025)

CherryRec: Enhancing News Recommendation Quality via LLM-driven Framework
by: Wang, Shaohuang, et al.
Published: (2024)

InRanker: Distilled Rankers for Zero-shot Information Retrieval
by: Laitz, Thiago, et al.
Published: (2024)

R1-Ranker: Teaching LLM Rankers to Reason
by: Feng, Tao, et al.
Published: (2025)

RecLM: Recommendation Instruction Tuning
by: Jiang, Yangqin, et al.
Published: (2024)

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems
by: Shang, Yu, et al.
Published: (2025)

MixRec: Individual and Collective Mixing Empowers Data Augmentation for Recommender Systems
by: Zhang, Yi, et al.
Published: (2025)

LLM-RecG: A Semantic Bias-Aware Framework for Zero-Shot Sequential Recommendation
by: Li, Yunzhe, et al.
Published: (2025)

An Investigation of Prompt Variations for Zero-shot LLM-based Rankers
by: Sun, Shuoqi, et al.
Published: (2024)

DaRec: A Disentangled Alignment Framework for Large Language Model and Recommender System
by: Yang, Xihong, et al.
Published: (2024)

RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interface
by: Zhang, Zeyuan, et al.
Published: (2024)