mlsanityData to 14 Oct 2026

LlamaRec: Two-Stage Recommendation using Large Language Models for Ranking

arXiv 2311.02089 ↗First posted 25 Oct 2023cs.IR cs.AI cs.CLcited by 53

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Abstract (arXiv)

Recently, large language models (LLMs) have exhibited significant progress in language understanding and generation. By leveraging textual features, customized LLMs are also applied for recommendation and demonstrate improvements across diverse recommendation scenarios. Yet the majority of existing methods perform training-free recommendation that heavily relies on pretrained knowledge (e.g., movie recommendation). In addition, inference on LLMs is slow due to autoregressive generation, rendering existing methods less effective for real-time recommendation. As such, we propose a two-stage framework using large language models for ranking-based recommendation (LlamaRec). In particular, we use small-scale sequential recommenders to retrieve candidates based on the user interaction history. Then, both history and retrieved items are fed to the LLM in text via a carefully designed prompt template. Instead of generating next-item titles, we adopt a verbalizer-based approach that transforms output logits into probability distributions over the candidate items. Therefore, the proposed LlamaRec can efficiently rank items without generating long text. To validate the effectiveness of the proposed framework, we compare against state-of-the-art baseline methods on benchmark datasets. Our experimental results demonstrate the performance of LlamaRec, which consistently achieves superior performance in both recommendation performance and efficiency.

Key facts. Cited by 53 papers in the map (data through 14 Oct 2026). Builds on 26 of its 35 references that are in the map. First posted on arXiv 25 Oct 2023.

Builds on

26 of 35 references.

References · 26

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  5. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  6. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,512
  7. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
  8. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,984
  9. 2018Self-Attentive Sequential Recommendationcited by 1,184
  10. 2019BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformercited by 964
  11. 2015Image-based Recommendations on Styles and Substitutescited by 706
  12. 2016Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filteringcited by 520
14 more
  1. 2022Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)cited by 402
  2. 2023Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agentscited by 360
  3. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 309
  4. 2023Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender Systemcited by 242
  5. 2017Neural Attentive Session-based Recommendationcited by 237
  6. 2023Is ChatGPT a Good Recommender? A Preliminary Studycited by 193
  7. 2023Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approachcited by 168
  8. 2023Text Is All You Need: Learning Language Representations for Sequential Recommendationcited by 149
  9. 2023Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Predictioncited by 116
  10. 2023GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretationcited by 103
  11. 2023PALR: Personalization Aware LLMs for Recommendationcited by 96
  12. 2023Linear Recurrent Units for Sequential Recommendationcited by 32
  13. 2021Zero-Shot Recommendation as Language Modelingcited by 28
  14. 2022Defending Substitution-Based Profile Pollution Attacks on Sequential Recommenderscited by 11

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 22; 2025: 12; 2026: 19.

53 papers.

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  1. 2024Position: Graph Foundation Models are Already Herecited by 86
  2. 2025A Survey on LLM-powered Agents for Recommender Systemscited by 50
  3. 2024Customizing Language Models with Instance-wise LoRA for Sequential Recommendationcited by 32
  4. 2024Rethinking Large Language Model Architectures for Sequential Recommendationscited by 27
  5. 2024P/D-Serve: Serving Disaggregated Large Language Model at Scalecited by 27
  6. 2024Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyondcited by 26
  7. 2024Large Language Models and Video Games: A Preliminary Scoping Reviewcited by 23
  8. 2024RDRec: Rationale Distillation for LLM-based Recommendationcited by 22
  9. 2024Review-driven Personalized Preference Reasoning with Large Language Models for Recommendationcited by 22
  10. 2024LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Applicationcited by 21
  11. 2024Federated Recommendation via Hybrid Retrieval Augmented Generationcited by 16
  12. 2024A Survey of Generative Search and Recommendation in the Era of Large Language Modelscited by 15
38 more
  1. 2025The Future is Agentic: Definitions, Perspectives, and Open Challenges of Multi-Agent Recommender Systemscited by 14
  2. 2024Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Reviewcited by 12
  3. 2024Make Large Language Model a Better Rankercited by 11
  4. 2025CoFiRec: Coarse-to-Fine Tokenization for Generative Recommendationcited by 11
  5. 2024Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendationcited by 10
  6. 2024Enhancing High-order Interaction Awareness in LLM-based Recommender Modelcited by 8
  7. 2024Token-level Proximal Policy Optimization for Query Generationcited by 7
  8. 2024Are Longer Prompts Always Better? Prompt Selection in Large Language Models for Recommendation Systemscited by 6
  9. 2025Understanding Generative Recommendation with Semantic IDs from a Model-scaling Viewcited by 6
  10. 2025Generative Product Recommendations for Implicit Superlative Queriescited by 5
  11. 2024DELRec: Distilling Sequential Pattern to Enhance LLMs-based Sequential Recommendationcited by 3
  12. 2025MLLMRec: A Preference Reasoning Paradigm with Graph Refinement for Multimodal Recommendationcited by 3
  13. 2025Efficient and Responsible Adaptation of Large Language Models for Robust and Equitable Top-k Recommendationscited by 2
  14. 2026De-conflating Preference and Qualification: Constrained Dual-Perspective Reasoning for Job Recommendation with Large Language Modelscited by 2
  15. 2024Advancing Large Language Models for Spatiotemporal and Semantic Association Mining of Similar Environmental Eventscited by 1
  16. 2024PyTerrier-GenRank: The PyTerrier Plugin for Reranking with Large Language Modelscited by 1
  17. 2025Do LLMs Understand Collaborative Signals? Diagnosis and Repaircited by 1
  18. 2025Augment or Not? A Comparative Study of Pure and Augmented Large Language Model Recommenderscited by 1
  19. 2025Improving the Performance of Sequential Recommendation Systems with an Extended Large Language Modelcited by 1
  20. 2025Token-Controlled Re-ranking for Sequential Recommendation via LLMscited by 1
  21. 2026Efficient Sequential Recommendation for Long Term User Interest Via Personalizationcited by 1
  22. 2026Reasoning-guided Collaborative Filtering with Language Models for Explainable Recommendationcited by 1
  23. 2026Offline Reasoning for Efficient Recommendation: LLM-Empowered Persona-Profiled Item Indexingcited by 1
  24. 2026F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Rankingcited by 1
  25. 2024Exploring Applications of State Space Models and Advanced Training Techniques in Sequential Recommendations: A Comparative Study on Efficiency and Performancecited by 0
  26. 2024Transferable Sequential Recommendation via Vector Quantized Meta Learningcited by 0
  27. 2025LlamaRec-LKG-RAG: A Single-Pass, Learnable Knowledge Graph-RAG Framework for LLM-Based Rankingcited by 0
  28. 2026Facet-Aware Multi-Head Mixture-of-Experts Model with Text-Enhanced Pre-training for Sequential Recommendationcited by 0
  29. 2026GRAB: An LLM-Inspired Sequence-First Click-Through Rate Prediction Modeling Paradigmcited by 0
  30. 2026VLM4Rec: Multimodal Semantic Representation for Recommendation with Large Vision-Language Modelscited by 0
  31. 2026Filling the Gaps: Selective Knowledge Augmentation for LLM Recommenderscited by 0
  32. 2026SRBench: A Comprehensive Benchmark for Sequential Recommendation with Large Language Modelscited by 0
  33. 2026HORIZON: A Benchmark for In-the-wild User Behaviour Modelingcited by 0
  34. 2026Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillationcited by 0
  35. 2026TimeMM: Time-as-Operator Spectral Filtering for Dynamic Multimodal Recommendationcited by 0
  36. 2026Meta-Modal Agent: Sequential Evidence Routing for Missing-Modality Candidate Rerankingcited by 0
  37. 2026Hierarchical Latent Reasoning for LLM-based Recommendationcited by 0
  38. 2026rEDMRec: Distilling Large Language Model Reasoning into an Editable Experience Memory for Recommendationcited by 0

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