mlsanityData to 7 Oct 2026

Large Language Models for Intent-Driven Session Recommendations

arXiv 2312.07552 ↗First posted 7 Dec 2023cs.CL cs.LGcited by 30

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Abstract (arXiv)

Intent-aware session recommendation (ISR) is pivotal in discerning user intents within sessions for precise predictions. Traditional approaches, however, face limitations due to their presumption of a uniform number of intents across all sessions. This assumption overlooks the dynamic nature of user sessions, where the number and type of intentions can significantly vary. In addition, these methods typically operate in latent spaces, thus hinder the model's transparency.Addressing these challenges, we introduce a novel ISR approach, utilizing the advanced reasoning capabilities of large language models (LLMs). First, this approach begins by generating an initial prompt that guides LLMs to predict the next item in a session, based on the varied intents manifested in user sessions. Then, to refine this process, we introduce an innovative prompt optimization mechanism that iteratively self-reflects and adjusts prompts. Furthermore, our prompt selection module, built upon the LLMs' broad adaptability, swiftly selects the most optimized prompts across diverse domains. This new paradigm empowers LLMs to discern diverse user intents at a semantic level, leading to more accurate and interpretable session recommendations. Our extensive experiments on three real-world datasets demonstrate the effectiveness of our method, marking a significant advancement in ISR systems.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 31 of its 61 references that are in the map. First posted on arXiv 7 Dec 2023.

Builds on

31 of 61 references.

References · 31

  1. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,769
  2. 2018Self-Attentive Sequential Recommendationcited by 1,169
  3. 2019BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformercited by 952
  4. 2015Session-based Recommendations with Recurrent Neural Networkscited by 685
  5. 2023Automatic Prompt Optimization with "Gradient Descent" and Beam Searchcited by 628
  6. 2023TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendationcited by 336
  7. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 307
  8. 2017Neural Attentive Session-based Recommendationcited by 237
  9. 2017Recurrent Neural Networks with Top-k Gains for Session-based Recommendationscited by 165
  10. 2023Uncovering ChatGPT's Capabilities in Recommender Systemscited by 160
  11. 2023Large Language Models as Zero-Shot Conversational Recommenderscited by 126
  12. 2023GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretationcited by 101
19 more
  1. 2016Improved Recurrent Neural Networks for Session-based Recommendationscited by 86
  2. 2021Global Context Enhanced Graph Neural Networks for Session-based Recommendationcited by 81
  3. 2023Leveraging Large Language Models for Sequential Recommendationcited by 78
  4. 2020Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendationcited by 75
  5. 2023A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systemscited by 73
  6. 2023Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferencescited by 66
  7. 2019Rethinking the Item Order in Session-based Recommendation with Graph Neural Networkscited by 43
  8. 2022Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Networkcited by 38
  9. 2018Evaluation of Session-based Recommendation Algorithmscited by 37
  10. 2022CORE: Simple and Effective Session-based Recommendation within Consistent Representation Spacecited by 37
  11. 2020TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendationcited by 33
  12. 2022DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluationcited by 19
  13. 2023Large Language Model Can Interpret Latent Space of Sequential Recommendercited by 19
  14. 2023Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendationcited by 14
  15. 2019Improving End-to-End Sequential Recommendations with Intent-aware Diversificationcited by 12
  16. 2022Evolutionary Preference Learning via Graph Nested GRU ODE for Session-based Recommendationcited by 11
  17. 2022S-Walk: Accurate and Scalable Session-based Recommendationwith Random Walkscited by 5
  18. 2022Implicit Session Contexts for Next-Item Recommendationscited by 5
  19. 2022Understanding Diversity in Session-Based Recommendationcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 16; 2026: 6.

30 papers.

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  1. 2025Reinforced Latent Reasoning for LLM-based Recommendationcited by 46
  2. 2024Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyondcited by 26
  3. 2024Large Language Models and Video Games: A Preliminary Scoping Reviewcited by 23
  4. 2025Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1Mcited by 12
  5. 2025Improving LLM-powered Recommendations with Personalized Informationcited by 9
  6. 2024Re2LLM: Reflective Reinforcement Large Language Model for Session-based Recommendationcited by 8
  7. 2024Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendationcited by 8
  8. 2024Active Large Language Model-based Knowledge Distillation for Session-based Recommendationcited by 6
  9. 2025Toward Super Agent System with Hybrid AI Routerscited by 6
  10. 2025Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Modelcited by 6
  11. 2025SessionIntentBench: A Multi-task Inter-session Intention-shift Modeling Benchmark for E-commerce Customer Behavior Understandingcited by 6
  12. 2025Role-Augmented Intent-Driven Generative Search Engine Optimizationcited by 5
18 more
  1. 2025AIP: Subverting Retrieval-Augmented Generation via Adversarial Instructional Promptcited by 5
  2. 2024Multi-view Intent Learning and Alignment with Large Language Models for Session-based Recommendationcited by 3
  3. 2025Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimizationcited by 2
  4. 2024IntentRec: Predicting User Session Intent with Hierarchical Multi-Task Learningcited by 1
  5. 2025Distilling Transitional Pattern to Large Language Models for Multimodal Session-based Recommendationcited by 1
  6. 2025Does Knowledge Distillation Matter for Large Language Model based Bundle Generation?cited by 1
  7. 2025Augment or Not? A Comparative Study of Pure and Augmented Large Language Model Recommenderscited by 1
  8. 2025LightKG: Efficient Knowledge-Aware Recommendations with Simplified GNN Architecturecited by 1
  9. 2025Routing Distilled Knowledge via Mixture of LoRA Experts for Large Language Model based Bundle Generationcited by 1
  10. 2026LLMGreenRec: LLM-Based Multi-Agent Recommender System for Sustainable E-Commercecited by 1
  11. 2026R3-REC: Reasoning-Driven Recommendation via Retrieval-Augmented LLMs over Multi-Granular Interest Signalscited by 1
  12. 2024MRP-LLM: Multitask Reflective Large Language Models for Privacy-Preserving Next POI Recommendationcited by 0
  13. 2025LatentCRS: A Variational EM Framework for Bridging Semantics and Behavior in LLM-based Conversational Recommendationcited by 0
  14. 2025CORONA: A Coarse-to-Fine Framework for Graph-based Recommendation with Large Language Modelscited by 0
  15. 2026A Reproducibility Analysis of PO4ISR: Diagnosing and Mitigating Semantic Drift in LLM-Based Session Recommendationcited by 0
  16. 2026SAERec: Constructing Fine-grained Interpretable Intents Priors via Sparse Autoencoders for Recommendationcited by 0
  17. 2026TRACE: Transition-Aware Residual Control for Multi-Objective Materials Discoverycited by 0
  18. 2026Continual Graph Memory for Adaptive Recommendation under Intent Driftcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Revisiting Prompt Engineering: A Comprehensive Evaluation for LLM-based Personalized Recommendation
  2. 2025Intent-Guided Reasoning for Sequential Recommendation ↗
  3. 2025MemGuide: Intent-Driven Memory Selection for Goal-Oriented Multi-Session LLM Agents
  4. 2025RecGPT-V2 Technical Report
  5. 2024Can Small Language Models be Good Reasoners for Sequential Recommendation?
  6. 2025iServe: An Intent-based Serving System for LLMs
  7. 2026rEDMRec: Distilling Large Language Model Reasoning into an Editable Experience Memory for Recommendation
  8. 2025MR.Rec: Synergizing Memory and Reasoning for Personalized Recommendation Assistant with LLMs