On the public citation graph

Tapping the Potential of Large Language Models as Recommender Systems: A Comprehensive Framework and Empirical Analysis

https://doi.org/10.1145/3726871
0 signed · 93 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/(sici)1097-4571(199401)45:1<12::aid-asi2>3.0.co;2-lopenalex-snapshot
The relationship between Recall and Precision
inferredcites →https://doi.org/10.1007/978-3-031-56060-6_24openalex-snapshot
Large Language Models are Zero-Shot Rankers for Recommender Systems
inferredcites →https://doi.org/10.1007/978-981-97-5569-1_18openalex-snapshot
Unlocking the Potential of Large Language Models for Explainable Recommendations
inferredcites →https://doi.org/10.1007/s11280-024-01276-1openalex-snapshot
When large language models meet personalization: perspectives of challenges and opportunities
inferredcites →https://doi.org/10.1007/s11280-024-01291-2openalex-snapshot
A survey on large language models for recommendation
inferredcites →https://doi.org/10.1007/s11704-024-40231-1openalex-snapshot
A survey on large language model based autonomous agents
inferredcites →https://doi.org/10.1016/j.tbench.2023.100089openalex-snapshot
An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges
inferredcites →https://doi.org/10.1109/access.2024.3368027openalex-snapshot
Empowering Few-Shot Recommender Systems With Large Language Models-Enhanced Representations
inferredcites →https://doi.org/10.1109/jas.2023.123618openalex-snapshot
A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development
inferredcites →https://doi.org/10.1109/tkde.2024.3392335openalex-snapshot
Recommender Systems in the Era of Large Language Models (LLMs)
inferredcites →https://doi.org/10.1145/2827872openalex-snapshot
The MovieLens Datasets
inferredcites →https://doi.org/10.1145/2988450.2988454openalex-snapshot
Wide & Deep Learning for Recommender Systems
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3397271.3401063openalex-snapshot
LightGCN
inferredcites →https://doi.org/10.1145/3404835.3463069openalex-snapshot
Empowering News Recommendation with Pre-trained Language Models
inferredcites →https://doi.org/10.1145/3459637.3482016openalex-snapshot
RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms
inferredcites →https://doi.org/10.1145/3511808.3557101openalex-snapshot
Multimodal Meta-Learning for Cold-Start Sequential Recommendation
inferredcites →https://doi.org/10.1145/3511808.3557680openalex-snapshot
RecBole 2.0: Towards a More Up-to-Date Recommendation Library
inferredcites →https://doi.org/10.1145/3523227.3546767openalex-snapshot
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)
inferredcites →https://doi.org/10.1145/3539597.3570384openalex-snapshot
Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation
inferredcites →https://doi.org/10.1145/3539618.3591889openalex-snapshot
Towards a More User-Friendly and Easy-to-Use Benchmark Library for Recommender Systems
inferredcites →https://doi.org/10.1145/3539618.3591932openalex-snapshot
Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited
inferredcites →https://doi.org/10.1145/3560815openalex-snapshot
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
inferredcites →https://doi.org/10.1145/3580488openalex-snapshot
Personalized Prompt Learning for Explainable Recommendation
inferredcites →https://doi.org/10.1145/3583780.3615017openalex-snapshot
Prompt Distillation for Efficient LLM-based Recommendation
inferredcites →https://doi.org/10.1145/3589334.3645347openalex-snapshot
Collaborative Large Language Model for Recommender Systems
inferredcites →https://doi.org/10.1145/3589334.3645458openalex-snapshot
Representation Learning with Large Language Models for Recommendation
inferredcites →https://doi.org/10.1145/3589334.3645467openalex-snapshot
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
inferredcites →https://doi.org/10.1145/3604915.3608829openalex-snapshot
Large Language Model Augmented Narrative Driven Recommendations
inferredcites →https://doi.org/10.1145/3604915.3608845openalex-snapshot
Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences
inferredcites →https://doi.org/10.1145/3604915.3608857openalex-snapshot
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
inferredcites →https://doi.org/10.1145/3604915.3608860openalex-snapshot
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
inferredcites →https://doi.org/10.1145/3604915.3610639openalex-snapshot
Leveraging Large Language Models for Sequential Recommendation
inferredcites →https://doi.org/10.1145/3604915.3610646openalex-snapshot
Uncovering ChatGPT’s Capabilities in Recommender Systems
inferredcites →https://doi.org/10.1145/3616855.3635853openalex-snapshot
LLMRec: Large Language Models with Graph Augmentation for Recommendation
inferredcites →https://doi.org/10.1145/3624918.3625339openalex-snapshot
How to Index Item IDs for Recommendation Foundation Models
inferredcites →https://doi.org/10.1145/3626772.3657807openalex-snapshot
Data-efficient Fine-tuning for LLM-based Recommendation
inferredcites →https://doi.org/10.1145/3626772.3657821openalex-snapshot
IDGenRec: LLM-RecSys Alignment with Textual ID Learning
inferredcites →https://doi.org/10.1145/3627673.3679569openalex-snapshot
Learnable Item Tokenization for Generative Recommendation
inferredcites →https://doi.org/10.1145/3627673.3679922openalex-snapshot
Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems
inferredcites →https://doi.org/10.1145/3627673.3679987openalex-snapshot
RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models
inferredcites →https://doi.org/10.1145/3640457.3688121openalex-snapshot
CALRec: Contrastive Alignment of Generative LLMs for Sequential Recommendation
inferredcites →https://doi.org/10.1145/3690655openalex-snapshot
Understanding Biases in ChatGPT-based Recommender Systems: Provider Fairness, Temporal Stability, and Recency
inferredcites →https://doi.org/10.1145/3698878openalex-snapshot
A Unified Framework for Multi-Domain CTR Prediction via Large Language Models
inferredcites →https://doi.org/10.1145/3700604openalex-snapshot
Enhancing Recommendation Diversity by Re-ranking with Large Language Models
inferredcites →https://doi.org/10.1145/3704999openalex-snapshot
Understanding Before Recommendation: Semantic Aspect-Aware Review Exploitation via Large Language Models
inferredcites →https://doi.org/10.1145/3705728openalex-snapshot
RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation
inferredcites →https://doi.org/10.1145/3708882openalex-snapshot
Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach
inferredcites →https://doi.org/10.1145/582415.582418openalex-snapshot
Cumulated gain-based evaluation of IR techniques
inferredcites →https://doi.org/10.1561/1500000019openalex-snapshot
The Probabilistic Relevance Framework: BM25 and Beyond
inferredcites →https://doi.org/10.1609/aaai.v35i5.16557openalex-snapshot
U-BERT: Pre-training User Representations for Improved Recommendation
inferredcites →https://doi.org/10.1609/aaai.v38i8.28769openalex-snapshot
Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations
inferredcites →https://doi.org/10.18653/v1/2023.emnlp-main.621openalex-snapshot
Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models
inferredcites →https://doi.org/10.2139/ssrn.4749402openalex-snapshot
Controlrec: Bridging the Semantic Gap between Language Model and Personalized Recommendation
inferredcites →https://doi.org/10.24963/ijcai.2017/239openalex-snapshot
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
inferredcites →https://doi.org/10.3390/electronics12224654openalex-snapshot
BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model
inferredcites →https://doi.org/10.48550/arxiv.1205.2618openalex-snapshot
BPR: Bayesian Personalized Ranking from Implicit Feedback
inferredcites →https://doi.org/10.48550/arxiv.1910.10683openalex-snapshot
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
inferredcites →https://doi.org/10.48550/arxiv.2005.11401openalex-snapshot
Affordance-Compiled Intelligence: Observable-Only Cognitive Impedance Matching for No-Meta LLM-Integrated Systems
inferredcites →https://doi.org/10.48550/arxiv.2005.14165openalex-snapshot
Language Models are Few-Shot Learners
inferredcites →https://doi.org/10.48550/arxiv.2201.11903openalex-snapshot
BNAI, NO-TOKEN, and MIND-UNITY: Pillars of a Systemic Revolution in Artificial Intelligence
inferredcites →https://doi.org/10.48550/arxiv.2210.11416openalex-snapshot
Scaling Instruction-Finetuned Language Models
inferredcites →https://doi.org/10.48550/arxiv.2302.00923openalex-snapshot
Multimodal Chain-of-Thought Reasoning in Language Models
inferredcites →https://doi.org/10.48550/arxiv.2305.18290openalex-snapshot
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
inferredcites →https://doi.org/10.52202/075280-1213openalex-snapshot
Lending Interaction Wings to Recommender Systems with Conversational Agents
inferredcites →https://doi.org/10.5555/184656.180369openalex-snapshot
The relationship between recall and precision

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-88720-8_33openalex-snapshot
Cooperative and Competitive LLM-Based Multi-Agent Systems for Recommendation
inferred← citeshttps://doi.org/10.1007/978-981-96-1210-9_10openalex-snapshot
LLM-Enhanced Collaborative Filtering for Personalized Recommendation
inferred← citeshttps://doi.org/10.1007/s00521-024-10866-zopenalex-snapshot
In-depth survey: deep learning in recommender systems—exploring prediction and ranking models, datasets, feature analysis, and emerging trends
inferred← citeshttps://doi.org/10.1007/s44366-025-0059-6openalex-snapshot
Current Trends and Future Prospects of Large-Scale Foundation Model in K-12 Education
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.113234openalex-snapshot
Personalised healthy food text recommendations through fuzzy linguistic variables: A generative AI-based approach
inferred← citeshttps://doi.org/10.1016/j.ipm.2024.103938openalex-snapshot
Sequential recommendation by reprogramming pretrained transformer
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.130753openalex-snapshot
Recommendation systems with LLM-based semantic embeddings and FAISS similarity search
inferred← citeshttps://doi.org/10.1038/s41598-026-37075-zopenalex-snapshot
Knowledge-grounded large language model for personalized sports training plan generation
inferred← citeshttps://doi.org/10.1109/2575-8411.2026.00067openalex-snapshot
RcLLM: Accelerating Generative Recommendation via Beyond-Prefix KV Caching
inferred← citeshttps://doi.org/10.1109/aiac68175.2025.11332469openalex-snapshot
PEMM-REC: A Prompt Engineering-Based Semantic Alignment Framework for Large Multimodal Model Recommender System
inferred← citeshttps://doi.org/10.1109/bigdata66926.2025.11401642openalex-snapshot
Exploring the Impact of Large Language Models on Recommender Systems: An Extensive Review
inferred← citeshttps://doi.org/10.1109/cascon62161.2024.10837708openalex-snapshot
FaultLLAMA2: A Fine Tuned Large Language Model for Code Recommendations to Reduce Java Lock Contention
inferred← citeshttps://doi.org/10.1109/iccies63851.2025.11032798openalex-snapshot
Chrono Linguistic Modelling through AI Driven Conceptual Frameworks
inferred← citeshttps://doi.org/10.1109/iecon58223.2025.11221498openalex-snapshot
Generative AI Assistant for Netlist Generation and Smart Component Suggestion Using Knowledge Graphs and Retrieval Augmented Generation
inferred← citeshttps://doi.org/10.1109/tcss.2026.3669970openalex-snapshot
KDG-Rec: Enhanced Dual-GNN Programming Exercise Recommendation via LLM-Powered Knowledge Annotation and Preference-Decoupling
inferred← citeshttps://doi.org/10.1145/3669754.3669821openalex-snapshot
Zeroshot Listwise Learning to Rank Algorithm for Recommendation
inferred← citeshttps://doi.org/10.1145/3746252.3761369openalex-snapshot
LangPTune: Optimizing Language-based User Profiles for Recommendation
inferred← citeshttps://doi.org/10.20944/preprints202507.0515.v1openalex-snapshot
A Predictive Modeling Approach Based on Curriculum Meta-Learning and Attention-Enriched DeepFM for Sparse Data Scenarios
inferred← citeshttps://doi.org/10.21203/rs.3.rs-7122121/v1openalex-snapshot
QualiPilot – an offline AI tool for qualitative content analysis
inferred← citeshttps://doi.org/10.2139/ssrn.5341184openalex-snapshot
A Study of Hybrid DeepFM Frameworks Enhanced with Self-Attention and Meta-Learning for Accurate Product Usage Forecasting
inferred← citeshttps://doi.org/10.2139/ssrn.5341186openalex-snapshot
A Comprehensive Review of DeepFM-Based Predictive Models with Integrated Attention Layers and Meta-Learning Approaches
inferred← citeshttps://doi.org/10.2139/ssrn.5341192openalex-snapshot
Development and Validation of a Lightweight DeepFM Model with Attention-Driven Feature Selection and Meta-Learning Tuning
inferred← citeshttps://doi.org/10.2139/ssrn.5341198openalex-snapshot
Exploring the Role of Dual Attention in DeepFM Networks Enhanced by Meta-Learning for E-Commerce Usage Prediction
inferred← citeshttps://doi.org/10.26599/tst.2025.9010137openalex-snapshot
Large Language Models for Recommender Systems: A Problem-Driven Survey
inferred← citeshttps://doi.org/10.3390/electronics14153153openalex-snapshot
Large Language Models for Structured and Semi-Structured Data, Recommender Systems and Knowledge Base Engineering: A Survey of Recent Techniques and Architectures
inferred← citeshttps://doi.org/10.3390/electronics14224448openalex-snapshot
Context-Aware Tourism Recommendations Using Retrieval-Augmented Large Language Models and Semantic Re-Ranking
inferred← citeshttps://doi.org/10.36227/techrxiv.170956672.21573677/v1openalex-snapshot
Evaluating Large Language Models: ChatGPT-4, Mistral 8x7B, and Google Gemini Benchmarked Against MMLU
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.