mlsanityData to 14 Oct 2026

RecGPT: Generative Pre-training for Text-based Recommendation

arXiv 2405.12715 ↗First posted 21 May 2024cs.IR cs.CLcited by 9

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Abstract (arXiv)

We present the first domain-adapted and fully-trained large language model, RecGPT-7B, and its instruction-following variant, RecGPT-7B-Instruct, for text-based recommendation. Experimental results on rating prediction and sequential recommendation tasks show that our model, RecGPT-7B-Instruct, outperforms previous strong baselines. We are releasing our RecGPT models as well as their pre-training and fine-tuning datasets to facilitate future research and downstream applications in text-based recommendation. Public "huggingface" links to our RecGPT models and datasets are available at: https://github.com/VinAIResearch/RecGPT

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 24 of its 41 references that are in the map. First posted on arXiv 21 May 2024.

Builds on

24 of 41 references.

References · 24

  1. 2017Attention Is All You Needcited by 60,361
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  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
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  12. 2019BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformercited by 964
12 more
  1. 2016Wide & Deep Learning for Recommender Systemscited by 747
  2. 2015Image-based Recommendations on Styles and Substitutescited by 706
  3. 2015Session-based Recommendations with Recurrent Neural Networkscited by 695
  4. 2022Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)cited by 402
  5. 2020S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximizationcited by 311
  6. 2023Is ChatGPT a Good Recommender? A Preliminary Studycited by 193
  7. 2018DKN: Deep Knowledge-Aware Network for News Recommendationcited by 137
  8. 2023GenRec: Large Language Model for Generative Recommendationcited by 63
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  12. 2021Learning to Recommend Items to Wikidata Editorscited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 3.

9 papers.

  1. 2024Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyondcited by 26
  2. 2025A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigmscited by 17
  3. 2024Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendationcited by 8
  4. 2025Can LLMs Outshine Conventional Recommenders? A Comparative Evaluationcited by 3
  5. 2025CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systemscited by 3
  6. 2026Lightweight Fairness for LLM-Based Recommendations via Kernelized Projection and Gated Adapterscited by 1
  7. 2025SPECTRA: Revealing the Full Spectrum of User Preferences via Distributional LLM Inferencecited by 0
  8. 2026Give Users the Wheel: Towards Promptable Recommendation Paradigmcited by 0
  9. 2026RPCBench: A Benchmark for Proactive Premise Critique in LLM-based Recommendationcited by 0