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Empowering News Recommendation with Pre-trained Language Models

arXiv 2104.07413 ↗First posted 15 Apr 2021cs.IRcited by 63

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Abstract (arXiv)

Personalized news recommendation is an essential technique for online news services. News articles usually contain rich textual content, and accurate news modeling is important for personalized news recommendation. Existing news recommendation methods mainly model news texts based on traditional text modeling methods, which is not optimal for mining the deep semantic information in news texts. Pre-trained language models (PLMs) are powerful for natural language understanding, which has the potential for better news modeling. However, there is no public report that show PLMs have been applied to news recommendation. In this paper, we report our work on exploiting pre-trained language models to empower news recommendation. Offline experimental results on both monolingual and multilingual news recommendation datasets show that leveraging PLMs for news modeling can effectively improve the performance of news recommendation. Our PLM-empowered news recommendation models have been deployed to the Microsoft News platform, and achieved significant gains in terms of both click and pageview in both English-speaking and global markets.

Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Apr 2021.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 8; 2023: 14; 2024: 20; 2025: 14; 2026: 5.

63 papers.

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  1. 2023A Survey on Large Language Models for Recommendationcited by 378
  2. 2023How Can Recommender Systems Benefit from Large Language Models: A Surveycited by 141
  3. 2023When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunitiescited by 89
  4. 2021Fastformer: Additive Attention Can Be All You Needcited by 61
  5. 2024A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)cited by 58
  6. 2023ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Modelscited by 54
  7. 2024IDGenRec: LLM-RecSys Alignment with Textual ID Learningcited by 50
  8. 2022NoisyTune: A Little Noise Can Help You Finetune Pretrained Language Models Bettercited by 43
  9. 2023ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languagescited by 33
  10. 2023RAH! RecSys-Assistant-Human: A Human-Centered Recommendation Framework with LLM Agentscited by 30
  11. 2024IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFTcited by 26
  12. 2023Prompt Learning for News Recommendationcited by 25
38 more
  1. 2024LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendationscited by 24
  2. 2024LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Applicationcited by 21
  3. 2023UniTRec: A Unified Text-to-Text Transformer and Joint Contrastive Learning Framework for Text-based Recommendationcited by 20
  4. 2025LLM-Generated Fake News Induces Truth Decay in News Ecosystem: A Case Study on Neural News Recommendationcited by 19
  5. 2023Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendationscited by 16
  6. 2023Knowledge Prompt-tuning for Sequential Recommendationcited by 12
  7. 2024Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignmentcited by 8
  8. 2024RA-Rec: An Efficient ID Representation Alignment Framework for LLM-based Recommendationcited by 7
  9. 2026AMEM4Rec: Leveraging Cross-User Similarity for Memory Evolution in Agentic LLM Recommenderscited by 7
  10. 2024SPAR: Personalized Content-Based Recommendation via Long Engagement Attentioncited by 6
  11. 2025Rethinking the Privacy of Text Embeddings: A Reproducibility Study of "Text Embeddings Reveal (Almost) As Much As Text"cited by 6
  12. 2023Modeling User Viewing Flow Using Large Language Models for Article Recommendationcited by 4
  13. 2024EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendationscited by 4
  14. 2024News Recommendation with Category Description by a Large Language Modelcited by 4
  15. 2024News Without Borders: Domain Adaptation of Multilingual Sentence Embeddings for Cross-lingual News Recommendationcited by 4
  16. 2022GRAM: Fast Fine-tuning of Pre-trained Language Models for Content-based Collaborative Filteringcited by 3
  17. 2022Few-shot News Recommendation via Cross-lingual Transfercited by 3
  18. 2025MIM: Multi-modal Content Interest Modeling Paradigm for User Behavior Modelingcited by 3
  19. 2025Can LLMs Outshine Conventional Recommenders? A Comparative Evaluationcited by 3
  20. 2025From Millions of Tweets to Actionable Insights: Leveraging LLMs for User Profilingcited by 3
  21. 2025CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systemscited by 3
  22. 2022Two-Stage Neural Contextual Bandits for Personalised News Recommendationcited by 2
  23. 2023COURIER: Contrastive User Intention Reconstruction for Large-Scale Visual Recommendationcited by 2
  24. 2024UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systemscited by 2
  25. 2024Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Userscited by 2
  26. 2021On the Overlooked Significance of Underutilized Contextual Features in Recent News Recommendation Modelscited by 1
  27. 2022GateFormer: Speeding Up News Feed Recommendation with Input Gated Transformerscited by 1
  28. 2022Understanding the Relation of User and News Representations in Content-Based Neural News Recommendationcited by 1
  29. 2023PUNR: Pre-training with User Behavior Modeling for News Recommendationcited by 1
  30. 2024Time Matters: Enhancing Pre-trained News Recommendation Models with Robust User Dwell Time Injectioncited by 1
  31. 2024Laser: Parameter-Efficient LLM Bi-Tuning for Sequential Recommendation with Collaborative Informationcited by 1
  32. 2024Efficient Pointwise-Pairwise Learning-to-Rank for News Recommendationcited by 1
  33. 2024Peeling Back the Layers: An In-Depth Evaluation of Encoder Architectures in Neural News Recommenderscited by 1
  34. 2025A Survey on LLM-based News Recommender Systemscited by 1
  35. 2025Enhance Large Language Models as Recommendation Systems with Collaborative Filteringcited by 1
  36. 2026Improving LLM-based Recommendation with Self-Hard Negatives from Intermediate Layerscited by 1
  37. 2026EvoRec: Self Evolving Agentic Recommender Systemscited by 1
  38. 2022User recommendation system based on MIND datasetcited by 0

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