--- title: "Who cites TALLRec: An Effective and — 81 citing papers" description: "81 papers of the Elamur Research library cite «TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with…" canonical: "https://research.elamur.ai/free/en/papers/bao-2023-tallrec-effective-efficient-tuning-framework/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/bao-2023-tallrec-effective-efficient-tuning-framework/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [TALLRec: An Effective and Efficient Tuning…](https://md.research.elamur.ai/free/en/papers/bao-2023-tallrec-effective-efficient-tuning-framework/) / cited by # Who cites «TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation» 81 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation»](https://md.research.elamur.ai/free/en/papers/bao-2023-tallrec-effective-efficient-tuning-framework/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 2. **[WizardLM: Empowering large pre-trained language models to follow complex instructions](https://md.research.elamur.ai/free/en/papers/xu-2023-wizardlm-empowering-large-pre-trained/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Can Xu, Qingfeng Sun, Kai Zheng, et al.*2023 · 741 citations* 3. **[Large Language Models are Zero-Shot Rankers for Recommender Systems](https://md.research.elamur.ai/free/en/papers/hou-2023-large-language-models-zero-shot/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yupeng Hou, Junjie Zhang, Zihan Lin, et al.*2023 · 394 citations* 4. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/) 5. **[Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation](https://md.research.elamur.ai/free/en/papers/wang-2025-knowledge-graph-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shijie Wang, Wenqi Fan, Yue Feng, et al.*2025 · 77 citations* 6. **[OneRec-Think: In-Text Reasoning for Generative Recommendation](https://md.research.elamur.ai/free/en/papers/liu-2026-onerec-think-text-reasoning-generative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhanyu Liu, Shiyao Wang, Xingmei Wang, et al.*2026 · 10 citations* 7. **[What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context](https://md.research.elamur.ai/free/en/papers/ouyang-2026-what-makes-llms-effective-sequential/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang, et al.*2026 · 1 citation* 8. **[Adaptive and Representative Multi-Interest Modeling for Recommendation with Large Language Model](https://md.research.elamur.ai/free/en/papers/wang-2026-adaptive-representative-multi-interest-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziyan Wang, Yingpeng Du, Tianjun Wei, et al.*2026* 9. **[From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation](https://md.research.elamur.ai/free/en/papers/wei-2026-past-path-masked-history-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaiwen Wei, Kejun he, Xiaomian Kang, et al.*2026* 10. **[GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model Recommendation](https://md.research.elamur.ai/free/en/papers/mu-2026-graphlora-structure-aware-low-rank/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Mu, Guoji Wang, Li Ni, et al.*2026* 11. **[GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models](https://md.research.elamur.ai/free/en/papers/zhong-2026-groclm-grocery-category-recommendation-e/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuan Zhong, Chuanwei Ruan, Moein Hasani, et al.*2026* 12. **[Internalizing Multi-Agent Reasoning for Accurate and Efficient LLM-based Recommendation](https://md.research.elamur.ai/free/en/papers/wu-2026-internalizing-multi-agent-reasoning-accurate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yang Wu, Haoze Wang, Qian Li, et al.*2026* 13. **[PrePPER: A Preference Pattern-based Profiling Framework for Explainable Recommendation](https://md.research.elamur.ai/free/en/papers/usumi-2026-prepper-preference-pattern-based-profiling/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Taisuke Usumi, Akiko Masaki, Sanae Muramatsu, et al.*2026* 14. **[Unleashing the Native Recommendation Potential: LLM-Based Generative Recommendation via Structured Term Identifiers](https://md.research.elamur.ai/free/en/papers/zhang-2026-unleashing-native-recommendation-potential-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyang Zhang, Junda She, Kuo Cai, et al.*2026* 67 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/bao-2023-tallrec-effective-efficient-tuning-framework/) — TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation