🔗 Who cites «Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback»

37 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback»

1. Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language ModelsarXiv:2304.01852 · Meta-Radiology (2023)100,017Yiheng Liu, Tianle Han, Siyuan Ma, et al.2023 · 940 citations
2. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
3. LaMP: When Large Language Models Meet PersonalizationAnnual Meeting of the Association for Computational Linguistics (ACL)Alireza Salemi, Sheshera Mysore, Michael Bendersky, et al.2024 · 246 citations
4. Large Language Models Meet Harry Potter: A Dataset for Aligning Dialogue Agents with CharactersFindings of the Association for Computational LinguisticsNuo Chen, Yan Wang, Haiyun Jiang, et al.2023 · 81 citations
5. The Art of Saying No: Contextual Noncompliance in Language ModelsConference on Neural Information Processing Systems (NeurIPS)Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.2024 · 56 citations
6. NormAd: A Framework for Measuring the Cultural Adaptability of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Abhinav Rao, Akhila Yerukola, Vishwa Shah, et al.2025 · 46 citations
7. Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data RefinementInternational Conference on Computational Linguistics (COLING)Chenkai Sun, Ke Yang, Revanth Gangi Reddy, et al.2025 · 29 citations

30 more papers of our library cite it; they have no page here yet.

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