---
title: "Who cites Personalisation within bounds: A — 37 citing papers"
description: "37 papers of the Elamur Research library cite «Personalisation within bounds: A risk taxonomy and policy framework for the alignment of…"
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---
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# 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»](https://md.research.elamur.ai/free/en/papers/kirk-2023-personalisation-within-bounds-risk-taxonomy/)

1. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models arXiv:2304.01852 · Meta-Radiology (2023)100,017**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 940 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/)
2. **[Tool Learning with Foundation Models](https://md.research.elamur.ai/free/en/papers/qin-2023-tool-learning-foundation-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Yujia Qin, Shengding Hu, Yankai Lin, et al.*2023 · 383 citations*
3. **[LaMP: When Large Language Models Meet Personalization](https://md.research.elamur.ai/free/en/papers/salemi-2024-lamp-when-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/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 Characters](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-meet-harry/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nuo Chen, Yan Wang, Haiyun Jiang, et al.*2023 · 81 citations*
5. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations*
6. **[NormAd: A Framework for Measuring the Cultural Adaptability of Large Language Models](https://md.research.elamur.ai/free/en/papers/rao-2025-normad-framework-measuring-cultural-adaptability/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/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 Refinement](https://md.research.elamur.ai/free/en/papers/sun-2025-persona-db-efficient-large-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/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.

- [← back to](https://md.research.elamur.ai/free/en/papers/kirk-2023-personalisation-within-bounds-risk-taxonomy/) — Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback