Persona-L has Entered the Chat: Leveraging LLM and Ability-based Framework for Personas of People with Complex Needs
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Abstract (arXiv)
We present Persona-L, a novel approach for creating personas using Large Language Models (LLMs) and an ability-based framework, specifically designed to improve the representation of users with complex needs. Traditional methods of persona creation often fall short of accurately depicting the dynamic and diverse nature of complex needs, resulting in oversimplified or stereotypical profiles. Persona-L enables users to create and interact with personas through a chat interface. Persona-L was evaluated through interviews with UX designers (N=6), where we examined its effectiveness in reflecting the complexities of lived experiences of people with complex needs. We report our findings that indicate the potential of Persona-L to increase empathy and understanding of complex needs while also revealing the need for transparency of data used in persona creation, the role of the language and tone, and the need to provide a more balanced presentation of abilities with constraints.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Sep 2024.
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Citing papers per year: 2025: 6; 2026: 5.
11 papers.
- 2025Boosting Relational Deep Learning with Pretrained Tabular Modelscited by 9
- 2026KnowMe-Bench: Benchmarking Person Understanding for Lifelong Digital Companionscited by 9
- 2025Phraselette: A Poet's Procedural Palettecited by 4
- 2025Using AI for User Representation: An Analysis of 83 Persona Promptscited by 4
- 2025PersonaBOT: Bringing Customer Personas to Life with LLMs and RAGcited by 2
- 2025Synthia: Scalable Grounded Persona Generation from Social Media Datacited by 1
- 2026How to Model AI Agents as Personas?: Applying the Persona Ecosystem Playground to 41,300 Posts on Moltbook for Behavioral Insightscited by 1
- 2025Living the Novel: A System for Generating Self-Training Timeline-Aware Conversational Agents from Novelscited by 0
- 2026PersonaCite: VoC-Grounded Interviewable Agentic Synthetic AI Personas for Verifiable User and Design Researchcited by 0
- 2026Rules or Weights? Comparing User Understanding of Explainable AI Techniques with the Cognitive XAI-Adaptive Modelcited by 0
- 2026CHORUS: An Agentic Framework for Generating Realistic Deliberation Datacited by 0
- 2026CHORUS: An Agentic Framework for Generating Realistic Deliberation Data22 Apr 2026
- 2026How to Model AI Agents as Personas?: Applying the Persona Ecosystem Playground to 41,300 Posts on Moltbook for Behavioral Insights3 Mar 2026
- 2026Rules or Weights? Comparing User Understanding of Explainable AI Techniques with the Cognitive XAI-Adaptive Model23 Feb 2026
- 2026PersonaCite: VoC-Grounded Interviewable Agentic Synthetic AI Personas for Verifiable User and Design Research29 Jan 2026
- 2026KnowMe-Bench: Benchmarking Person Understanding for Lifelong Digital Companions8 Jan 2026
- 2025Living the Novel: A System for Generating Self-Training Timeline-Aware Conversational Agents from Novels8 Dec 2025
- 2025Using AI for User Representation: An Analysis of 83 Persona Prompts18 Aug 2025
- 2025Synthia: Scalable Grounded Persona Generation from Social Media Data20 Jul 2025
- 2025PersonaBOT: Bringing Customer Personas to Life with LLMs and RAG22 May 2025
- 2025Boosting Relational Deep Learning with Pretrained Tabular Models7 Apr 2025
- 2025Phraselette: A Poet's Procedural Palette8 Mar 2025