paper-with-me

홈 › Papers

Does Persona Make LLMs K-pop Fans? A Pilot Study of LLM-Based Online Concert Audience Agents

2026-06-05 · Kirak Kim, Hyojin Kim, Yejin Son, Sungyoung Kim, Kyung Myun Lee arxiv

A concert is a collective experience, but recorded performance videos are typically watched alone, stripping away the shared audience presence that makes concerts feel eventful. We investigate whether persona-based LLM audience agents can recreate aspects of this collective experience by generating real-time fan chat alongside a K-pop performance video. We present a multi-agent system in which ten LLM agents react through live-chat messages, comparing a persona-conditioned audience (each agent assigned a distinct fan identity, bias, and chat style) with a no-persona baseline. In a within-subjects pilot with K-pop fans (N=11), persona conditioning substantially improved model-level chat quality and perceived naturalness, but did not translate into differences in social connectedness, engagement, or affective response. Interviews suggest that online K-pop concert chat may operate as collective monologue rather than interpersonal dialogue, and that meaningful participation depends on shared identification with the specific artist and fandom. Persona conditioning can make LLM audiences appear more natural, but culturally meaningful collective experience may require deeper alignment between persona, crowd behavior, fandom identity, and user expectations.

📄 PDF Abstract BibTeX arXiv:2606.07837

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

PILOT: Steering Synthetic Data Generation with Psychological & Linguistic Output Targeting

2025-09-18 · Caitlin Cisar, Emily Sheffield, Joshua Drake, Alden Harrell 외 arxiv

Generative AI applications commonly leverage user personas as a steering mechanism for synthetic data generation, but reliance on natural language representations forces models to make unintended inferences about which a…

Synthetic Data Generation

FANS -- Formal Answer Selection for Natural Language Math Reasoning Using Lean4

2025-03-05 · Jiarui Yao, Ruida Wang, Tong Zhang

Large Language Models (LLMs) have displayed astonishing abilities in various tasks, especially in text generation, classification, question answering, etc. However, the reasoning ability of LLMs still faces many debates.…

Answer SelectionMathQuestion AnsweringText Generation

PerPilot: Personalizing VLM-based Mobile Agents via Memory and Exploration

2025-08-25 · Xin Wang, Zhiyao Cui, Hao Li, Ya Zeng 외 arxiv

Vision language model (VLM)-based mobile agents show great potential for assisting users in performing instruction-driven tasks. However, these agents typically struggle with personalized instructions -- those containing…

FaNS: a Facet-based Narrative Similarity Metric

2023-09-09 · Mousumi Akter, Shubhra Kanti Karmaker Santu

Similar Narrative Retrieval is a crucial task since narratives are essential for explaining and understanding events, and multiple related narratives often help to create a holistic view of the event of interest. To accu…

Retrievaltext similarity

PersoPilot: An Adaptive AI-Copilot for Transparent Contextualized Persona Classification and Personalized Response Generation

2026-02-04 · Saleh Afzoon, Amin Beheshti, Usman Naseem arxiv

Understanding and classifying user personas is critical for delivering effective personalization. While persona information offers valuable insights, its full potential is realized only when contextualized, linking user …

Response GenerationActive Learning