Exploring Presence in Interactions with LLM-Driven NPCs: A Comparative Study of Speech Recognition and Dialogue Options

Опубликована: Сен. 22, 2024

Язык: Английский

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The Art of Replication: Lifelike Avatars with Personalized Conversational Style

Robotics, Год журнала: 2025, Номер 14(3), С. 33 - 33

Опубликована: Март 13, 2025

This study presents an approach for developing digital avatars replicating individuals’ physical characteristics and communicative style, contributing to research on virtual interactions in the metaverse. The proposed method integrates large language models (LLMs) with 3D avatar creation techniques, using what we call Tree of Style (ToS) methodology generate stylistically consistent contextually appropriate responses. Linguistic analysis personalized voice synthesis enhance conversational auditory realism. results suggest that ToS offers a practical alternative fine-tuning creating accurate responses while maintaining efficiency. outlines potential applications acknowledges need further work adaptability ethical considerations.

Язык: Английский

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Generative AI in Virtual Reality Communities: A Preliminary Analysis of the VRChat Discord Community

Опубликована: Апрель 23, 2025

Язык: Английский

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AI Agents and Agentic Systems: A Multi-Expert Analysis

Journal of Computer Information Systems, Год журнала: 2025, Номер unknown, С. 1 - 29

Опубликована: Апрель 24, 2025

Язык: Английский

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Toward Dynamic NPC Interactions: Integrating GPT-Driven Agents in 3D Virtual Environments

Lecture notes in computer science, Год журнала: 2025, Номер unknown, С. 199 - 211

Опубликована: Янв. 1, 2025

Язык: Английский

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Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation

Опубликована: Апрель 25, 2025

Student simulation supports educators to improve teaching by interacting with virtual students. However, most existing approaches ignore the modulation effects of course materials because two challenges: lack datasets granularly annotated materials, and limitation models in processing extremely long textual data. To solve challenges, we first run a 6-week education workshop from N = 60 students collect fine-grained data using custom built online system, which logs students' learning behaviors as they interact lecture over time. Second, propose transferable iterative reflection (TIR) module that augments both prompting-based finetuning-based large language (LLMs) for simulating behaviors. Our comprehensive experiments show TIR enables LLMs perform more accurate student than classical deep models, even limited demonstration approach better captures granular dynamism performance inter-student correlations classrooms, paving way towards ''digital twin'' education.

Язык: Английский

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Exploring Large Language Model-Driven Agents for Environment-Aware Spatial Interactions and Conversations in Virtual Reality Role-Play Scenarios

Опубликована: Март 8, 2025

Язык: Английский

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Danmaku Avatar: Enabling Asynchronous Co-viewing Experiences in Virtual Reality via Danmaku

Опубликована: Апрель 23, 2025

Язык: Английский

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EvAlignUX: Advancing UX Evaluation through LLM-Supported Metrics Exploration

Опубликована: Апрель 24, 2025

Язык: Английский

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Social Simulation for Everyday Self-Care: Design Insights from Leveraging VR, AR, and LLMs for Practicing Stress Relief

Опубликована: Апрель 24, 2025

Язык: Английский

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