Towards Interactive Intelligence for Digital Humans
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Abstract (arXiv)
We introduce Interactive Intelligence, a novel paradigm of digital human that is capable of personality-aligned expression, adaptive interaction, and self-evolution. To realize this, we present Mio (Multimodal Interactive Omni-Avatar), an end-to-end framework composed of five specialized modules: Thinker, Talker, Face Animator, Body Animator, and Renderer. This unified architecture integrates cognitive reasoning with real-time multimodal embodiment to enable fluid, consistent interaction. Furthermore, we establish a new benchmark to rigorously evaluate the capabilities of interactive intelligence. Extensive experiments demonstrate that our framework achieves superior performance compared to state-of-the-art methods across all evaluated dimensions. Together, these contributions move digital humans beyond superficial imitation toward intelligent interaction.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 107 of its 147 references that are in the map. First posted on arXiv 15 Dec 2025.
Builds on
107 of 147 references.
References · 107
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38 more
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50 most cited of 107 All 107 (JSON)
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Citing papers per year: 2026: 10.
10 papers.
- 2026LPM 1.0: Video-based Character Performance Modelcited by 11
- 2026Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Modelscited by 7
- 2026ProAct: Harnessing Streaming Motion Generation and Agentic Reasoning for Real-Time Embodied Social Interactioncited by 3
- 2026InteracVid: Building a Real Interactive Audio-Visual Response Dataset from Live-Chat Videoscited by 2
- 2026UMo: Unified Sparse Motion Modeling for Real-Time Co-Speech Avatarscited by 1
- 2026Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?cited by 1
- 2026ECHO: Towards Emotionally Appropriate and Contextually Aware Interactive Head Generationcited by 0
- 2026Human-Centric Intelligence in the Era of Foundation Models: A Surveycited by 0
- 2026Super Star: Towards Streaming Real-time Interactive Agents for Digital Humanscited by 0
- 2026What Makes a Social Agent's Interactions Effective? Learning from Verifiable Outcomes in Paired Worldscited by 0
- 2026What Makes a Social Agent's Interactions Effective? Learning from Verifiable Outcomes in Paired Worlds14 Oct 2026
- 2026Human-Centric Intelligence in the Era of Foundation Models: A Survey18 Aug 2026
- 2026InteracVid: Building a Real Interactive Audio-Visual Response Dataset from Live-Chat Videos2 Aug 2026
- 2026Super Star: Towards Streaming Real-time Interactive Agents for Digital Humans22 Jul 2026
- 2026Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models23 Jun 2026
- 2026Perception or Prejudice: Can MLLMs Go Beyond First Impressions of Personality?21 May 2026
- 2026UMo: Unified Sparse Motion Modeling for Real-Time Co-Speech Avatars14 May 2026
- 2026LPM 1.0: Video-based Character Performance Model9 Apr 2026
- 2026ECHO: Towards Emotionally Appropriate and Contextually Aware Interactive Head Generation18 Mar 2026
- 2026ProAct: Harnessing Streaming Motion Generation and Agentic Reasoning for Real-Time Embodied Social Interaction15 Feb 2026