LiveTalk: Real-Time Interactive Video Generation with Improved Distillation
Published:Dec 29, 2025 16:17
•1 min read
•ArXiv
Analysis
This paper addresses the challenge of real-time interactive video generation, a crucial aspect of building general-purpose multimodal AI systems. It focuses on improving on-policy distillation techniques to overcome limitations in existing methods, particularly when dealing with multimodal conditioning (text, image, audio). The research is significant because it aims to bridge the gap between computationally expensive diffusion models and the need for real-time interaction, enabling more natural and efficient human-AI interaction. The paper's focus on improving the quality of condition inputs and optimization schedules is a key contribution.
Key Takeaways
- •Proposes LiveTalk, a real-time multimodal interactive avatar system.
- •Improves on-policy distillation for better performance with multimodal conditioning.
- •Achieves significant reduction in inference cost and latency compared to baseline models.
- •Outperforms state-of-the-art models in multi-turn video coherence and content quality.
Reference
“The distilled model matches the visual quality of full-step, bidirectional baselines with 20x less inference cost and latency.”