Researchers have introduced Wan-Streamer v0.3, a new interaction model that conceptualizes video as a combination of a persistent "world" and a dynamic "event stream." This approach allows for general-purpose pretraining on video data, enabling models to predict how a world changes over time based on incoming input. The model has been applied to real-time, full-duplex audio-visual interaction, mapping multimodal user input to speech and behavioral actions with a response latency of approximately 200ms. AI
IMPACT Introduces a novel video pretraining task that could enhance multimodal understanding and real-time interaction capabilities in AI agents.
RANK_REASON The cluster contains research papers detailing a new model and interaction paradigm.
- arXiv
- Audio Interaction Model
- DuplexSLA
- Hugging Face
- Lianghua Huang
- StreamChar
- VideoFDB
- Vidu S1
- Wan-Streamer v0.1
- Wan-Streamer v0.2
- Wan-Streamer v0.3
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