Hy-Nomas: Towards Free-form Interactive World Generation
Hy-Nomas is presented as a video world model with an 8B diffusion backbone that supports free-form text instructions and continuous camera control across multiple interaction turns. It generates variable-length segments conditioned on current inputs and cached history. Its design aligns structured video captions with action-aware causal attention, so descriptive context stays accessible across segments while action instructions are restricted to their intended temporal windows. A vision-language Prompt Enhancer translates user requests and interaction histories into structured conditions. A multi-stage curriculum leads into diffusion distillation. The authors report superior human-evaluation performance over existing world models and release weights, code and benchmarks.
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Hy-Nomas is presented as a video world model with an 8B diffusion backbone that supports free-form text instructions and continuous camera control across multiple interaction turns. It generates variable-length segments conditioned on current inputs and cached history. Its design aligns structured video captions with action-aware causal attention, so descriptive context stays accessible across segments while action instructions are restricted to their intended temporal windows. A vision-language Prompt Enhancer translates user requests and interaction histories into structured conditions. A multi-stage curriculum leads into diffusion distillation. The authors report superior human-evaluation performance over existing world models and release weights, code and benchmarks.
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Key findings from the stored brief
- Uses an 8B diffusion backbone supporting free-form text instructions and continuous camera control across multiple interaction turns.
- Aligns structured video captions with action-aware causal attention, restricting action instructions to their intended temporal windows.
- A vision-language Prompt Enhancer converts user requests and multimodal histories into structured conditions for the next segment.
- Reports superior human-evaluation results over existing world models; model weights, code and benchmarks are released.
Source claims not independently checked; the supplied text does not give the human-evaluation protocol or quantitative results.
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Evidence & sources
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Why this may matter
Open release of an interactive video world model with multi-turn text and camera control gives researchers a reproducible baseline for controllable, history-aware world generation.
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