We present a Generative World Simulation framework that couples persistent shared world state with continuous first-person audiovisual generation. The framework integrates DAO, a computable world engine, and JING, an Egocentric Interactive Experience Model, to support sustained interaction for humans and agents. DAO ma...
Xgen Team Guohao Cai, Hao-Xuan Che, Frank Fan et al.· 1 citation
It is demonstrated that strengthening the understanding capability of the Boogu-Image system, through a stronger multimodal encoder, agentic prompt rewriting, and related techniques, together with improvements in data quality, training pipelines, and agentic inference-time scaling, can substantially enhance generation...
Guoxuan Chen, Chufeng Xiao, Haoran Yang et al.· arXiv.org· 3 citations
Unified image and video creation requires a model to follow diverse instructions while preserving identity, geometry, and temporal structure from visual context. However, semantic-only conditioning and creation-only training do not explicitly supervise the local structure needed for precise, temporally consistent editi...
Zhe-Fan Rao, Bin-Yi Zou, Xuanhua He et al.· 0 citations
This work proposes OPTD, On-Policy Transition Distillation with consistency-guided adaptive compression, which consistently improves the quality--efficiency trade-off and attains the strongest overall quality-constrained AUP among the evaluated few-step baselines.
Xiaocheng Lu, Hualei Zhang, Shuhan Guo et al.· 0 citations
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