Unified audio-video creation requires a single model capable of text-conditioned joint synthesis, bidirectional cross-modal generation, and instruction-guided editing across both modalities. Existing methods rely heavily on paired corpora, which are scarce for joint generation and even rarer for editing. Consequently,...
Kien T. Pham, Yu-Hao Liu, C. Choi et al.· 0 citations
D-Loop is proposed, which introduces \emph{intra-block causal conditioning} within the original diffusion drafter without additional model components, and can beat DFlash and DSpark on Qwen3-4B and Qwen3-8B with obvious gains.
Ke-Cheng Chen, Yu-Yang He, Cheng Gong et al.· 0 citations
SAP combines state guidance, tool-argument provenance constraints, and turn-level validation to efficiently construct tool-use trajectories with long-range dependencies and high accuracy.
Zi-Chen Tian, Jin-Peng Chen, Cheng Gong 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
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