12 citations · 13 across the 11 of their papers we have counts for
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cs.CV2026
Beyond Text Conditioning: A Systematic Study of MLLM-DiT Fusion for Video Generation
Yanbo Ding, Yijia Fan, Caihua Shan +8
Diffusion Transformers (DiTs) have become the dominant paradigm for high-fidelity video generation, yet their ability to perform high-level semantic planning remains limited. While…
cs.CV2026
Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners
Qingyang Liu, Bingjie Gao, Canmiao Fu +9
Recent unified models integrate multimodal understanding and generation within a single framework. However, an "understanding-generation gap" persists, where models can capture use…
cs.CV2026
WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens
Yiwei Guo, Shaobin Zhuang, Zhipeng Huang +4
Building a unified visual tokenizer is essential for bridging the gap between visual understanding and generation. Yet existing approaches struggle with the inherent conflict betwe…