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cs.CV2026
Beyond Attention Masks: Instruction Anchoring for Efficient In-Context Diffusion Generation
Yangshuai Liu, Zheming Li, Jiaao Li +4
In-context diffusion transformers concatenate instruction, target, and reference tokens into a single sequence for joint attention. Reference-side computation must therefore be rep…
cs.CV2026
HeadCast: Casting Attention Heads for Efficient Autoregressive Video Generation
Jinliang Shen, Lianghao Su, Zheming Li +4
Autoregressive (AR) video diffusion models have become a promising paradigm for long and streaming video synthesis, but the continuously growing Key-Value (KV) cache makes attentio…