Beyond Attention Masks: Instruction Anchoring for Efficient In-Context Diffusion Generation

arXiv:2608.21229 · cs.CV · Submitted 2026-08-21 · Read on arXiv

cs.CV

Submitted: 2026-08-21

Updated: 2026-09-24

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Distillation — 31× in this paper · explained in 2 episodes
Transformer — 26× in this paper · explained in 2 episodes
Benchmark — 11× in this paper · explained in 2 episodes
On-Policy Distillation — 11× in this paper · explained in 3 episodes
Diffusion Model — 8× in this paper · explained in 8 episodes
Diffusion Models — 8× in this paper · explained in 6 episodes
Sparse Attention — 8× in this paper · explained in 5 episodes
Fidelity — 5× in this paper · explained in 2 episodes
Consistency — 4× in this paper · explained in 3 episodes
Aggregation — 3× in this paper · explained in 1 episode
Alignment — 2× in this paper · explained in 1 episode
Pruning — 2× in this paper · explained in 4 episodes
Quantization — 2× in this paper · explained in 12 episodes
Sparsity — 2× in this paper · explained in 4 episodes
Embeddings — 1× in this paper · explained in 2 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Flow Matching — 1× in this paper · explained in 8 episodes
Generative Model — 1× in this paper · explained in 2 episodes
Generative Modeling — 1× in this paper · explained in 3 episodes
Generative Models — 1× in this paper · explained in 2 episodes
KV cache — 1× in this paper · explained in 3 episodes
Rectified Flow — 1× in this paper · explained in 3 episodes

Sources

OmniGen2: Towards Instruction-Aligned Multimodal Generation

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