SteeringDiffusion supplies a bottlenecked, prompt-conditioned activation interface for frozen diffusion models that delivers smooth monotonic content-style control via one runtime scalar and timestep gating.
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FaSTA* combines LLM fast planning with A* search and inductive subroutine mining to create an efficient agent for multi-turn image editing tasks.
Mamoda2.5 is a 25B-parameter DiT-MoE unified AR-Diffusion model that reaches top video generation and editing benchmarks with 4-step inference up to 95.9x faster than baselines.
citing papers explorer
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SteeringDiffusion: A Bottlenecked Activation Control Interface for Diffusion Models
SteeringDiffusion supplies a bottlenecked, prompt-conditioned activation interface for frozen diffusion models that delivers smooth monotonic content-style control via one runtime scalar and timestep gating.
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FaSTA$^*$: Fast-Slow Toolpath Agent with Subroutine Mining for Efficient Multi-turn Image Editing
FaSTA* combines LLM fast planning with A* search and inductive subroutine mining to create an efficient agent for multi-turn image editing tasks.
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Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE
Mamoda2.5 is a 25B-parameter DiT-MoE unified AR-Diffusion model that reaches top video generation and editing benchmarks with 4-step inference up to 95.9x faster than baselines.