A new adjoint matching framework formulates flow model alignment as optimal control, enabling direct regression training and terminal-trajectory truncation for efficiency gains on models like SiT-XL and FLUX.
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TrajDLM applies block diffusion language models to discrete road-segment sequences with topology constraints to generate realistic trajectories up to 2.8 times faster than prior methods while supporting zero-shot transfer.
BRIDGE improves coarse-mask local image editing in DiT models by routing background and subject paths separately and using a discrete geometric gate on positional embeddings to reduce mask-shape bias.
citing papers explorer
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Improved techniques for fine-tuning flow models via adjoint matching: a deterministic control pipeline
A new adjoint matching framework formulates flow model alignment as optimal control, enabling direct regression training and terminal-trajectory truncation for efficiency gains on models like SiT-XL and FLUX.
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TrajDLM: Topology-Aware Block Diffusion Language Model for Trajectory Generation
TrajDLM applies block diffusion language models to discrete road-segment sequences with topology constraints to generate realistic trajectories up to 2.8 times faster than prior methods while supporting zero-shot transfer.
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BRIDGE: Background Routing and Isolated Discrete Gating for Coarse-Mask Local Editing
BRIDGE improves coarse-mask local image editing in DiT models by routing background and subject paths separately and using a discrete geometric gate on positional embeddings to reduce mask-shape bias.