FlowBender: Feedback-Aware Training for Self-Correcting Conditional Flows
FlowBender is a closed-loop framework that addresses constraint satisfaction in diffusion and flow models by training networks to correct alignment errors using inference-time feed…
Hugging Face · Daily Papers
·Daniel Gilo, Sven Elflein
·
·▲ 20 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Daniel Gilo, Sven Elflein, Ido Sobol, Or Litany
- 20 upvotes da comunidade
- Temas: conditional diffusion models, flow models, alignment error, closed-loop framework, unguided look-ahead pass, refinement pass
Resumo
Resumo original (em inglês), extraído do paper:
FlowBender is a closed-loop framework that addresses constraint satisfaction in diffusion and flow models by training networks to correct alignment errors using inference-time feedback, outperforming traditional supervised and guidance-based approaches across multiple tasks.
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