FlowTool is a new framework for image retouching that models tool parameters as a flow matching problem, using a vision-language model and diffusion transformer to generate editing plans. It outperforms specialized MLLM agents and proprietary models in reference-based evaluations while improving inference efficiency.
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FlowTool improves efficiency and performance in image editing by modeling parameters directly without autoregressive reasoning, making it suitable for real-time applications.
The paper explores the linearity in Large Language Models (LLMs) by showing that combining inputs from different text streams leads to a superposition of next-token distributions. It suggests that this linearity is an inherent property of the Transformer architecture and can be restored through fine-tuning, allowing for generating two coherent continuations from one forward pass.
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6 days ago