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FaSTA^*: Fast-Slow Toolpath Agent with Subroutine Mining for Efficient Multi-turn Image Editing

Advait Gupta, Rishie Raj, Dang Nguyen, Tianyi Zhou

2025-06-27

FaSTA^*: Fast-Slow Toolpath Agent with Subroutine Mining for Efficient
  Multi-turn Image Editing

Summary

This paper talks about FaSTA*, a new AI system that helps edit images efficiently by combining fast planning using language models with careful searching techniques to create detailed steps for editing.

What's the problem?

The problem is that editing images over multiple steps can be slow and expensive when AI tries to plan every detail at once, making it hard to complete complex changes quickly and accurately.

What's the solution?

The researchers built a system that uses language models to quickly plan the big picture steps of the editing process and then applies a search algorithm called A* to find the best detailed editing paths within those steps, balancing speed and accuracy while saving on costs.

Why it matters?

This matters because it makes AI-powered image editing faster and more affordable, allowing users to make complicated edits through multiple steps without waiting too long or using a lot of computing power.

Abstract

A neurosymbolic agent combines language models for fast subtask planning with A$^*$ search for detailed toolpaths, creating a cost-efficient multi-turn image editing solution.