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AI self-heals broken UI locators using fine-tuned Qwen3.5-2B model

A new framework called Optics Framework has been developed to enable AI models to self-heal broken locators in applications. This system sends failed locators, screen data, and screenshots to an AI model, which then identifies the correct UI element. The author experimented with fine-tuning a 2 billion parameter model, Qwen3.5-2B, using two methods: direct weight editing and LoRA. The LoRA method showed more significant improvements, particularly for purpose-based locators, and was successfully integrated into Optics Framework to operate on a Google Pixel 4a. AI

IMPACT Enables more robust UI automation by allowing AI to dynamically fix broken element locators.

RANK_REASON The item describes a framework and a method for improving UI automation, not a core AI model release or research paper.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI self-heals broken UI locators using fine-tuned Qwen3.5-2B model

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26 / 100
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Tool
The item describes a framework and a method for improving UI automation, not a core AI model release or research paper.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, model release
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · chinmayajha ·

    Self-heal broken locators with a 2B model on your own GPU

    <p>When a step cannot find its element, Optics Framework can ask an AI model to find it. This is AI self-heal. Optics Framework sends the failed locator, the rows of the screen and a screenshot to the model. The model selects the correct row. The model can run on any OpenAI-compa…